Upper Paraguay River Basin GIS Database

Transcrição

One Waterfowl Way - Memphis, TN 38120,
USAwww.ducks.org/conservation/latinamerica.asp
- Expanding the Pilot Project -
- Expanding the Pilot Project Edited by
Mario Cardozo
Dawn Browne
Montserrat Carbonell
Prepared by the “Upper Paraguay River Basin GIS Database Consortium”
Bolivia
Brazil
Paraguay
Pamela Rebolledo
Fábio Ayres
Aníbal Aguayo
Heidi Resnikowski
Luiz Benatti
Rob Clay
Julia Boock
Claudia Mercolli
Lindalva Cavalcanti
Laura Rodríguez
Mário Dantas
Oscar Rodas
Gislaine Disconzi
Wolf Eberhardt
Eliani Fachim
Nelson Laturner
Bill Liu
Humberto Maciel
Carlos Padovani
Sylvia Torrecilha
Ayr Trevisanelli
U.S.A.
Dawn Browne
Mario Cardozo
Kristine Kuhlman
Montserrat Carbonell
Dick Kempka
Nancy Thompson
December 2004
Printed by:
Ducks Unlimited, Inc., Memphis, TN, U.S.A.
Prepared with financial assistance of Ducks Unlimited, Inc., USDA Forest Service and US Fish and
Wildlife Service
Copyright:
The organizations responsible for this publication have waived copyright.
ISBN: 1 932052 17 8
Suggested citation:
Cardozo, M., Browne, D. & Carbonell, M. (Eds.) 2004. Upper Paraguay River Basin GIS Database,
Expanding the Pilot Project. Ducks Unlimited, Inc., Memphis, TN, USA.
Available from:
Ducks Unlimited, Inc., One Waterfowl Way, Memphis, TN 38120-2351, U.S.A.
http://www.ducks.org/conservation/latinamerica_projects.asp
The presentation of material in this book and the geographical designation employed do not imply
the expression of any opinion whatsoever on the part of Ducks Unlimited, Inc. concerning the
legal status of any country, area or territory, or concerning the delimitation of its boundaries or
frontiers.
The information contained in this book and accompanying maps are unsuited for, and shall not be
used for any regulatory purpose of action, nor shall the report or accompanying maps be the basis
for any determination relating to impact assessment or mitigation.
2004
Contents
1. INTRODUCTION/ INTRODUCCIÓN /INTRODUÇÃO ............................................ 1
2. EXPANDING THE PILOT PROJECT ......................................................................... 7
2A.
RELATÓRIO TÉCNICO DE ATIVIDADES DA ECOTRÓPICA NA ESTRADA P ARQUE
T RANSPANTANEIRA ...................................................................................... 7
2B.
LAND C OVER C LASSIFICATION FOR THE UPPER P ARAGUAY RIVER BASIN P ILOT
P ROJECT AREA.......................................................................................... 40
2C.
UPPER P ARAGUAY RIVER INUNDATION P REDICTION USING RAINFALL AND NDVI:
BASIN AND SIX SUB BASIN MODELS ................................................................. 69
3. FURTHER CONSERVATION EFFORTS IN THE UPRB........................................ 87
3A.
3B.
BOLIVIA: RESULTS OF THE P ANTANAL P ROGRAM IN BOLIVIA (WWF BOLIVIA) ....... 87
BRAZIL: P LANNING AND MANAGEMENT OF THE “NASCENTES DO RIO T AQUARI”
STATE P ARK............................................................................................. 89
3C.
BRAZIL: FLOOD MONITORING IN THE P ANTANAL WETLAND........................... 95
3D.
BRAZIL: RE -DRAWING THE P ANTANAL WETLAND DELINEATION IN BRAZIL, BOLIVIA
AND P ARAGUAY ........................................................................................ 98
3E .
3F.
BRAZIL: FIRE MONITORING AND ANALYSIS FOR THE BRAZILIAN P ANTANAL......... 103
P ARAGUAY: USE OF REMOTE SENSING TO P LAN WATERBIRD C ONSERVATION IN THE
C ENTRAL P ARAGUAYAN C HACO ................................................................... 110
4. ACKNOWLEDGEMENTS ....................................................................................... 120
This page left blank intentionally
1. INTRODUCTION/ INTRODUCCIÓN /INTRODUÇÃO
The results of the work conducted for the advancement of the “Upper Paraguay River
Basin GIS Database Project” (UPRB Project) are compiled in the present report. During
the Pilot Project (2000-2003) remote sensing and geographic information system (GIS)
techniques were applied to a trinational pilot area.
These methods were tested and
adjusted, and environmental data of regional significance for resource management of
the UPRB were obtained.
The results of the Pilot Project were published in 2003,
including descriptions of the methods employed and the GIS data produced1. The report
also
emphasized
the
challenge
presented
when
working
with
sixteen
partner
organizations in five countries, Bolivia, Brazil, Paraguay, Canada and the U.S.A. Because
the main goal of the project was to build technical capacity, promote transboundary
cooperation and standardization of methods for easy sharing of information, the results
of the Pilot Project should not be measured only by its products, but also by the network
of professionals formed and the GIS capacity built in each of the partner organizations.
The wider application of methods, data and results led to the successful implementation
of conservation projects in the UPRB.
This second report is a compilation of the Pilot
Project results and ancillary information generated through conservation projects
implemented by the different partner organizations.
Since
the
completion of the Pilot Project in 2003, the consortium of partner
organizations has completed a number of additional studies including an impact
analysis along the Transpantaneria highway in Mato Grosso, Brazil, mapping vegetation
and land use (Section 2a); a land cover classification system for the UPRB, for use with
remotely sensed data (Section 2b);
and a model for river water level prediction using
Normalized Difference Vegetation Index (NDVI), precipitation and river water level data
for several sub-basins in the UPRB (Section 2c)2.
GIS and remote sensing are technologies broadly employed as resource-management
tools, and the methods used, data gathered and results obtained through the Pilot
Project and ancilliary activities have already been applied to conservation projects by
different partners in South America.
Only a few examples have been included in this
CD-atlas to provide an idea of the potential application of a GIS database for the
conservation, management and sustainable use of natural resources in the UPRB. These
include the delineation of buffer zones and environmental zoning for the management
plan for the Taquari State Park in Mato Grosso do Sul, Brazil (Section 3b); an analysis of
maximum and minimum inundation areas for four sub-basins of the Brazilian UPRB
1
Browne, D., Carbonell, M. & Kempka,D. (Eds.) 2003. Upper Paraguay River Basin GIS Database, Pilot Project I.
Ducks Unlimited, Inc., Memphis, TN, USA.
2 The editors of this report have made only minor changes to the papers and are not responsible for their
contents; for full versions or for more information about each study please contact the corresponding authors.
1
(Section 3c);
preliminary results of wetland delineation (Section 3d) a study of fire
incidence (Section 3e); and a classification of wetlands in the central Chaco region of
Paraguay (Section 3f).
As a complement to this report, a CD-atlas was prepared including an interactive map
with selected data generated through the Pilot Project and ancilliary activities in which
these datasets can be viewed within a simple ArcGIS desktop application.
To
demonstrate the usefulness of analyzing environmental data in GIS format, this
application allows the user to select and display different datasets of relevance for
conservation in the UPRB.
The complete datasets from the UPRB Project have not been
included in this CD-atlas due to size limitations, but are available through an FTP server
accessible via the internet.3
3
Please contact [email protected] or [email protected] for FTP access information.
2
Introducción
Los resultados del trabajo realizado para expandir el proyecto “Upper Paraguay River
Basin GIS Project” (Proyecto UPRB) han sido compilados en el presente informe. Durante
el Proyecto Piloto (2000-2003) técnicas de sensoramiento remoto y sistemas de
información geográfica (SIG) fueron aplicadas a un área piloto trinacional.
En el
proceso, estos métodos se evaluaron y ajustaron, obteniéndose datos ambientales de
importancia regional para el manejo de los recursos de la Cuenca Alta del Rio Paraguay
(CARP).
Los resultados del Proyecto Piloto fueron publicados en 2003 en un informe
describiendo los métodos empleados y datos de SIG generados4.
En ese informe
también se enfatizó el desafío que representó trabajar con 16 organizaciones en cinco
países: Bolivia, Brasil, Paraguay, Canadá y los Estados Unidos. El propósito primario del
proyecto ha sido la capacitación técnica, la promoción de cooperación transfronteriza y
la estandarización de métodos para facilitar el intercambio de información, por lo tanto
los resultados del Proyecto Piloto no han de medirse sólo por sus productos, sino
también por la red de profesionales formada, la capacitación en SIG lograda, y la más
amplia aplicación de estos métodos, datos y resultados a la exitosa implementación de
proyectos de conservación en la CARP. Por tanto, este informe es una compilación de
los resultados del Proyecto Piloto y los proyectos de conservación desarrollados por las
distintas organizaciones involucradas.
Desde la finalización del Proyecto Piloto en 2003, el consorcio de organizaciones del
Proyecto UPRB ha completado varios estudios adicionales tales como: un análisis de
impacto ambiental a lo largo de la carretera “Transpantaneira” en Mato Grosso, Brasil,
incluyendo mapeo de la vegetación y uso de la tierra (Sección 2a); un sistema de
clasificación de cobertura terrestre para la CARP y uso con datos de sensores remotos
(Sección 2b); y un modelo de predicción de nivel de río para algunas sub-cuencas de la
CARP, usando “Normalized Vegetation Difference Index” (NDVI), precipitación y datos
historicos de nivel de río (Sección 2c)5.
Las tecnologías de SIG y sensoramiento son ampliamente utilizadas como herramientas
para el manejo de recursos, y los métodos empleados, datos recolectados y resultados
obtenidos en el Proyecto Piloto y actividades adicionales ya han sido aplicados a
proyectos de conservación por las distintas organizaciones participantes en América del
Sur.
Sólo una selección de estos proyectos ha sido incluida en este informe para
mostrar las aplicaciones potenciales de una base de datos en SIG para conservación,
4
5
Los editores de este informe sólo han hecho cambios mínimos a los trabajos incluidos y no son responsables
por sus contenidos; para versiones completas o más información sobre estos trabajos, por favor contacte a los
autores correspondientes.
3
manejo, y uso sustentable de recursos naturales en la CARP. Estos proyectos incluyen la
delimitación de zonas de amortiguamiento y zonificación ambiental para el plan de
manejo del Parque Estadual Taquari en Mato Grosso do Sul, Brasil (Sección 3b); un
análisis de área de inundación máxima y mínima para cuatro sub-cuencas de la sección
brasileña
de
la
CARP
(Sección
3c);
resultados
preliminares
de
estudios
sobre
delimitación de humedales (Sección 3d); y distribución de incendios (Sección 3e); y una
clasificación de humedales en la región central del Chaco paraguayo (Sección 3f).
Como complemento a este informe, se ha preparado un CD-atlas incluyendo un mapa
interactivo con parte de los datos generados en el Proyecto Piloto y varias actividades
relacionadas. En este mapa los datos pueden verse en una aplicación simple de ArcGIS
desktop.
aplicación
Para demostrar la utilidad de analizar datos ambientales en formato SIG, esta
permite
seleccionar
y
visualizar
diferentes
datos
de
relevancia
para
conservación en la CARP. Los datos completos del Proyecto UPRB no han sido incluidos
en el CD-atlas por limitaciones de espacio, pero están disponibles a través de un
servidor FTP por internet6.
6
Contacte a [email protected] o a [email protected] para información sobre accesso al servidor de
FTP.
4
Introdução
Os resultados do trabalho realizado para a expansão do projeto “Upper Paraguay River
Basin GIS Database Project” (Projeto UPRB) foram compilados no presente relatório.
Durante o Projeto Piloto (2000-2003) técnicas de sensoreamento remoto e sistemas de
informação geográfica (SIG) foram aplicadas a uma área piloto trinacional. No processo,
estes
métodos
foram
avaliados
e
ajustados,
obtendo-se
dados
ambientais de
importância regional para o manejo dos recursos da Bacia do Alto Paraguai (BAP).
Os
resultados do Projeto Piloto foram publicados num relatório sobre os métodos usados e
os dados de SIG gerados7.
Nesse relatório também se enfatizou o desafio que
representou trabalhar com 16 organizaçõoes em cinco países: Bolivia, Brasil, Paraguai,
Canadá e Estados Unidos.
Como o propósito primário do projeto tem sido de
capacitação técnica, promoção da cooperação transfronteriza e estandardização de
métodos para facilitar o intercâmbio de informação, os resultados do Projeto Piloto não
devem medir-se só pelos seus produtos, mas também pela rede de profissionais
formada, a capacitação em SIG obtida, e uma aplicação mais ampla dos métodos, dados
e resultados à bem sucedida implementação de projetos de conservação na BAP.
Por
tanto, este relatório é uma compilação dos resultados do Projeto Piloto e projetos de
conservação desenvolvidos pelas organizações envolvidas.
Desde a finalização do Projeto Piloto em 2003, o consórcio de organizações do Projeto
UPRB completou vários estudos adicionais como: uma análise de impacto ambiental ao
longo da estrada parque “Transpantaneira” no estado de Mato Grosso, Brasil, incluindo o
mapeamento da vegetação e uso do solo (Secção 2a); um sistema de classificação da
cobertura terrestre para a BAP e uso com dados de sensores remotos (Secção 2b); e um
modelo de de nível de rio para algumas sub-bacias da BAP, usando “Normalized
Vegetation Difference Index” (NDVI), precipitação e dados anteriores de nível de rio
(Secção 2c) 8.
As tecnologias de SIG y sensoreamento remoto são amplamente utilizadas como
ferramentas para o manejo de recursos, e os métodos usados, dados coletados e
resultados obtidos no Projeto Piloto e atividades adicionais já foram aplicados a projetos
de conservação na América do Sul pelas organizações participantes.
Apenas uma
seleção destes projetos foram incluídos neste relatório para mostrar as aplicações
potenciais de uma base de dados em SIG para conservação, manejo, e uso sustentável
dos recursos naturais na BAP.
Estes projetos incluem a delimitação de zonas de
amortecimento y zonificação ambiental para o plano de manejo do Parque Estadual
7
Os editores deste relatório só fizeram mudanças mínimas aos trabalhos incluídos e não são responsáveis
pelos seus conteúdos; para versões completas ou mais informação sobre estes trabalhos, por favor contacte
8
aos autores correspondentes..
5
Taquari em Mato Grosso do Sul, Brasil (Secção 3b); uma análise da máxima e mínima
área de inundação para quatro sub-bacias da seção brasileira da BAP (Secção 3c);
resultados preliminares de estudos sobre delimitação de zonas húmidas (Secção 3d) e
distribução de incêndios (Secção 3e) na BAP; e uma classificação de zonas húmedas na
região central do Chaco paraguaio (Secção 3f).
Como complemento a este relatório, um CD-atlas foi preparado incluindo um mapa
interativo com parte dos dados gerados no Projecto Piloto e actividades relacionadas.
Neste mapa os datos podem ser vistos numa simples aplicação de ArcGIS desktop.
Para
demostrar a utilidade de analizar dados ambientales em formato SIG, esta aplicação
permite seleccionar e visualizar diferentes dados de relevância para conservação na BAP.
Os dados completos do Projeto UPRB não foram incluídos no CD-atlas por limitações de
espaço, mas estão disponíveis através de um servidor FTP na internet9.
9
Por favor, contacte [email protected] ou [email protected] para informação sobre acesso ao servidor
FTP .
6
2. EXPANDING THE PILOT PROJECT
2A. R ELATÓRIO TÉCNICO
T RANSPANTANEIRA
DE ATIVIDADES DA
E COTRÓPICA
NA
E STRADA P ARQUE
WOLF EBERHARD10
S UMMARY
This document reports the results of the project conducted by Ecotrópica (Fundação de
Apoio à Vida nos Trópicos) with the support of Ducks Unlimited, Inc. (DU) to gather data
related to the current state of land use and vegetation along the “Estrada Parque
Transpantaneira” (Highway-Park Transpantaneira) (EPT), for a Geographic Information
System (GIS) database.
In a first phase, project activities focused on the:
−
Upgrade of hardware and software for the GIS laboratory,
−
Compilation of ancillary data, and their metadata, related to the cartography of the
Upper Paraguay River Basin section in the state of Mato Grosso, and
−
Creation of an index of aerial photography for the same area.
During the second phase of the project, anthropogenic and/or natural impacts on the
vegetation along the EPT were assessed, for which land cover was mapped in detail and
properties were located in the study area.
R ESUMO
O presente relatório refere-se às atividades da Ecotrópica (Fundação de Apoio à Vida
nos Trópicos) desenvolvidas em parceria com a Ducks Unlimited, Inc. (DU) com o
objetivo de realizar levantamento de dados e desenvolver estudos sobre o estado atual
da cobertura vegetal, ocupação e uso do solo da Estrada Parque Transpantaneira (EPT)
para colaborar na criação do SIG Pantanal.
Numa primeira fase os trabalhos realizados focalizaram os seguintes aspectos:
−
Otimização da sala de geoprocessamento com a colocação de alguns itens de
infraestrutura,
10
Fundação Ecotrópica, Cuibá, Mato Grosso, Brazil; [email protected]. Este relatório contém treixos de
relatórios parciais internos realizados para a Ecotrópica durante 2002-2003 pelo profissional E. A. Silveira.
7
−
Atualização de softwares e dos equipamentos de informática para as atividades
técnicas, administrativas e de gestão dos recursos, e
−
Coleta de dados secundários abordando a compilação de metadados de referências
cartográficas e confecção de um índice de aerofotografias, ambos referentes à
região da Bacia do Alto Paraguai, no Estado de Mato Grosso.
Numa segunda fase, as atividades do projeto enfocaram a avaliação dos impactos
antrópicos e/ou naturais sobre a vegetação ao longo da EPT, bem como o mapeamento
da vegetação e a localização dos limites de propriedades ao longo da Unidade de
Conservação com os nomes dos respectivos donos e, ainda, a digitalização da EPT e
estradas secundárias.
I NTRODUÇÃO
A existência de um número reduzido de informações sobre o Pantanal levou a Ducks
Unlimited Inc. (DU) a estimular a criação de um Sistema de Informação Geográfica (SIG)
com dados sobre a região. A idéia foi contemplar a região do Pantanal do Brasil, da
Bolívia e do Paraguai, numa proposta de trabalho conjunto. Foram, então, realizadas
reuniões de estudo e vários treinamentos para nivelamento de conhecimentos sobre o
uso de programas específicos de computador, para capacitação do pessoal dos três
países para dar início à criação do SIG Pantanal.
Com a finalidade de adequar técnicas e procedimentos relacionados com trabalhos de
campo e tratamento de imagens de satélite, foi realizado o Projeto Piloto I que
contemplou uma região comum ao Brasil, Bolívia e Paraguai. O Projeto Piloto I foi
concluído com sucesso e os resultados já foram divulgados através de trabalhos
impressos.
Com base nos resultados obtidos com a experiência do Projeto Piloto I foram iniciadas
atividades com vistas à realização deste estudo ao longo da transpantaneira.
Este
projeto visa contemplar o Estado de Mato Grosso e teve suas atividades voltadas para
uma Unidade de Conservação: a Estrada Parque Transpantaneira que está localizada no
município de Poconé, sudoeste do Estado de Mato Grosso e tem início no quilómetro
(km) 17 da estrada MT 060, no posto de fiscalização da FEMA e IBAMA.
No início da década de 70 teve início a construção da parte da MT 060, Poconé-Porto
Joffre, que passou a se chamar Transpantaneira. Ela faz a ligação da cidade de Poconé
ao complexo hoteleiro Porto Joffre na margem direita do Rio Cuiabá, com uma extensão
de 146 km com 116 pontes.
A Transpantaneira é um dique construído em pleno
Pantanal, na direção geral norte-sul, que represa a água durante o período da cheia que
acontece na direção geral leste-oeste. Com a finalidade de permitir a passagem da água
sem destruir o aterro, foram deixadas 116 passagens, onde algumas são naturais como
8
a do Rio Bento Gomes, Rio Pixaim, Rio Cassange e inúmeros corixos. A construção deste
aterro, de alto impacto à zona inundável, permite, aos criadores de gado da região,
escoar a sua produção durante quase o ano todo, bem como, facilita o acesso de
turistas até o Rio Cuiabá, no final da Transpantaneira.
O material necessário à construção do aterro foi retirado de caixas de empréstimo
localizadas à esquerda e à direita da Transpantaneira. As cavidades resultantes da
retirada de terra, alguns com mais de 300 metros cúbicos (m3) cada um, resultaram em
reservatórios de água que, ao longo do tempo, se transformaram em sistemas de
criação de vários tipos de pequenos animais (crustáceos, moluscos, peixes, pequenos
répteis) e numerosas plantas que participam da dieta preferencial de muitos pássaros,
répteis e mamíferos. Em conseqüência da fartura de alimento, durante o período da
vazante, ocorre uma concentração natural da fauna ao longo da Transpantaneira criando
assim um atrativo para visitação e turismo. Houve um momento em que a concentração
de jacarés (Caiman yacare) se transformou numa tragédia, pois muitas centenas deles
foram atropelados pelos veículos que transitavam pela Transpantaneira.
Em 1996 a
Estrada Transpantaneira foi transformada, pelo Decreto Estadual nº 1028, de 26 de
julho, em uma Unidade de Conservação Estadual: a Estrada Parque Transpantaneira. No
presente estudo sobre esta Unidade de Conservação, os impactos foram avaliados
apenas
qualitativamente,
sendo
considerada
a
presença
de
espécies
exóticas
(invasoras), áreas queimadas, placas de publicidade, erosão do aterro, abertura de
drenos, construção de diques e desmatamentos.
M ETODOLOGIA
Metadatos
Depois de escolhido e separado o material cartográfico de interesse para a Bacia do
Alto Paraguai (BAP), foi contratado um técnico para fazer o lançamento de 171 registros
de metadados em “software” apropriado, o MetaLite.
Após a conferência de todos os
registros, foi gerada uma cópia do banco de dados MetaLite.dbf. Este arquivo poderá ser
consultado e atualizado através do MS Access 2000 ou então poderá ser colocado no
Programa de Metadados (MetaLite) substituindo o MetaLite.dbf original, previamente
renomeado para MetaLite.old. Esta opção permite ao Coordenador do SIG Pantanal
escolher os registros de maior interesse e gerar apenas os arquivos de exportação
desejados.
Pluviometria
Em virtude da indisponibilidade de dados atuais sobre estações e níveis pluviométricos
na região da EPT, foi utilizado um mapa (Figura 1) de Precipitação Média – Mês de Junho
de 1979 do trabalho Estudo de Desenvolvimento Integrado da Bacia do Alto Paraguai
9
(EDIBAP),
que
apresenta
características
semelhantes
às
do
semi-árido,
com
precipitações anuais em torno de 1100 milimetros (mm).
Figura 1. Mapa de precipitação na BAP, região de Mato Grosso
Fotoíndices
A região do Pantanal do Brasil e a BAP estão contidas no interior do retângulo formado
pelas seguintes coordenadas geográficas: W60°, S14° e W52°30´, S19°, o que significa
um mosaico de 25 folhas na escala de 1:250 000 da base cartográfica oficial. Com base
nestas coordenadas e no contorno da BAP para a região de Mato Grosso, foi feita uma
solicitação à 5ª Divisão de Levantamento do Exército para confecção dos fotoíndices
necessários para a cobertura da área. Foram gerados 113 fotoíndices com uma
cobertura de 00°30´x 00°30´, cada um, equivalente a uma folha na escala de 1:100 000
da base cartográfica oficial. Os fotoíndices, depois de identificados, conforme a grade
da Figura 2, foram escanerizados em scanner de rolo marca Ocê, modelo 9400,
com
resolução de 300 dpi, em preto e branco e armazenados em CD-ROM com arquivos no
formato tif.
10
Figura 2. Grade de localização e distribuição dos fotoíndices
Avaliação dos Impactos Ambientais na EPT
Os impactos ambientais foram avaliados qualitativamente, portanto, não foi realizada
uma avaliação da sua grandeza ou extensão. Foi anotada somente a presença do
impacto e descritas algumas considerações sobre a sua importância. Entre os impactos
ambientais
observados
na
EPT,
destacam-se
a
presença
de
espécies
exóticas
(invasoras), queimadas, placas de publicidade, erosão do aterro, abertura de drenos,
construção de diques e desmatamento.
Mapeamento Fitofisionômico
A caracterização da vegetação ao longo da Estrada Parque Transpantaneira, foi realizada
verificando-se os tipos vegetacionais que ocorrem na margem da Estrada e em
incursões
nas
estradas
vicinais,
principalmente
naquelas
que
dão
acesso
às
propriedades. Assim, o efeito de borda e as áreas degradadas às margens da Estrada,
que impedem a visualização dos tipos fitofisionômicos, foram contornados.
11
A coleta de dados teve início com viagens de campo realizadas no período de dezembro
de 2002 a janeiro de 2003 onde, partindo-se de Porto Joffre, sistematicamente o veículo
foi parado sobre cada ponte com a finalidade de colher suas coordenadas métricas
(Universal Transverse Mercator - UTM) e anotar informações com fotografias sobre a
vegetação. As coordenadas foram registradas em um Garmin GPSMAP 195 configurado
para UTM com Datum WGS84. As fotografias digitais foram obtidas através de uma
câmera Kodak DC 290 Zoom.
Com a finalidade de melhorar a autonomia em horas de trabalho da câmera Kodak DC
290 Zoom, foi realizada uma adaptação num inversor de corrente, marca Trancham,
com entrada de 12 VCC e saída de 110 VCA com 280 W de potência, para que pudesse
ser plugado no sistema elétrico (acendedor de cigarros) de qualquer veículo.
Foi realizada, também, uma pequena modificação para que o cabo do Digital Câmera AC
Adapter pudesse receber uma extensão de 10 m
para permitir ao operador sair do
veículo e subir em cima da capota para obter melhor ângulo de visualização.
Esta modificação permitiu que a câmera fosse utilizada indefinidamente e sem
necessidade da utilização das suas baterias originais (Figuras 3 e 4). O sistema também
recebeu uma tomada para plugar o Garmin GPSMAP 195 que tem um grande consumo
de energia. Seis baterias AA permitem uma autonomia de apenas 6 (seis) horas de
operação contínua. O sistema foi testado em automóvel, barco e avião monomotor.
Sistema de inversão do corrente
Plug DC (12V) para
GPSMAP 195
Inversor de corrente
Adaptador AC (127V)
para câmera
Extensão com 10,0 m
de comprimento
Plug para sistema
elétrico veicular
Garmin GPSMAP 195
Antena externa
GPSMAP 195
Conector DC (6V)
para câmera
Figura 3. Fonte de energia para funcionamento simultâneo de Garmin GPSMAP 195 e da
câmera digital Kodak DC 290 Zoom
12
Painel trazeiro do inversor de corrente
Plug DC para
GPSMAP 195
Adapador AC para
câmera DC 290 Zoom
Inversor de corrente
Figura 4. Conexão do Adaptador AC para a câmera Kodak DC 290 Zoom
Na seqüência, foram utilizadas as folhas Poconé, MIR 404 e Ilha Camargo, MIR 418, do
Plano de Conservação da Bacia do Alto Paraguai (PCBAP) (PNMA, 1997), na escala de
1:250 000, para suporte inicial e orientação no estudo da vegetação existente ao longo
da EPT (Figura 5). Para a digitalização do curso da EPT e estradas secundárias, foram
utilizadas as mesmas folhas, porém, não do PCBAP e sim da base cartográfica oficial
(Diretoria do Serviço Geográfico do Exército, ou DSG). Estes mapas foram escanerizados
num scanner de rolo marca Ocê, modelo 9400, com 300 dpi de resolução e
posteriormente foram georreferenciadas, no IDRISI (SIG da ClarkLabs), usando quatro
interseções do grid UTM como pontos de controle. Estes bitmaps foram importados
para o CartaLinx (Software para digitalização de vetores da ClarkLabs) e usados como
“backdrop
image”
para
obtenção,
por
digitalização
“on
screen”,
dos
vetores
correspondentes à EPT e estradas secundárias.
Num segundo momento foram utilizadas duas imagens de satélite Landsat Enhanced
Thematic Mapper (ETM)+7, bandas 5, 4 e 3 (Red, Green, Blue – RGB), WRS 227/071, de
julho de 2000, correspondente à região de Poconé e WRS 227/072, de maio de 2001,
correspondente à região de Ilha Camargo. As duas imagens foram unificadas num
mosaico. Os “layers” origindados pelo CartaLinx foram carregados no ArcView 3.2.a,
onde a nova “view” foi projetada para UTM com Datum WGS84. A imagem (mosaicada)
também foi importada para o ArcView e georreferenciada com auxílio do “align tool”.
Com a ferramenta apropriada foram gerados dois “buffers”: o primeiro de 1 km para
cada lado da EPT, que tinha sido decidido de comum acordo entre DU, ECOTRÓPICA e
FEMA, como área de trabalho e tem uma superfície de 29 463 ha; o segundo “buffer”,
de 10 km, surgiu de uma necessidade estética para melhorar a apresentação, porque o
“buffer” de 1 km é muito estreito e longo e, em função da escala do mapa, quase não se
torna visível.
13
Figura 5. Mapa preliminar da vegetação ao longo da EPT (PCBAP).
14
Inicialmente foi realizada uma classificação não supervisionada das imagens com a
ferramenta “categorize”. O resultado não foi satisfatório considerando o detalhe de
mapeamento requerido, motivo pelo que se procedeu a realizar uma interpretação visual
apoiada nos dados de observação no campo e fotografias.
Utilizando-se as ferramentas de desenho do ArcView foram digitalizadas todas as
unidades vegetacionais, bem como as alterações antrópicas, ex.: área urbana, garimpo,
depósito de lixo, etc. com o respectivo registro na tabela do banco de dados (Figura 6).
Figura 6. Resultado da digitalização das unidades vegetacionais dentro do limite de 10
km para cada lado da EPT.
Para facilitar a análise da composição das unidades vegetacionais foram utilizadas
algumas fotografias justapostas, obtidas em seqüência, que ilustram a vegetação com
maior amplitude (Figuras 7, 8, 9 e10).
15
Figura 7. Fotografia central de um grupo de cinco fotos.
Figura 8. Unidade vegetacional composta por 5 fotografias. Vista de um “capão”.
Figura 9. Unidade vegetacional composta por 7 fotografias num ângulo de 180°. A EPT
é visível no estremo esquerdo, bem como, no estremo direito da composição. Exemplo
de um cerradão (savana florestada).
Figura 10. Exemplo de campo inundável (savana gramíneo-lenhosa) com “capões” ao
fundo. Nesta composição de 7 fotografias pode-se observar o represamento das águas
causado pelo aterro da EPT.
16
Na “view” correspondente ao mapeamento da fitofisionomia da EPT foram colocadas,
somente
como
ilustração,
três
fotografias
daquelas
que
foram
utilizadas
na
identificação das unidades vegetacionais. Elas foram relacionadas com as classes
correspondentes no mapa de fitofisionomias para mostrar o tipo de vegetação
predominante naquela região. Através da ferramenta “Hot Link”, as fotografias foram
associadas
a um símbolo imitando um disparo de flash de máquina fotográfica e
correspondem àquela classe vegetacional onde está localizado o símbolo (Figura 11).
Figura 11. Exemplo de associação de fotografia a uma unidade vegetacional.
Abaixo encontra-se uma relação numérica das fotografias utilizadas, com a descrição
da paisagem correspondente.
−
Foto 01. Floresta estacional semidecidual aluvial (mata ciliar do Rio Cuiabá, Porto
Joffre).
−
Foto 02. Comunidade pioneira em primeiro plano e ao fundo Cambarazal (Fazenda
Rodeio da Campina Grande, antiga Fazenda Joffre).
17
−
Foto 03. Comunidade pioneira (espinheiral) (Fazenda Rodeio da Campina Grande).
−
Foto 04. Vista parcial de savana gramíneo lenhosa (campo inundável), ao fundo
Cambarazal (Região dos Campos de Joffre).
−
Foto 06. Savana gramíneo lenhosa (campo inundável). (Região dos Campos de Joffre,
próximo da divisa com o Leirinho)
−
Foto 08. Savana gramíneo lenhosa (campo inundável); em primeiro plano a
Brachiaria
subquadripara, espécie de origem africana que foi introduzida no
Pantanal e é considerada uma invasora agressiva.
−
Foto 09. Savana gramíneo lenhosa (campo inundável); margem da Transpantaneira
com duas espécies invasoras Panicum maximum (campim-colonião) e Brachiaria
subquadripara (capim-braquiaria).
−
Foto 10. “Murundu”, pequeno monte de terra com vegetação mais alta, cercado pelo
campo inundável.
−
Foto 11. Vista da Estrada Parque Transpantaneira e ao fundo uma “cordilheira de
mata”, extensa faixa de floresta.
−
Foto 12. Cambarazal, formação arbórea com dominância de Cambará (Vochysia
divergens).
−
Foto 13. Vista parcial de um cambarazal, com espécies pioneiras de embaúba
(Cecropia pachystachya).
−
Foto 14. Cambarazal invadindo um campo inundável.
−
Foto 15. Cambarazal adulto, apresentando dois estratos, o arbóreo formado por
cambará (Vochysia divergens) e o arbustivo com outras espécies.
−
Foto 16. Vista geral de pastagem manejada, fazenda Campo Largo.
−
Foto 17. Pastagem manejada, ao fundo a Savana Florestada (Cerradão); fazenda
Campo Largo
−
Foto 18. Pastagem manejada.
−
Foto 19. Pastagem manejada. Fazenda Campo Largo.
−
Foto 20. Contato entre Floresta Estacional Semidecidual e Comunidades Pioneiras
(próximo ao Leirinho).
18
−
Foto 01
Foto 02
Foto 03
Foto 04
Foto 06
Foto 07
Foto 08
Foto 09
19
Foto 10
Foto 11
Foto 12
Foto 13
Foto 14
Foto 15
Foto 16
Foto 17
20
Foto 19
Foto 18
Foto 20
Limites e Propriedades
A falta de demarcação das propriedades na região do Pantanal envolve questões
relacionadas à redistribuição de terras entre herdeiros. Outro fator que contribuiu para a
atual situação da questão fundiária, ocorreu após a abertura da Transpantaneira, onde
os proprietários que ficaram sem acesso à estrada, acabaram acordando ou trocando
lotes de terras para obter o acesso. O custo da demarcação, as dificuldades para a
construção e manutenção das cercas, aliados a outros fatores, levou os proprietários a
acordos verbais. Tais acordos foram possíveis pelo fato de que a maioria dos
proprietários têm parentescos entre si. A região que apresentou os maiores problemas
com demarcação de terras, foi a que compreende o trecho do km 85 (Fazenda Nova
Berlim) até o km 107 (Pousada Recanto do Jaguar), onde cinco proprietários foram
identificados até o momento. Para o levantamento de dados foi organizada uma viagem
de campo que permitiu visitar todas as propriedades que tinham limites com a EPT.
Este trabalho relacionou a existência de 46 propriedades que encostam na EPT, cujos
nomes e proprietários foram cadastrados no banco de dados. A posição dos limites das
propriedades junto da EPT foi registrada no GPSMAP 195, juntamente com todas as
21
pontes. Posteriormente estes dados foram descarregados do GPS para o CartaLinx, a
projeção UTM foi convertida para coordenadas geográficas com Datum WGS84 e
exportados para o ArcView 3.2.a, pelo processo anteriormente descrito. A utilização
destes dados permitiu a elaboração do Mapa de Limites e Propriedades.
R ESULTADOS
Metadados
Foram compilados 171 títulos de referências cartográficas que estão armazenados em
um arquivo *.dbf. Este arquivo poderá ser aberto para consulta e edição dos dados
através do MS Access 2000, bem como poderá ser introduzido no MetaLite para
consultas, alterações e exportação de dados.
Fotoíndices
Foram confeccionados 113 fotoíndices de aerofotos realizadas no período de 1964 a
1967, através do Projeto AF-63-32, AST-10 (Brasil–USA). Uma cópia digital de todos os
índices foi encaminhada em CD_ROM à DU e os originais em papel encontram-se na
Ecotrópica.
Impactos ambientais sobre a EPT
Espécies Exóticas
A presença de espécies exóticas, refere-se à introdução de forrageiras para plantio de
pastagens, que na região são basicamente duas espécies: a Brachiaria subquadripara e a
B. humidicola. A primeira tem ampla dispersão sendo encontrada desde os ambientes
mais alagados, sobre macrófitas aquáticas, até áreas mais secas; enquanto que a
segunda teve sua distribuição restrita apenas às áreas em que foi introduzida. O
controle da B. subquadripara é difícil, uma vez que apresenta crescimento rápido
competindo com as espécies de gramíneas nativas e inclusive com as macrófitas
aquáticas (aguapés). A espécie também é favorecida por proprietários que a plantam
como forma de combater outras espécies invasoras, como o algodão-bravo (Ipomea
carnea).
Queimadas
As queimadas são outra ameaça às áreas da região, principalmente onde não há gado
bovino, pois esses locais acumulam biomassa rapidamente e o fogo pode alastrar-se ali
com rapidez dificultando o seu controle. Os locais onde foram observados vestígios de
fogo estavam em áreas de savana arborizada e parque. Estes tipos de vegetação são
utilizados como áreas de pastagens naturais, sendo que durante o período seco o capim
22
nativo torna-se duro e é recusado pelo gado. A queima provoca o brotamento das
espécies de gramíneas proporcionando a reabilitação da área para o gado.
Publicidade
Placas de publicidade foram colocadas sem nenhum controle dos órgãos competentes e
ao longo da Estrada elas estão penduradas em árvores e até mesmo fincadas nas áreas
de campo, impedindo a visão da paisagem.
Estas placas variam em tamanho, e anunciam principalmente as pousadas e também
empresas de telefonia. Algumas trazem informações sobre a quilometragem, sendo a
única informação disponível para os usuários porque a
Estrada não é sinalizada. A
maioria das placas foi observada nos primeiros 50 km.
Erosão
Os processos erosivos sobre o aterro da Estrada são pontuais, sendo observados
somente sulcos, não configurando problema grave. Estas alterações foram observadas
principalmente nos desvios, construídos para contornar as pontes quebradas.
Aterros
Os aterros alteram toda a dinâmica hídrica da paisagem dificultando o escoamento das
águas. A EPT é a maior expressão desse impacto, mas também pode ser observado nas
estradas que acessam as sedes das propriedades.
Muitos aterros são construções antigas, o que não chega a ser uma preocupação, pois
os processos de adaptação das espécies às mudanças do meio físico já ocorreram.
A
divisão das propriedades e a abertura de pousadas provocam uma nova demanda por
estradas, o que poderá aumentar este tipo de impacto a médio e longo prazo.
Drenos e diques
A abertura de drenos e construção de diques também causam alterações na dinâmica
hídrica. Este impacto ambiental foi observado na planície do Pantanal antes do início da
EPT (no km 10), em área de uso agropecuário. O barramento das águas pode causar
sérios prejuízos econômicos e ecológicos, pois áreas próximas aos diques permanecem
mais tempo inundadas.
Desmatamentos
Os desmatamentos, embora pouco observados, merecem uma maior atenção, pois estão
ocorrendo nas áreas mais altas, recobertas com vegetação de floresta ou savana
florestada. Estas áreas constituem abrigo para a fauna e para o gado bovino durante a
época de cheia no Pantanal. As áreas desmatadas estão sendo destinadas à pastagem,
com plantio de braquiária, o que reduz a biodiversidade.
23
Assoreamento
Embora não citado entre os impactos ambientais, o assoreamento é um tema muito
discutido entre os proprietários da região. Muitos argumentam que os leitos de rios,
corixos e vazantes estão assoreados e que deveriam ser drenados como forma de
aumentar o escoamento das águas e reduzir o avanço das espécies invasoras
(pombeiros, algodão-bravo, pimenteira, etc.). No entanto, o Pantanal é uma planície de
sedimentação, onde os processos estão em pleno andamento. Ao longo da EPT não há
grandes indícios de assoreamentos, estes são visíveis, principalmente, nas calhas dos
grandes rios que nascem nos Planaltos e que cortam a Planície do Pantanal, como o Rio
Cuiabá e o Rio Paraguai.
Há, entretanto, que se considerar o barramento das águas provocado pelo aterro da EPT
(Oliveira, 1998; Campos Filho, 2002) pois este sim provoca o processo de colmatação
dos canais que drenam as águas. Grandes blocos de biomassa (batumes) ficam presos
aos pilares das pontes e impedem a passagem da água e no período seco a biomassa
morre, deposita-se nas baías, nas caixas de empréstimo e nos canais sob as pontes. As
alterações no meio físico estimulam a colonização por novas espécies nos ambientes em
processo de mudança. Intervenções antrópicas para restabelecer a dinâmica hídrica dos
corixos e vazantes desencadearão novos processos ecológicos, mas não garantem o
retorno das comunidades vegetais que existiram no passado.
Restos de manutenção
Outro impacto, de caráter estético, é o dos restos de madeira, encontrados sob as
pontes, que são constituídos por pedaços de tábuas e vigas que foram abandonados
depois de trabalhos de manutenção. Em todas as pontes foi observado este impacto.
Embora a madeira possa se decompor ao longo do tempo, os restos de madeira causam
uma forte impressão de abandono e falta de consciência ecológica.
A Figura 12 mostra a distribuição percentual dos vários tipos de impactos ambientais
observados na EPT.
Erosão
10%
Placas
15%
Aterro
10%
Dreno
10%
Espécie
exotica
25%
Dique
5%
Desmatamento
10%
Queimada
15%
Figura 12. Impactos ambientais observados na Estrada Parque Transpantaneira.
24
Foi produzido um mapa de vegetação, uso e ocupação da região da EPT, no município
de Poconé, MT, Brasil (Figura 13). A nomenclatura das unidades vegetacionais obedeceu
às normas do Manual Técnico de Vegetação Brasileira do Instituto Brasileiro de
Geografia e Estadística (IBGE) (IBGE, 1992) e a paleta de cores foi especialmente
montada para este estudo. A legenda mostra, além dos símbolos e a descrição de cada
unidade, o número total de unidades de cada classe (Σ) com a correspondente área em
hectares (ha) (Figuras 14 e 15).
25
Figura 13. Mapa de vegetação, ocupação e uso do solo.
26
Figura 14: Legenda dos tipos de vegetação
27
Figura 15: Legenda dos tipos de vegetação (continuação da Figura 14).
28
Observações da Flora da Estrada Parque Transpantaneira
A flora caracterizada ao longo da EPT, pertence em sua grande parte à Savana, sendo os
elementos florestais situados em encraves (cordilheiras e capões). As margens da EPT
geralmente têm influência antrópica, sendo a flora caracterizada como ruderal, portanto
a caracterização foi realizada sempre em unidades menos impactadas e distantes do
efeito de borda da Estrada, com exceção para as comunidades pioneiras. No total foram
observadas 76 espécies, pertencentes a 44 famílias, sendo as mais importantes
Poaceae (6), Bignoniaceae (5), Fabaceae (4) e Mimosaceae (4) (Tabela 1).
Tabela 1. Espécies observadas nas unidades de mapeamento ao longo da Estrada Parque
Transpantaneira, município de Poconé, MT. Fa: Floresta Estacional Semidecidual Aluvial;
Fb: Floresta Estacional Semidecidual da s Terras Baixas; Cb: Floresta Estacional Decidual
das Terras Baixas; Sd: Savana Florestada; Sa: Savana Arborizada; Sp: Savana Parque; Sg:
Savana Gramineo-Lenhosa; Pa: Comunidades Pioneiras; Ag: Agropecuária.
Família/Espécie
Nome regional
Fa
Fb
Cb
Sd
Sa
x
x
Sp
Sg
Pa
Amaryllidaceae
Agave americana L.
x
Anacardiaceae
Astronium fraxinifolium Schott
Gonçaleiro
Myracroduon urundeuva (Enbgl.) Fr.All. Aroeira
x
Annonaceae
Anona dioica St. Hil.
Arixicum
x
Apocynaceae
Aspidosperma australe M. Arg.
Peroba
Aspidosperma cylindrocarpon M. Arg.
Peroba
x
Rhabidadenia pohlii M. Arg.
Thevetia bicornuta M. Arg.
x
Lingua-de-vaca
x
x
x
x
Arecaceae
Acrocomia aculeata (Jacq.) Lodd.
Bocaiuva
Bactris sp.
Tucum
Copernicia alba Morong
Caranda
Scheelea pharelata (Mart) Burret
Acuri
x
x
x
x
x
x
x
Asteraceae
Aspilia latissima Malme
Bignoniaceae
Mirassolzinho
Jacaranda cuspidifolia Mart.
Caroba
Tabebuia aurea (Manso) B. et H.
Paratudo
Tabebuia heptaphylla (Vell.) Tol.
Piúva
Tabebuia sp.
Ipê amarelo
Thevertia bicornuta Muell. Arg.
Leiterinho
x
x
x
x
x
x
x
x
Bombacaceae
Pseudobombax longiflorum (Mart. et
Zucc.)
Embiruçu
29
x
Ag
Família/Espécie
Nome regional
Fa
Fb
Cb
Bombacaceae (cont.)
Pseudobombax marginatum (St. Hil.) Rob. Embiruçu-da-
Sd
Sa
Sp
Sg
Pa
x
mata
Boraginaceae
Cordia glabrata (Mart.) DC.
Louro
x
Bromeliaceae
Bromelia balansae Mez
Gravatá
x
Cactaceae
Cereus peruvianus Mill.
Urumbeba
x
Caes alpinaceae
Bauhinia forficata Link.
Pé-de-boi
x
(branca)
Bauhinia sp.
Pata-de-vaca
Cassia grandis L. f.
Canafístula
x
x
x
Embaúba
x
x
Cecropiaceae
Cecropia pachystachya Trec.
Chrysobalanaceae
Couepia uiti (Mart. et Zucc.) Bth.
Pateiro
x
Licania minutiflora (Sag.) Fritsch
Cedro-d'água
x
Licania parvifolia Huber
Pimenteira
x
Clusiaceae
Rheedia brasiliensis (Mart.) Pl. et Tr.
Cupari
x
Combretaceae
Buchenavia tomentosa Eichl.
Tarumarana
Combretum laxum Jacq.
Pombeiro-branco
x
x
Convolvulaceae
Ipomoea carnea Jacq.
x
x
Algodão-bravo
Cyperaceae
Cyperus giganteus Vahl
Pirizeiro
x
Rhynchospora trispicata (Ness) Steud.
Capim-navalha
x
Dilleniaceae
Curatella americana L.
Lixeira
x
Erythroxylaceae
x
Erythroxylum anguifugum Mart.
Pimenteirinha
x
Sapium obovatum Kl.
Sarã-de-leite
x
Sarã
x
x
E u p h o rbiaceae
Alchornea castaneifolia (Willd.) A. Juss.
Fabaceae
Albizia samam (Jacq.) F. v. M.
Farinha-seca
Dipteryx alata Vog.
Cumbaru
x
Machaerium aculeatum Raddi
Espinheiro
x
Machaerium hirtum (Vell.) Stellf.
Barreirinho
x
x
x
Smilacaceae
Smilax fluminensis Steud.
Japecanga
x
Malphiguiaceae
Byrsonima orbignyana A. Juss.
Marantaceae
Canjiqueira
Thalia geniculata L.
Caeté
x
x
30
x
Ag
Família/Espécie
Melastomataceae
Mouriri guianensis Aubl.
Nome regional
Fa
Roncador
Fb
Cb
Sd
Sa
Sp
Sg
Pa
Ag
x
Mimosaceae
Anadenathera colubrina (Vell.) Brenan
Angico
Inga vera ssp. affinis (DC) TD. Penn.
Ingá
x
Mimosa pellita H. et B.
Espinheiro
x
x
Monimiaceae
Siparuna guianensis Aubl.
Negramina
x
Moraceae
Ficus gardneriana (Miq.) Miq.
Figueira-matapau
x
x
Myrtaceae
Eugenia pitanga (Berg) Nied.
Pitanga
x
Psidium kennedyanum Morong
Araçazinho
x
Ninphaeaceae
Ninphaeae prolifera Wiersema
Lagartixa
x
Ochnaceae
Ouratea sp.
Curte-seco
x
Onagraceae
Ludwigia tomentosa (Cambess.) Hara
Florzeiro
x
Poacea
Brachiaria humidicola (Rend.) Schweich
Braquiária
Paspalum Hydrophilum Henr.
Felpudo
Andropogon bicornis L.
Capim-rabo-de-
x
x
x
burro
Axonopus sp.
Capim-mimoso
x
Brachiaria subquadripara (Trin.) Hitchc. Tanner-grass
Paspalum repens Berg.
x
Capim-fofo
x
x
Polygonaceae
Coccoloba molis Casar
Belém
x
Coccoloba ochreolata Wedd.
Uveira-do-mato
x
Triplaris americana L.
Novateiro
x
x
Pontederiaceae
Eichhornia azurea (Sw.) Kunth.
Camalote
x
Eichornia crassipes (Mart.) Solms
Camalotinho
x
Guapé
x
Pontederiaceae
Pontederia parviflora Alexander
Rubiaceae
Alibertia edulis (L. l. Rich.) A. C. Rich.
Marmelada-bola
Genipa americana L.
Jenipapo
x
x
Fagara hassleriana Chod.
Mamica-deporca
x
x
Sapindaceae
Dilodendron bipinnatum Radlk.
Mulher-pobre
x
Sterculiaceae
Helicteres guazumaefolia H.B.K.
Rosquinha
x
Typhaceae
Typha angustifolia L.
Tabôa
x
31
x
Família/Espécie
Vitaceae
Cissus erosa L. C. Rich.
Nome regional
Fa
Fb
Cipó-de-arraia-
x
x
x
x
Cb
Sd
Sa
Sp
Sg
Pa
x
x
Ag
liso
Vochysiaceae
Vochysia divergens Pohl
Cambará
x
Zingiberaceae
Costus cf. arabicus L.
Cana-do-brejo
x
Observações da Fauna da Estrada Parque Transpantaneira
Foram realizadas observações sobre a fauna ao longo da EPT e nas estradas vicinais que
dão acesso às propriedades. Os locais de maior avistamento de animais foram na
estrada de acesso à Fazenda Pouso Alegre (km 33) e na região dos Campos de Joffre. Os
dados foram separados de acordo com os grupos, sendo que os jacarés são avistados
ao longo de toda a Transpantaneira, principalmente próximo às pontes (Tabela 2).
Tabela 2. Lista de espécies de répteis observados na Estrada Parque Transpantaneira,
município de Poconé, MT.
O r d e m / Subordem / Família
Espécie
Nome regional
Crocodilia
Alligatoridae
Caiman yacare
Jacaré
Eunectes murinus
Sucuri
Squamata
Serpentes
Boidae
As aves representam o grupo de maior facilidade para observação e são facilmente
avistadas nos locais abertos como a Savana Gramíneo-lenhosa e Savana Parque. Ninhos
de Tuiuiu também foram avistados (Tabela 3).
Tabela 3. Lista de espécies de aves observadas na Estrada Parque Transpantaneira,
Município de Poconé, MT.
Ordem/Família
Espécie
Nome regional
Anseriformes
Anatidae
Dendrocygna sp.
Marreca
Anhimidae
Cairina moschata
Pato-do-mato
Chauna torquata
Tachã
Anhima cornuta
Anhuma
Nytidromus sp.
Curiango
Jacana jacana
Cafezinho
Caprimulgiformes
Caprimulgidae
Charadriiformes
Jacanidae
32
Ordem/Família
Espécie
Nome regional
Ardeidae
Egretta thula
Garcinha-branca
Ardeidae
Tigrisoma lineatum
Socó-boi
Ciconiidae
Jabiru mycteria
Tuiuiu
Ardeidae
Casmerodius albus
Garça-branca-grande
Herpetotheres cachinnans
Acauã
Caracara plancus
Gavião caracará
Rostrhamus sociabilis
Gavião caramujeiro
Busarellus nigricollis
Gavião-belo
Ortalis canicollis
Arancuã
Aramidae
Aramus guarauna
Carão
Eurypygidae
Eurypyga helias
Pavãozinho-do-pará
Ciconia maguari
Maguari
Pardaria capitata
Cardeal
Psittacidae
Anodorhynchus hyacinthinus
Arara-azul-grande
Psittacidae
Aratinga aurea
Periquitos
Rhea americana
Ema
Crypturellus undulatus
Jaó
Ceryle torquata
Martim pescador
Caprimulgiformes (cont.)
Falconiformes
Falconidae
Accipitridae
Galliformes
Cracidae
Gruiformes
Oiciconiformes
Ciconiidae
Passeriformes
Emberezidade
Psittaciformes
Rheiformes
Rheidae
Tinamiformes
Tinamidae
Trogoniformes
Trogonidae
Os mamíferos mais comuns são as capivaras, sendo observado, também com facilidade,
o cervo-do-pantanal.
A Fazenda Pouso Alegre foi o local de maior avistamento de
grupos de animais; no restante da EPT os animais geralmente foram avistados isolados
ou em grupos pequenos. Informações sobre onças foram obtidas na região da floresta
semidecidual das terras baixas, na Pousada do Jaguar, onde o proprietário informou
sobre o avistamento de 4 animais, e na Fazenda Esperança também foi relatado o
avistamento. As duas propriedades estão situadas na mesma região (Tabela 4).
Tabela 4. Lista de espécies de mamíferos observados na Estrada Parque
Transpantaneira, município de Poconé, MT.
Ordem/família
Espécie
Nome regional
Artiodactyla
Tayassuidae
Tayassu tajacu *
Caititu
Cervidae
Blastocerus dichotomus
Cervo-do-pantanal
Ozotoceros bezoarticus
Veado campeiro
33
Ordem/família
Espécie
Nome regional
Panthera onca **
Onça-pintada
Alouatta caraya
Bugio
Hydrochaeris hydrocaeris
Capivara
Carnívora
Felidae
Primates
Callithricidae
Rodentia
Hydrochaeridae
* Criado em sede de pousada.
** Não houve observação direta; as informações sobre avistamentos são provenientes de
proprietários, peões e usuários da EPT.
Limites e Propriedades
Foi produzido um mapa apresentando a localização das pontes, estradas secundárias da
EPT, os limites entre as propriedades que chegam à beira da Estrada e o nome dos
respectivos proprietários (Figura 15).
RECOMENDAÇÕES
Com a finalidade de melhorar a ilustração do Mapa de Vegetação, Uso e Ocupação da
EPT, sugere-se fotografar todas as diferentes unidades vegetacionais ao longo da EPT
existentes no mapa, mostrando os diferentes tipos de vegetação e/ou qualquer outra
alteração
da
paisagem.
A seguir estas fotos poderão ser ligadas às classes de
vegetação constantes da legenda, através da ferramenta “Hot Link” do ArcView 3.2.a.
Ameaças
É indispensável a permanente vigilância sobre as atividades de impacto ambiental
envolvendo a região da EPT e entorno.
Degradação das pastagens naturais
Muitas áreas de pastagem natural no Pantanal foram degradadas e estão sendo
convertidas em pastagens cultivadas, sendo que a principal espécie utilizada para o
plantio
é a braquiária. Aumentar a produtividade das pastagens é uma das iniciativas
tomadas pelos produtores para fazer frente à competitividade das pastagens cultivadas
nas áreas fora do Pantanal. A viabilidade econômica das fazendas de gado no Pantanal
deve estar contida no plano de manejo da EPT, como forma de garantir a conservação
das paisagens no Pantanal.
34
Figura 15. Mapa das divisas das propiedades que encostam na EPT
35
Embora seja um tema polêmico, a forma de ocupação que os antigos fazendeiros
realizaram no passado e que propiciou a conservação da paisagem pantaneira, já não é
suficiente para gerar renda para manter as propriedades (Oliveira, 1998; Campos Filho,
2002). Embora muitas propriedades estejam incrementando a renda através da abertura
de pousadas; uma maioria carece de estrutura e informação sobre o turismo ecológico,
confundindo-o com o turismo rural. Como nem todas as propriedades terão vocação e
capital para investir no turismo, será necessário discutir formas de incremento na renda
dos produtores. Técnicas de manejo e recuperação de pastagens naturais e certificação
de carne orgânica, seriam as principais alternativas no momento.
Abertura de novas pousadas e construções de estradas e sedes de fazenda
As medidas supracitadas são de fundamental importância para evitar o abandono das
atividades
agropecuárias
e
o
parcelamento
do
solo.
Cada
pedaço
de
terra
desmembrado, significa pelo menos uma nova sede e uma nova estrada. As estradas
são altamente impactantes no Pantanal, pois quando construídas sobre o campo são
aterradas, o que altera o ciclo hidrológico e, quando construídas sobre cordilheiras
(Florestas e Cerradão), causam desmatamento e fragmentação de hábitats.
Abertura de trilhas ecológicas ao longo da EPT
Na faixa de 300m que compreende a EPT, deve-se ter cuidado ao planejar trilhas
ecológicas, pois nesta área predominam as comunidades pioneiras de macrófitas
aquáticas e pombeiros. Este tipo de comunidade se estabeleceu, principalmente após a
abertura da Transpantaneira, colonizando as caixas de empréstimo. Novas intervenções
poderão desestruturar a estrutura das comunidades.
Recuperação das caixas de empréstimo
As caixas de empréstimo ao longo da EPT, são um dos impactos ambientais causados ao
Pantanal e ao mesmo tempo um dos atrativos turísticos, pois armazenam água para o
período seco, atraindo os animais e criando nichos para as plantas aquáticas, que
adaptaram-se rapidamente a este ambiente (Campos Filho). Este novo nicho, criado
após a abertura da estrada, encontra-se em pleno processo de sucessão ecológica. As
comunidades
aquáticas
estão
sendo
substituídas
por
comunidades
arbustivas
e
arbóreas (pombeiros) à medida em que aumenta o processo de colmatação e dos
períodos de seca. As mudanças nos recursos para a fauna, aparentemente tem causado,
segundo relatos da população local, uma redução no número de animais.
A
recuperação destas áreas deve ser amplamente discutida e questionada, devendo ter
como referência a conservação e não a restauração dos ambientes já impactados e em
pleno processo de sucessão ecológica. Assim podem-se selecionar áreas, com relevante
interesse cênico, como as áreas de Savana Gramíneo-lenhosa (campo), para que sirvam
como
áreas
piloto
onde
se possam ser implementadas práticas de manejo e
monitoramento da biodiversidade.
36
Questão fundiária
Sobre a questão fundiária há de se pensar em um amplo acordo com os proprietários
para que se efetue a regularização das propriedades em conjunto, de forma a reduzir os
custos. Tal demarcação feita por GPS e plotada em imagem de satélite, solucionará a
questão, facilitando futuros parcelamentos e controle dos nomes dos proprietários por
parte do órgão gestor da UC EPT.
A regularização fundiária é de vital importância para que não ocorra o parcelamento do
solo paralelo a UC EPT. Embora a escrituração de terras no Pantanal deva ser superior a
100 ha, existem casos de propriedades com área menor do que o permitido. Esse tipo
de “micro-parcelamento” deve ser evitado para que se possa ter um mínimo de garantia
de conservação das paisagens da UC EPT. Outra medida preventiva deve ser no sentido
de promover a conscientização dos grandes proprietários que confrontam com a EPT,
destacando a importância da conservação ambiental da paisagem pantaneira para a
manutenção das atividades econômicas relacionadas ao ecoturismo. Esta medida de
caráter preventivo, poderá evitar o parcelamento das propriedades paralelas à EPT. Para
as pequenas propriedades já estabelecidas podem ser proporcionadas alternativas
econômicas de manejo sustentável de modo a integrá-las às atividades relacionadas ao
ecoturismo.
Resíduos
Sobre o destino dos resíduos dos estabelecimentos ao longo da EPT, não há problemas
graves com tratamento que recebem, até porque, são poucos estabelecimentos e a
maioria tem como clientela turistas, o que acaba reforçando a necessidade da
manutenção de uma postura ecologicamente correta e preocupação com o destino
correto dos resíduos. Devem ser realizadas campanhas de orientação dos proprietários
de lanchonetes e pousadas para o manuseio correto do lixo; os proprietários devem,
também, ser orientados no sentido de permitir a introdução de técnicas e tecnologia
acessíveis ao nível dos empreendimentos, o que poderá garantir melhores resultados.
Atividades impactantes
Instalação de Placas de publicidade em locais indevidos, queimadas não autorizadas,
desmatamentos, construções de aterros e abertura de drenos, refletem a fraca atuação
dos órgãos públicos estaduais responsáveis pela fiscalização. A ausência do poder
público é uma das reclamações dos produtores e donos de pousadas. Tais práticas
devem ser combatidas com esclarecimentos à população da região sobre a importância
da UC EPT. Esta atividade deve ser realizada através de cursos de educação ambiental
envolvendo os sindicatos de produtores rurais e entidades de classe do setor, como o
Núcleo de Criadores de Cavalo Pantaneiro. É importante ressaltar que no decorrer do
37
trabalho a maior parte dos produtores entrevistados desconheciam a finalidade da
Unidade de Conservação.
Fiscalização
Reforço da atividade de fiscalização, no sentido de estruturação dos meios de
fiscalização, também serão necessários. Ressaltando que a Fundação Ecotrópica já
promoveu um curso de treinamento em fiscalização e educação ambiental para a
abordagem de turistas para a Polícia Militar Ambiental e técnicos da FEMA. Sobre
queimadas, o IBAMA já treinou uma brigada contra incêndio na região.
Espécies exóticas
Sobre as espécies exóticas de braquiária, serão necessários estudos mais aprofundados
sobre Dinâmica de População e monitoramento para a espécie Brachiaria subquadrípara.
Estudos sobre a possibilidade de plantio de espécies forrageiras nativas podem ser
encontrados na EMBRAPA Pantanal e, finalmente, estimular os produtores para o cultivo
das espécie nativas e evitar a espécie exótica.
Erosão
Os processos erosivos sobre o aterro da EPT são pouco freqüentes e, aparentemente,
não apresentam maiores problemas com a preservação ambiental. Os trechos com
maior incidência desses processos, que são as cabeceiras de pontes, sofrerão
intervenções
que
estão
previstas
no
projeto
BID-Pantanal.
Informações
técnicas
adicionais sobre os processos erosivos foram tratadas pelo EIA/RIMA da Rodovia MT –
060, Estrada Parque Transpantaneira.
G LOSSÁRIO
−
Assoreamento: Diminuição da profundidade de cursos de água por deposição de
sedimentos
−
Batume: Ilha flutuante composta por vários tipos de vegetação.
−
BID: Banco Interamericano de Desenvolvimento.
−
Caixa de empréstimo: Cavidade retangular, às margens da EPT, resultante da
retirada de terra utilizada para formar o aterro da Estrada.
−
Capão: Vegetação florestal situada em relevo mais alto e não inundável.
−
Cênico: Referente à cena, paisagem.
−
Colmatação: É o aumento de material arrastado e depositado em determinado lugar
ao ponto de dificultar, ou mesmo, impedir a passagem da água.
−
DU – Ducks Unlimited, Inc, www.ducks.org
−
ECOTRÓPICA: Fundação de Apoio à Vida nos Trópicos, www.ecotropica.org.br
38
−
EIA/RIMA: Estudo e Relatório de Impacto Ambiental.
−
EPT: Estrada Parque Transpantaneira.
−
FEMA: Fundação Estadual do Meio Ambiente, www.fema.mt.gov.br
−
IBAMA: Instituto Brasileiro do Meio Ambiente e dos Recursos Renováveis da
Amazônia, www.ibama.gov.br
−
Inversor de corrente: Dispositivo eletrônico que transforma a corrente elétrica
contínua (DC 12V) em corrente alternada (AC 120 V).
−
Murundu: Pequeno monte de terra com vegetação mais alta, cercado pelo campo
inundável.
−
Ruderal:
Vegetação
que
cresce,
preferencialmente,
em
torno
das
habitações
humanas e estradas.
−
TCBR: Tecnologia e Consultoria Brasileira S. A., Cuiabá, MT.
− TRANSPANTANEIRA: Estrada Estadual de Mato Grosso, MT 060, que liga a Rodovia
Federal BR 070 a Porto Joffre, município de Poconé, MT.
R EFERÊNCIAS
BIBLIOGRÁFICAS
Campos, Filho L.V.S. 2002. Tradição e ruptura. Cultura e ambientes pantaneiros.
Entrelinhas, Cuiabá, MT. 184p.
Oliveira, B.A.C. 1998. Valor recreativo da Rodovia Transpantaneira: uso turístico e
conservação no Pantanal Mato-Grossense. Dissertação, Universidade Federal de Mato
Grosso, Instituto de Biociências, Programa de Pós-graduação em Ecologia e Conservação
da Biodiversidade. Cuiabá, MT. 102p.
Instituto Brasileiro de Geografia e Estatística (IBGE). 1992. Manual técnico da vegetação
brasileira. Rio de Janeiro: IBGE.
Programa Nacional de Meio Ambiente (PNMA), ed. 1997. Plano de Conservação da Bacia
do Alto Paraguai – PCBAP/Projeto Pantanal, Programa Nacional do Meio Ambiente. Vol.
3. Brasília: PNMA.
39
2 B .L AND C OVER C LASSIFICATION FOR THE UPPER P ARAGUAY RIVER BASIN P ILOT P ROJECT AREA
MARIO C ARDOZO11, W. THEODORE MEALOR , JR.12 AND DAWN BROWNE13
A BSTRACT
The Upper Paraguay River Basin (UPRB) is a large watershed in Bolivia, Brazil and
Paraguay that contains the Pantanal wetland complex. Both the basin and the Pantanal
have vegetation types characteristic of several ecoregions, including Chaco, Cerrado,
and Chiquitano Dry Forest. This study developed a hierarchical land cover classification
system based on those found in the literature and modified for local conditions. Oneand two-date variants of an unsupervised classification method using Landsat data were
employed to test the applicability of the proposed system. The results show that the
applied techniques are useful in discriminating land cover classes based on vegetation
physiognomy (forest, savanna, and grassland) and flooding seasonality. Accuracy
assessment proved the two-date approach more accurate for land cover classification
indicating the importance of explicitly incorporating seasonality when mapping dynamic
landscapes such as the Pantanal.
I NTRODUCTION
This study addresses a section of one of the largest interior freshwater wetlands in the
world, the Pantanal, and the drainage basin that encloses it, the Upper Paraguay River
Basin (UPRB), located in southern South America (Figure 1). The purpose of this study is
to develop a prototype land cover classification system of the UPRB that can be used in
the classification of remotely sensed data. Because the existing land cover classification
systems for the UPRB have been developed in different countries, utilizing different
methodologies based on different criteria, and at different scales and levels of
complexity, there is a need for their standardization when the various politically and
naturally diverse territories of the region are regarded as a unit.
Although global and
regional vegetation classification systems that can be applied to the UPRB exist
(Zeilhofer and Schessl, 1999; Paranhos, 2000), studies that integrate locally developed
classification systems are lacking.
The mapping of land cover is generally performed with the aid of remote sensing
technology, which constitutes a powerful tool for the identification and quantification of
land cover types in wetlands (Lyon, 2001).
Remotely sensed data can provide a
multitemporal description of land cover of large and/or inaccessible areas that vary
seasonally and throughout the years.
Experiments have demonstrated that seasonal
11
The University of Texas at Austin, TX, U.S.A; [email protected]
12
The University of Memphis, TN, U.S.A; [email protected]
13
Ducks Unlimited, Inc., Memphis, TN, U.S.A; [email protected]
40
variability must be considered for the proper classification of certain types of land cover
(Lunetta and Balogh, 1999).
Figure 1. Location of UPRB, the Pantanal, and Pilot Area.
In the Pantanal area, the characterization of landscape has been performed mainly
through mapping techniques rather than the use of multispectral classification (MME,
1982a; PNMA, 1997). Although Landsat images are mentioned as source data for many
studies and maps of the area, the classification of land cover in these studies usually
does not involve spectral pattern recognition and is generally performed through
manual digitization guided by visual interpretation and supported by ground reference
data (MME, 1982a; PNMA, 1997).
With this study, a pioneering effort was made to develop and test a land cover
classification system for the UPRB, for use with multispectral classification of remotely
sensed data. The logistical impossibility of testing the applicability of the scheme in the
entire UPRB led to the selection of a specific study site (pilot area) to evaluate single-
41
date versus two-date approaches of a remote sensing technique for land cover
classification.
This study provides insights into the efficiency of Landsat image
classification for the spectral differentiation of land cover at a broad scale in the pilot
area, having limited ancillary data and fieldwork to assist the process. It was designed
to
evaluate
the
importance
of
utilizing
multitemporal
data
for
the
proper
characterization of the land cover types of the UPRB where seasonal flooding has a
profound effect on vegetation and land use patterns.
S TUDY A R E A
The results of this study are presented at two different spatial extents. The entire UPRB
is addressed in the development of a land cover classification system for the region,
while a pilot area in the UPRB is the object of testing this system and automated image
classification procedures for use of Landsat data (Figure 1).
The UPRB, located in Bolivia, Brazil, and Paraguay, is at the junction of three South
American ecoregions, Cerrado, Chaco, and Chiquitano Dry Forest, which present
different vegetation types in wetland and upland environments. There is a lack of
agreement on the spatial extent and boundaries of the UPRB. Some authorities believe
that the UPRB extends westward into the Paraguayan and Bolivian Dry Chaco (Browne et
al., 2003; TNC, 2002). Liu (2003) states that the addition of the Dry Chaco sub-basin
would represent an increase of 50 percent in the total area of the UPRB.
The
contribution of the Dry Chaco sub-basin in the hydrological balance of the UPRB is
uncertain (Liu, 2003).
The Pantanal’s areal extent represents close to 28 percent of the UPRB and occupies
approximately 137,000 km2 (Liu, 2003) of areas below 200 m of altitude in Bolivia,
Brazil and Paraguay (EMBRAPA, 2003).
The Pantanal is characterized as an extensive
wetland having vegetation cover conditioned to standing water, and seasonal and
periodic flooding.
This dynamic landscape is diverse temporally and spatially and is
regionally and internationally valuable because of its large extent, scenic beauty, relative
pristine state, and high biological richness (Swarts, 2000).
The pilot area consists of a trinational section of the central-southern Pantanal and
UPRB, included in the Landsat scene corresponding to the World Reference System 2
(WRS-2) path 227 row 74, and encompassing 30,674 km2.
Chaco-influenced Pantanal portion of the UPRB.
42
The pilot area is in the
M ETHODS
Land Cover Classification System
Because different sources classify the vegetation of the Pantanal and the UPRB
differently, there is a need to establish a standard system that is comprehensive for the
region.
The proposed land cover classification system is based on the integration of
land uses and vegetation types described in the literature for the UPRB, but it also takes
into consideration factors that facilitate the classification of remotely sensed data in
automated procedures. In the UPRB region, the classification system with the most
detailed hierarchical structure is the official Brazilian vegetation classification system
(IBGE, 1992); as a result, this system is used as the basis for the land cover classification
scheme developed in this study. Other classification systems and vegetation studies
were reviewed and integrated to complete the scheme and conform it to local
conditions.
Most of these studies have in common the use of physiognomy (forest,
savanna, and grassland) as one of the basic parameters of classification (Table 1).
Another
parameter
commonly
used
is
general
appearance.
In
forests
general
appearance refers to deciduousness (phenology) or openness and in savannas to density
and spatial arrangement of arboreal stratum.
Table 1. Major vegetation studies reviewed
Authors of studies
related to vegetation
classification
Spatial extent
Description
Parameter(s) of classification (in
hierarchical order when
applicable)
IBGE, 1992
Brazil
Technical handbook of
vegetation
Natural/anthropogenic, vegetation
physiognomy, climate, physiology,
appearance, elevation
PNMA, 1997
Brazilian UPRB
Vegetation study and
maps for conservation
plan
physiognomy, climate, physiology,
appearence, elevation
Machado and Ribeiro, 1994
Brazilian Cerrado
Vegetation study
Vegetation physiognomy
UNA and GTZ, 1991
Paraguayan Western
Region
Vegetation and land
use study and map
physiognomy, appearance, flora
MAG and BGR, 1999
Paraguayan Western
Region
Vegetation study and
map
Vegetation physiognomy, physiology,
flora
Mereles, 2000
Paraguayan Pantanal
Ecological study for
conservation plan
Flooding seasonality, environment
WWF, 2002
Bolivian Pantanal
Ecological study for
conservation plan
Vegetation physiognomy,
appearance, physiology, flora
This study
UPRB
Land cover
classification system
physiognomy, appearance, flora,
flooding seasonality (as attribute)
43
Other criteria employed to classify vegetation in the existing systems include: climate,
which indicates subjection to dry seasons; physiology, which refers to availability/use of
water (xerophytic, mesophytic, hydrophytic); elevation (montane, submontane, lowland,
and alluvial); flooding seasonality; and flora, which alludes to predominance of
vegetation species. Only parameters that could be standardized for the majority of the
vegetation classes found in the literature were used as classification criteria in the
system developed in this study.
Image Data and Preprocessing Procedures
Landsat 5 TM and Landsat 7 ETM+ satellite data were used in this study (). Analysis of
Landsat data was performed with the software Erdas Imagine 8.5. The dates of imagery
were selected based on precipitation and river gauge data of stations located in the pilot
area or its proximity (Figures 2, 3, 4, and 5; Table 2).
Three dates of imagery were
selected to depict different seasons and flood extents. The 06/09/1997 image
corresponds to an extraordinary flood event that occurred during the high-flood season
of 1997. The other two dates correspond to comparable relatively typical water years:
one image is from the low-flood season (11/14/1999) and the other from the highflood season (07/30/1998).
Figure 2. Hydrological stations in or close to Pilot Area.
44
River Gauge - Ladário
6
River Gauge (m)
5
Year
4
3
1997
1998
1999
Average (1984-2000)
2
Date of selected
images
1
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Month
Figure 3. River gauge at Ladário
Precipitation - Corumbá
300
Precipitation (mm)
250
200
Year
1997
1998
150
1999
Average (1984-2000)
100
Date of selected
images
50
0
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Month
Figure 4. Precipitation at Corumbá
45
Dec
Precipitation - Bahía Negra
300
Year
250
Precipitation (mm)
1997
200
1998
1999
150
Average
(1986-2000)
100
Date of selected
images
50
0
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Month
Figure 5. Precipitation at Bahía Negra
Table 2. Selected images
Landsat
image date
Sensor
6/9/1997
Total monthly
precipitation (mm)
Monthly
average river
gauge at
Ladário (m)
Flood
season
in
Pantanal
Year flood
event
Bahía
Negra
Corumbá
TM
97.7
87.9
5.53
cheia
(high flood)
extraordinary
7/30/1998
TM
12
0.1
4.43
cheia
(high flood)
common
11/14/1999
ETM+
102
82.1
1.19
seca
(low flood)
common
The three selected images were co-registered and georeferenced by Image Links, Inc., a
value added vendor, to Universal Transverse Mercator (UTM) World Geodetic System
(WGS) 1984 Zone 21, using reference points from a one-kilometer Digital Elevation
Model (DEM) and available topographic maps, obtaining a Root Mean Square Error
(RMSE) of less than one pixel.
A
radiometric
correction
technique,
histogram
matching,
was
applied
to
the
07/30/1998 image in order to compensate for its different pixel value range in
comparison to the 11/14/1999 image. The 07/30/1998 image was resampled to match
46
the pixel value range of the 11/14/1999 image because the latter originated from a
sensor with improved signal to noise ratio (SNR), Landsat 7 ETM+.
Principal Component Analysis (PCA) was applied to minimize redundancies in the
dataset and prepare it for optimal performance in the unsupervised classification.
Studies show that preprocessing the data with PCA may improve the separability of land
cover types in the classification (Li and Yeh 1998; Lunetta 1998; Yuan, Elvidge, and
Lunetta 1998).
automated
Additionally, PCA was utilized in this study in order to evaluate an
approach
generalizable
and
more
practical
for
users
with
varied
technological resources in the countries that share the Pantanal and UPRB. The selected
components amounted to more than 96 percent of the variance of the original dataset
(Tables 3 and 4).
Table 3. Eigenvalues of One-date PCA
Component
Eigenvalue
% Variance
%
Accumulative
1
2
3
4*
1360.28
553.30
122.22
41.46
65.48
26.64
5.88
2.00
65.48
92.12
98.00
100.00
* discarded component
Table 4. Eigenvalues of Two-date PCA
Component
Eigenvalue
% Variance
%
Accumulative
1
2
3
4
5*
6*
7*
8*
1388.025
575.338
192.500
110.859
42.183
37.629
7.055
3.224
58.89
24.41
8.17
4.70
1.79
1.60
0.30
0.14
58.89
83.31
91.47
96.18
97.97
99.56
99.86
100.00
*discarded components
Image Classification Procedure
Because of the lack of extensive field-based data and the remoteness of the pilot area,
an unsupervised method, iterative self-organizing data analysis (ISODATA), was selected
47
for the classification of land cover. Two approaches of this method were compared. In
the first, the first three components derived from bands 3, 4, 5, and 7 of the
07/30/1998 image (Table 3) were classified into 120 classes using the ISODATA
method.
This number of classes was selected to maximize the spatial separability of
classes.
In the second approach, the first four components derived from bands 3, 4, 5, and 7 of
each of the 07/30/1998 and 11/14/1999 stacked images were used as input data for
the unsupervised classification (Table 4).
The same number of classes, 120, was
utilized for the classification process. Because phenological differences in the vegetation
were considered factors affecting seasonal variation in land cover, a second image
corresponding to a contrasting season was included to account for intra-annual
variation
in
vegetation.
To
finalize
the
imagery
classification
process
of
both
approaches, the 120 classes were recoded to pixel values of one to eight to reassign the
spectral classes to common land cover categories using the classes of a land cover
classification scheme proposed in this study for the UPRB.
The reassignment of the
classes was performed through visual interpretation of the original images with the help
of vegetation maps.
Open Water Delineation and Classification Finalization
Single band density slicing was used to classify water pixels in the three images
selected.
This procedure can provide results that are comparable in accuracy to more
elaborate and time-consuming techniques (Frazier and Page, 2000).
Band 5 (mid
infrared) was selected for use because it allows better water pixel separability than other
infrared and visible bands.
To add the multitemporal data of flood extent to the classified images, a new image was
created encompassing the water-pixel data from the three dates.
The pixels of the
three flood-extent images were recoded to a value of 100 and then the images were
overlaid to develop a composite of flood extent. The overlay process added the values
of pixels that coincided spatially so the resulting image presented pixel values of 100,
200 and 300. Pixels with values of 300 were considered permanent water, while pixels
with values of 100 and 200 were considered floodable and seasonally flooded areas,
respectively.
The multitemporal flood extent image was then merged with both classified images
(one- and two-date approaches).
The pixels of the two new images were recoded to
classes conforming to flood seasonality with the exception of the forest classes, which
were not reclassified because the remotely sensed data employed do not permit
accurate delineation of flooded forests.
A majority statistical filter with a moving
48
window of 5x5 pixels was used to enhance the continuity of dominant land cover
classes.
Field Data for Evaluation of Classification Approaches
Overall, user’s and producer’s accuracies, and the KHAT statistic were calculated to
evaluate and compare one versus two-date approaches of classification. A total of 199
oblique photographs (snapshots) taken in overflights in Bolivia, Brazil, and Paraguay
were used for classification accuracy assessment (Figure 6).
Global Positioning System
(GPS) coordinates were assigned to each photograph during the overflights.
Figure 6. Reference data for accuracy assessment.
Only photographs showing a predominant or single land cover were used. Because the
reference photographs correspond to dates different than those of the Landsat images
used in the classification procedures (December 2000 and March 2002), only the
49
physiognomy of vegetation was considered in the identification of land cover types in
the reference photographs.
L AND C OVER C LASSIFICATION S YSTEM R ESULTS (UPRB)
The proposed integrative hierarchical classification system for the UPRB (Table 5)
combines five schemes and several vegetation studies identified in the literature (Table
6). Because criteria and scale of application differ among the schemes, the levels of the
proposed classification system are based upon physiognomy, phenology, and flora.
Criteria such as elevation (submontane, alluvial) and physiological factors related to
use/availability of water (mesoxerophytic, xerophytic) are not consistently used to
create fourth and fifth levels because sufficient data are not available to standardize the
various forests types described in the literature.
Still, tentative fourth and fifth
classification levels are included in Table 5 to incorporate the most significant
vegetation types found in the literature.
The first level of the proposed system is the most general and divides land cover into
natural and anthropogenic classes.
The natural classes refer to natural communities,
while anthropogenic classes represent artificially impounded open water (reservoirs,
canals) and lands altered from a natural state by human occupancy (urban land,
agricultural land, reforestation, bare land).
Natural classes may include areas occupied
and used by humans, such as cattle ranching in savannas, only if these areas maintain
the basic natural structure. The placement of natural/anthropogenic classes in the first
level is based on the Brazilian vegetation classification system (IBGE, 1992).
In the natural category, the second level subdivides vegetation into three physiognomies
based on the study by Ribeiro and Machado (1998): forests (more than 50 percent tree
coverage), savannas (less than 50 percent tree coverage), and grasslands (predominantly
herbaceous).
Other classes in the natural category include open water (streams and
lakes) and bare land (floodable areas in succession).
The third level characterizes
forests in regard to their appearance/phenology in semideciduous, deciduous, and
evergreen categories. Savannas and grasslands are floristically classified in this level;
they correspond to either Chaco or Cerrado ecoregions.
Attributes employed for the characterization of wetland/upland habitats in the region
relate frequency of flooding to vegetation types.
The “permanently flooded lands” are
palustrine areas normally characterized by aquatic and/or hydrophytic vegetation
(Anderson et al., 1976), but they can also include non-vegetated inundated areas.
Permanently flooded lands include swamplands, lagoons, and plains and depressions
that are always inundated.
The “seasonally flooded lands” are those conditioned by
recurring inundation, and are considered part of the seasonal wetland complex.
“Floodable lands” are potentially floodable natural lands, which are disturbed by
50
inundation irregularly or at lower frequencies. Finally, the “non-floodable lands” do not
experience periodical or sporadic flooding.
Table 5. Proposed UPRB classification system
1. Natural land
1.1. Open water
1.2. Forest
1.2.1. Evergreen forest
1.2.1.1. Riparian evergreen forest b
1.2.1.2. Xerophytic evergreen forest – cerradão (Cerrado) d
1.2.1.3. Submontane open rainforest d
1.2.2. Semideciduous forest
1.2.2.1. Alluvial semideciduous forest c
1.2.2.2. Lowland semideciduous forest d
1.2.2.3. Submontane semideciduous forest (Chiquitano Dry Forest) d
1.2.2.4. Xerophytic semideciduous forest (Chaco) b, c, d
1.2.2.5. Mesoxerophytic semideciduous forest (Chaco) b, c
1.2.3. Deciduous forest
1.2.3.1. Lowland deciduous forest d
1.2.3.2. Submontane deciduous forest d
1.2.3.3. Deciduous forest (Chiquitano Dry Forest) c, d
1.3. Savanna
1.3.1. Cerrado savanna
1.3.1.1. Treed Cerrado savanna c, d
1.3.1.2. Parkland Cerrado savanna b, c, d
1.3.2. Chaco steppe savanna
1.3.2.1. Treed Chaco steppe savanna c, d
1.3.2.2. Parkland Chaco steppe savanna b, c, d
1.4. Grassland
1.4.1. Cerrado grassland a, b, c, d
1.4.2. Chaco grassland a, b, c, d
1.5. Bare land b, c, d
2. Anthropogenic Land
2.1. Open water
Attributes of flooding
a: permanently flooded land
2.2. Urban land/Built up area
2.3. Agricultural land
b: seasonally flooded land
c: floodable land
d: non floodable land
2.4. Reforestation
2.5. Bare land
51
Table 6. Proposed and reviewed vegetation classes
Vegetation
form
Forest
Proposed classes
Reviewed classes included in proposed
classes
Riparian evergreen forest (1.2.1.1)
Gallery forest (Ribeiro and Machado, 1998);
evergreen forest (Zeilhofer and Schessl, 1999)
Xerophytic evergreen forest-cerradão
(1.2.1.2)
Cerradão (Ribeiro and Machado, 1998); forested
savanna (IBGE, 1992; PNMA, 1997); dense arboreal
savana (MME, 1982a)
Submontane open rainforest (1.2.1.3)
Submontane open rainforest (IBGE, 1992; PNMA,
1997)
Alluvial semideciduous forest
(1.2.2.1)
Alluvial semideciduous seasonal forest (IBGE,
1992; PNMA, 1997)
Lowland semideciduous forest
(1.2.2.2)
Lowland semideciduous seasonal forest (IBGE,
1992; PNMA, 1997)
Submontane semideciduous forest
(Chiquitano Dry Forest) (1.2.2.3)
Submontane semideciduous seasonal forest (IBGE,
1992; PNMA, 1997); Chiquitano semideciduous
forest (WWF, 2002)
Xerophytic semideciduous forest
(Chaco) (1.2.2.4)
Forested steppe savanna (IBGE, 1992; PNMA, 1997);
quebracho blanco forest (UNA, and GTZ, 1999);
xerophytic forest (MAG, and BGR, 1999); floodable
forest (MAG, and BGR, 1999)
Mesoxerophytic semideciduous forest
(Chaco) (1.2.2.5)
Forested steppe savanna (IBGE, 1992; PNMA, 1997);
quebracho colorado forest (UNA, and GTZ, 1991;
MAG and BGR, 1999)
Lowland deciduous forest (1.2.3.1)
Lowland deciduous seasonal forest (IBGE, 1992;
PNMA, 1997)
Submontane deciduous forest
(1.2.3.2)
Submontane deciduous seasonal forest (IBGE,
1992; PNMA, 1997)
Deciduous forest (Chiquitano Dry
Forest) (1.2.3.3)
Chiquitano deciduous forest (WWF, 2002)
Treed Cerrado savanna (1.3.1.1)
Treed savanna (IBGE, 1992; PNMA, 1997)
Parkland Cerrado savanna (1.3.1.2)
Parkland savanna (IBGE, 1992; PNMA, 1997)
Treed Chaco steppe savanna (1.3.2.1)
Treed steppe savanna (IBGE, 1992; PNMA, 1997);
xeric savanna (Frey, 1995)
Parkland Chaco steppe savanna
(1.3.2.2)
Parkland steppe savanna (IBGE, 1992; PNMA, 1997);
hydromorphic savannas (MAG and BGR, 1999)
Cerrado grassland (1.3.1.1)
Gramineae-woody savanna (IBGE, 1992; PNMA,
1997)
Chaco grassland (1.3.2.1)
Gramineae-woody steppe savanna (IBGE, 1992;
PNMA, 1997)
Savanna
Grassland
52
The land cover classification system proposed in this study does not present an explicit
category for wetlands because the existing regional literature is neither specific nor
detailed in the characterization of wetlands. This fact reflects the complex dynamics of
vegetation successional patterns caused by the spatially and temporally variable
flooding patterns of the study area (Ponce and da Cunha, 1993).
Discussion of the proposed land cover classes is presented in the following subsections.
Each class of the proposed system is accompanied by its respective order
number found in Table 5.
Open Water (1.1)
The open water category includes natural linear lotic (flowing) water bodies such as
streams, and enclosed lentic (non-flowing) water bodies such as lakes (Anderson et al.,
1976).
In the Brazilian section of the Pantanal, seasonal water bodies, such as river
corridors temporarily connecting depressions and seasonal lagoons, are described
(Allem and Valls, 1987).
However, in this study, open water refers only to permanent
features and seasonal bodies of water are considered floodable lands.
Evergreen Forest (1.2.1)
Evergreen forests are found only in seasonally flooded and non-floodable lands, in the
Brazilian section of the UPRB. Some authors mention the presence of seasonally flooded
evergreen forest (1.2.1.1) associated with streams (Zeilhofer and Schessl, 1999; Frey,
1995).
Zeilhofer and Schessl (1999) observed this forest type in sites located in the
northern Brazilian Pantanal, on fluvial deposits along lower terraces of riverbanks. This
forest type presents a low arboreal stratum of 8–11 m and predominance of Vochysia
divergens can occur (Zeilhofer and Schessl, 1999).
Another evergreen forest in the Cerrado, generally located on non-floodable lands, is
the “xerophytic evergreen forest- cerradão” (1.2.1.2) (Ribeiro and Machado, 1998).
In
classification schemes directly related to the Pantanal and the UPRB, cerradão appears as
a subtype of cerrado (PNMA, 1997).
Its flora reflects that of the Cerrado, but in this
study, due to its physiognomy, cerradão is included within the forests. Its arboreal
stratum is low (8–16 m) (PNMA, 1997) and predominantly continuous, presenting 50 to
90 percent of coverage (Ribeiro and Machado, 1998). Species present in the cerradão of
the UPRB include Carycar brasiliense, Salvertia convallariodora, Dimorphandra mollis,
Astronium
graveolens,
Qualea
grandifolia,
Anadenanthera
pelegrina,
Hymenaea
stigonocarpa, Qualea parviflora, Kielmeyera coriacea, among others (PNMA, 1997).
Another type of non-floodable evergreen forest included in the UPRB is submontane
open
rainforest
Amazonian
(“floresta
influence
ombrófila
(IBGE,
1992).
aberta
Open
53
submontana”)
rain
forest
(1.2.1.3),
which
presents
four
is
of
typical
physiognomies: (1) forest with palm (floresta-de-palmeira, cocal), (2) forest with woody
vines (floresta-de-cipó, cipoal), (3) forest with bamboo (floresta-de-bambu, bambuzal),
and (4) forest with Phenakospermum quianense (floresta-de-sororoca, sororocal) (IBGE,
1992).
All open rain forests contain gaps or openings; subtypes are differentiated by
altitudinal gradient: (1) lowland, (2) submontane, and (3) montane (IBGE, 1992). In the
UPRB, only the subtype submontane has been identified (PNMA 1997), however, it is not
specified to which of the four typical open rainforest physiognomies it corresponds.
The highest submontane open rain forest identified in the region presents an arboreal
stratum of 30 m (PNMA, 1997).
Semideciduous Forest (1.2.2)
In the UPRB, semideciduous forest can be found in seasonally flooded, floodable, and
non-floodable lands. The forests classified as semideciduous in Brazil are comprised of
20–50 percent deciduous trees (PNMA, 1997).
They are found in areas where a rainy
summer is followed by a marked dry season (IBGE, 1992). Amazonian genera
predominate, such as Parapiptadenia, Peltophorum, Carianiana, Lecythis, and Tabebuia,
among others (IBGE, 1992).
recognized in Brazil:
According to altitude, the following subtypes are
(1) alluvial, (2) lowland, (3) submontane, and (4) montane (IBGE,
1992). In the UPRB, all subtypes are identified except the montane (PNMA, 1997).
The alluvial semideciduous forest (1.2.2.1) is floodable and associated with streams and
water bodies. In the UPRB, physiognomically it resembles other riparian forests found in
Brazil, but it is floristically distinct because of the presence of western Amazonian
species (PNMA, 1997). A highest canopy of 30 m was observed for this forest type in
the Brazilian UPRB (PNMA, 1997). Non-floodable lowland semideciduous forest (1.3.2.2)
in the Brazilian section of the UPRB is characterized by an evergreen middle stratum
formed predominantly by acuri palms (Scheelea phalerata) (PNMA, 1997).
A highest
canopy of 25 m was observed for this forest type (PNMA, 1997).
The submontane subtype (1.2.2.3) is present in non-floodable terrains of higher
elevation (more than 150 m) (PNMA, 1997).
Tabebuia, and Aspidosperma are frequent.
Certain species of the genera Cedrela,
Typically, a submontane semideciduous
forest comprises a stratum of shrubs and tree seedlings. A highest canopy of 30 m was
observed for this forest type in the UPRB (PNMA, 1997). Landivar (2001) states that the
submontane semideciduous forests described in the Brazilian section of the UPRB are
part of the Chiquitano Dry Forest ecoregion, which is more conspicuous in Bolivia.
The seasonally flooded and floodable Chaco forests of the region are described as
semideciduous in Paraguayan literature (UNA and GTZ, 1991; MAG and BGR, 1999). The
Chaco section of the UPRB presents xerophytic (quebracho blanco forest) (1.2.2.4) and
mesoxerophytic (quebracho colorado forest) (1.2.2.5) semideciduous forests (UNA and
54
GTZ, 1991). These forest types overlap with the “forested steppe savanna” registered in
the Brazilian vegetation classification system. Physiognomically a forest, this vegetation
type is classified as a subtype of steppe and presumably is the single descriptor of
several Chaco forest formations in the Brazilian literature (PNMA, 1997).
Formations designated as “xerophytic forest” (1.2.2.4) differ from one location to the
other in the Paraguayan Chaco (MAG and BGR, 1999).
The type present in the UPRB
thrives on sandy soils of hydric origin (MAG and BGR, 1999).
This forest is short in
stature, relatively dense, and usually comprised of three strata (canopy, understory,
herbaceous cover) (MAG and BGR, 1999).
Emerging specimens of the highest stratum
may give it an open forest physiognomy. Some of the most common species mentioned
for the xerophytic forest are: Pisionia sapallo, Anadenantera colubrina, A. peregrina,
Aspidosperma quebracho-blanco, Schinopsis heterophylla, Capparis retusa, Ruprechtia
triflora, Ximena americana, Acacia praecox, Mimosa velloziana, Capparis speciosa,
Bauhinia sp., Zizipus mistol, Croton sp., Oxalis erosa, Dickya sp., Bromelia hyernimi,
Rivina humilis, Eupatorium squarrosoramosum, among others (MAG and BGR, 1999). It
is present in seasonally flooded and floodable areas (MAG and BGR, 1999).
The
“quebracho
colorado”
forest,
called
in
the
present
study
“mesoxerophytic
semideciduous forest” (1.2.2.5) is described as belonging to the mesoxerophytic unit of
the Chaco.
This forest type is seasonally flooded (MAG and BGR, 1999).
The
predominant species is Schinopsis balansae; also common in the highest stratum are:
Astronium
urundeuva,
Calycophyllum
Caesalpina
multiflorum,
Arecastrum
paraguariensis,
romanzoffianum
Phyllostylon
(MAG
and
rhamnoides,
BGR,
1999).
Another source (UNA and GTZ, 1991) refers to the same formation as “quebrachal de
quebracho colorado." This forest type is characterized as being the tallest (15 m) in the
Chaco and localized in the lowest elevations (UNA and GTZ, 1991).
However,
“quebrachal de quebracho colorado" includes larger areas and does not exactly coincide
in spatial distribution in comparison to the “quebracho colorado” forest.
Deciduous Forest (1.2.3)
Deciduous forests are subjected to two contrasting seasons: a rainy period followed by
a long dry season. More than 50 percent of the canopy of this forest has deciduous tree
specimens that lose their leaves during the dry season (IBGE, 1992). In Bolivia, types of
deciduous forests are described as part of the section of the Chiquitano Dry Forest
ecoregion in the UPRB (WWF, 2002).
The literature suggests that these forests can be
located in either floodable or non-floodable terrains (WWF, 2002).
In the Brazilian classification system, subtypes of deciduous forest include: (1) alluvial,
(2) lowland, (3) submontane, and (4) montane (IBGE, 1992).
In the UPRB, only the
lowland (1.2.2.2) and submontane (1.2.2.3) subtypes are described and both are in non-
55
floodable areas of the state of Mato Grosso do Sul.
amazonian and Argentinean-andean species.
These subtypes present Afro-
Anadenanthera, Phyllostylon, Hymenaea,
and Aspidosperma are frequent genera in these forests (PNMA, 1997). In the UPRB, the
highest canopies observed present 20 m (PNMA, 1997).
Regionally, these forests are
known as “dry forests” (“matas secas”) and prefer calcareous substrates (PNMA, 1997).
Cerrado Savanna (1.3.1)
In the proposed UPRB classification system, Cerrado savanna includes all arborealherbaceous formations that belong to or are influenced by the Cerrado floristic province.
In the Brazilian official classification system (IBGE, 1992), Cerrado savannas are
subdivided into four subtypes: (1) forested savanna (“cerradão”), (2) treed savanna
(“cerrado”), (3) parkland (“savana parque – parque de cerrado”), and (4) Gramineaewoody savanna (“savana gramíneo-lenhosa”). These four subtypes can be found in the
UPRB. However, in the present study, the forested and the Gramineae-woody savannas
are excluded from the savanna class and placed in the forest and grassland classes,
respectively, because of physiognomic differences (Ribeiro and Machado, 1998).
The treed Cerrado savanna (1.3.1.1), known regionally as “cerrado,” and the parkland
(1.3.1.2) subtype are considered of natural and/or anthropogenic origin (PNMA, 1997).
In certain areas, especially those employed for cattle ranching, the Cerrado savannas are
subjected to periodical fires, usually of annual frequency (PNMA, 1997).
Sparsely
distributed trees averaging 5 m of height with thin and crooked trunks compose the
arboreal stratum of the treed Cerrado savanna subtype (PNMA, 1997). The herbaceous
stratum is continuous and dominated by species from the Gramineae, Cyperaceae, and
Eriocaulaceae families (PNMA, 1997).
The most frequent species include: Curatella
americana, Terminalia argentea, Luehea paniculata, Dimorphandra mollis, Annona
crassifolia, Stryphnodendron sp. (PNMA, 1997). A sparse shrubby stratum is sometimes
present, in which short palms predominate; the most common of them are from the
genera Astrocaryum and Diplothemium (PNMA, 1997). The RADAM Brazil project (MME,
1982b), which refers to vegetation regions rather than vegetation types, presents two
subcategories for this subtype: (1) without gallery forest, and (2) with gallery forest.
The parkland subtype is characterized by a predominant herbaceous stratum comprised
of hemicryptophytes and geocryptophytes, where species of Gramineae and Cyperaceae
are the most common (PNMA, 1997).
Isolated nano and microphanerophytes (3–5 m)
form the highly sparse arboreal stratum (PNMA, 1997).
In certain areas, parklands
present formations composed exclusively or predominantly by specimens of one tree
species, such as Tabebuia aurea or Curatella Americana (PNMA, 1997). In the RADAM
project (MME, 1982a), parkland is classified an herbaceous formation regionally known
as campo sujo (shrubby rangeland); however, Ribeiro and Machado (1998) classify it as a
savanna.
56
Chaco Steppe Savanna (1.3.2)
Chaco steppe savanna includes all arboreal-herbaceous formations that belong to or are
influenced by the Chaco floristic province: treed (1.3.2.1) and parkland (1.3.2.2) steppe
savanna subtypes. These vegetation types are present in the Chaco of Brazil, Paraguay,
and Bolivia.
Steppe savanna is the term used in the Brazilian classification system to
denote vegetation types from the Chaco and Caatinga floristic provinces. This descriptor
was originally employed in Africa to designate a tropical vegetation type with
characteristics of steppe, which is subjected to a double seasonality marked by two
annual dry seasons (IBGE, 1992).
Chaco savannas have also been regarded as xeric
savannas (Frey, 1995).
The Chaco penetrates Brazil near the confluence of the Apa and Paraguay rivers and
expands northward, bordering the Paraguay River, to the State of Mato Grosso (PNMA,
1997).
Chaco steppe savanna is usually associated with saline soils (IBGE, 1992).
In
Brazil, the steppe savanna is subdivided into: (1) forested steppe savanna, (2) treed
steppe savanna, (3) parkland steppe savanna, and (4) Gramineae-woody steppe savanna
(IBGE, 1992). All of these subtypes are present in UPRB (IBGE, 1992).
The forested
subtype has been described in the forest section, and the Gramineae-woody steppe
savanna is described among the herbaceous formations.
The treed Chaco steppe savanna (1.3.2.1) presents the same floristic characteristics as
the forested steppe savanna, but it consists of shorter trees that are less densely
grouped, forming an open arboreal stratum coexisting with a continuous but seasonal
herbaceous stratum (PNMA, 1997).
The predominant species of phanerophytes belong
to the genera Prosopis, Acacia, Ziziphus, and Celtis. It can be of anthropic origin, when
trees of forests are extracted favoring the extension of the herbaceous stratum (IBGE,
1992; PNMA, 1997).
More sparsely dispersed trees characterize the arboreal stratum of the parkland Chaco
steppe savanna (1.3.2.2).
This subtype usually occurs in depressions that become
inundated during the rainy season because of their poor drainage (PNMA, 1997).
Species of the genera Acacia and Machaerium are common; in the dry season,
Leptochloa sp. spreads through formerly flooded areas (PNMA, 1997).
This steppe
savanna subtype also includes the regionally named formation “carandazal” located in
floodable areas where the palm Copernicia alba forms almost pure groups (PNMA,
1997).
In the Paraguayan literature, “carandazal” is mentioned as “hydromorphic
savanna.” It occurs on structured soils rich in clay, with predominance of gleycosol and
vertisol, seasonally flooded during three to six months per year due to precipitation and
river flooding (MAG and BGR, 1999). It lacks an intermediate stratum; the ground-level
herbaceous stratum is formed by annual marshy vegetation (MAG and BGR, 1999).
57
Cerrado Grassland (1.4.1)
Cerrado grasslands are found in seasonally flooded, floodable, and non-floodable areas
and is designated in Brazilian classification systems as Gramineae-woody savanna.
Cerrado grassland can be of natural and/or anthropogenic origin (PNMA, 1997). In the
natural state, it is constituted by grasses and scattered shrubs, small isolated trees and
stem-less palms (PNMA, 1997).
Fire favors the establishment of geophytes over
hemicryptophytes (PNMA, 1997). The most common woody species are from the genera
Andira, Cassia, Byrsomina, and Bauhinia (PNMA, 1997). Frequent palms are Attalea sp.,
Orbignya eichleri, Allagoptera campestris; the herbarceous Gramineae stratum is mostly
comprised
of
species
of
Axonopus, Andropogon, Aristida, Tristachya, Paspalum,
Hemarthria, Digitaria, Panicum, and Brachiaria (PNMA, 1997).
Chaco Grassland (1.4.2)
Chaco grasslands are found in seasonally flooded, floodable, and non-floodable areas.
It is a predominantly herbaceous formation of Chaco origin in which Paratheria
prostrata, Aristida sp., and Elyonurus sp. are common (PNMA, 1997). Scattered thorny
shrubs, such as Celtis sp., also can be found (PNMA, 1997).
Land Cover in Pilot Area
Vegetation in the pilot area is dominated by Chaco formations, which include
semideciduous and deciduous forest, steppe savanna and Chaco grassland.
These
vegetation types, particularly the savannas and grasslands, are subjected to periodic
inundation, occurring on seasonally flooded and floodable lands.
Cerrado formations
and submontane open rain forest have not been mapped in the pilot area (IBGE, 1992;
PNMA, 1997; MME, 1982b). Chiquitano Dry Forest formations are present in the
northwestern corner of the pilot area. Anthropogenic categories (agriculture land, urban
land) are also observed.
I MAGE P ROCESSING R ESULTS (P ILOT A R E A )
A total of ten land cover classes were identified in the two classified images: (1) open
water, (2) deciduous forest, (3) semideciduous forest, (4) savanna, (5) floodable savanna,
(6) seasonally flooded savanna, (7) grassland, (8) floodable grassland, (9) seasonally
flooded grassland, and (10) bare land (Figure 7). The extent of open water is the same in
the two classified images because it results from the multi-flood extent image. All
pixels previously classified as open water that did not match the permanent water class
of the multi-flood extent image were reclassified to floodable or seasonally flooded
grasslands.
58
59
Figure 7. Land cover classification results.
It was not possible to discriminate the anthropogenic versus natural classes through the
unsupervised classification approaches performed in this study.
Natural land cover
classes were distinguished to the third level of the proposed classification system.
Land Cover Classes
Bare Land
Areas without vegetation, excluding open water, but including parts of urban areas and
roads, were classified as “bare land.”
Based on visual assessment of the unprocessed
images, the majority of the areas classified as bare land, in both approaches,
correspond to natural areas, which generally appear as some type of Chaco grassland or
savanna on Brazilian and Paraguayan vegetation maps (UNA and GTZ, 1991; PNMA,
1997).
In the process of assigning classes in the two-date approach, it was observed
that a large extent of the bare lands present on the 11/14/1999 image appeared as
grasslands or savannas on the 7/30/1998 image.
Therefore, the two-date classified image presents a lower extent of bare lands and more
grasslands and savannas. The difference of 16% corresponds mainly to grasslands and
savannas that are located in non-floodable areas (as determined by the three-date flood
extent image), since the bare lands classified in floodable and seasonally flooded areas
were reclassified, in both approaches, as categories of grasslands (Table 7).
The
seasonality or change in the land cover of these areas may be caused by flooding that
was not detected in this study or it may be caused by vegetation succession promoted
by other natural causes or anthropogenic intervention.
Table 7. Coverage of land cover types in the two classified images.
One-date approach
Class
Area (ha)
Open Water
Deciduous Forest
Semideciduous Forest
Area (ha)
% (B)
Difference
in % (A - B)
24,532.92
0.80
24,532.92
0.80
0
113,223.24
3.69
72,177.30
2.35
1.34
1,368,078.48
44.60
-5.74
1,192,097.52
Savanna
% (A)
Two-date approach
38.86
255,674.43
8.34
381,838.59
12.45
-4.11
Floodable Savanna
87,663.78
2.86
182,256.84
5.94
-3.08
Seasonally Flooded Savanna
14,999.31
0.49
17,749.17
0.58
-0.09
2.49
332,717.04
10.85
-8.36
19.55
483,843.87
15.77
3.78
48,570.66
1.58
0.17
5.08
16.09
100.00
-
Grassland
76,386.42
Floodable Grassland
599,774.40
Seasonally Flooded Grassland
Bare Land
Total
53,833.77
1.76
649,259.46
21.17
155,680.38
3,067,445.25
100.00
3,067,445.25
60
Grasslands and Savannas
Classes of grasslands and savannas were considered seasonally flooded, floodable, or
non-floodable. The floodable classes correspond to areas of potential flood, while the
extent of the seasonally flooded classes is considered the minimum area periodically
flooded. The seasonally flooded areas in the pilot area correspond mainly to grasslands
and palm savannas (parkland Chaco steppe savanna) from the Chaco ecoregion (MME,
1982b; UNA and GTZ, 1991; IBGE, 1992; PNMA, 1997).
Savannas and grasslands of
uncertain floristic origin were encountered in the Bolivian section of the pilot area.
Anthropogenic areas with pastures could not be spectrally differentiated and were
classified as grasslands. Grasslands (as well as other vegetation types) may also include
lagoons covered by aquatic vegetation.
Semideciduous Forest
Semideciduous forests in the study area are predominantly comprised of non-floodable
forests but also include riparian forest and forest in low areas that might be seasonally
flooded or in floodable areas.
The forests of this class are considered semideciduous
based on Brazilian and Paraguayan vegetation and land cover maps of the pilot area
(MME, 1982b; UNA and GTZ, 1991; IBGE, 1992; PNMA, 1997).
It was not possible to
divide this class into the various semideciduous forest types occurring in the area.
Deciduous forest types could be mistakenly included in this class, particularly in the
Brazilian section, where deciduous forest is found in the east-southern corner of the
scene. The two-date approach presents a greater extent of semideciduous forest, close
to 6 percent more than that of the one-date approach. This discrepancy is mainly due
to the differences in the classification of deciduous forest.
Deciduous Forest
The decision to classify certain forested areas as deciduous, mainly in Bolivia, was based
on the literature (WWF, 2002). In both classification approaches, this class of deciduous
forests is spectrally distinct. Particularly, in the two-date approach, it was observed that
in 7/30/1998 the vegetation cover is scarce in comparison to the evident forest cover
present in 11/14/1999. This reaffirms the strong seasonality of these forests. Areas of
deciduous forest found on vegetation maps of the Brazilian section (MME, 1982b) were
not differentiated from the semideciduous forest class and do not present the same
seasonality as the identified deciduous forest when comparing the two dates of imagery
(07/30/1998 and 11/14/1999).
Accuracy Assessment
It was not possible to evaluate all ten classes of the classified images because the
reference data do not include deciduous forest. Additionally, flooding aspects had to be
61
disregarded because the photographs used as reference data were taken at different
times of the year (December 2000 and March 2002).
Therefore, in the comparison
between the two approaches of land cover classification, only five combined classes
were considered:
(1) open water, (2) forest, (3) savanna, (4) grassland, and (5) bare
land.
The results show the two-date approach to be superior to the one-date approach
(Tables 8, 9, and 10).
The greatest difference between the two approaches is the
classification of bare land. In the one-date classification, the user’s accuracy of the bare
land class is extremely low, approximately 8%. In the two-date classification, the user’s
accuracy of the bare land class is greater, around 45%, but it is still the lowest among
the classes.
In both cases, the main source of error lies in the confusion of bare land
with savanna. The two-date approach also shows better results in the classification of
savanna, but this class still presents confusion with forest, bare land, and grassland.
Regarding the latter class, the two-date approach presents greater user’s accuracy (75%
versus 70%), but lower producer’s accuracy (69% versus 82%), which indicates that the
two-date approach produced a grassland class with less error, but that it also is less
inclusive of correctly classified grasslands than that of the one-date approach.
In
general, grassland shows less confusion with bare land than does savanna. The classes
presenting the greatest values of accuracy, in both approaches, are open water and
forest.
As expected, the open water class presents the same accuracy for both
approaches. Forest yielded similar accuracy results in both approaches.
Table 8. Accuracy assessment results for one-date approach.
Open Water
Forest
Classiffied
Savanna
Data
Grassland
Bareland
Total
Open
4
1
0
1
0
6
Forest
0
67
1
0
2
70
Reference Data
Savanna
Grassland
0
1
10
3
7
4
16
45
30
2
63
55
Overall Accuracy: 63.32%
KHAT Statistic: 0.5066
User's Producer's
Accuracy Accuracy
(%)
(%)
Open Water
80.00
66.67
Forest
82.72
95.71
Savanna
58.33
11.11
Grassland
70.31
81.82
Bareland
8.11
60.00
Class
62
Bareland
0
0
0
2
3
5
Total
5
81
12
64
37
199
Table 9. Accuracy assessment results for two-date approach.
Reference Data
Open Water
Open Water
4
Forest
1
Classified
Savanna
0
Data
Grassland
1
Bareland
0
Total
6
Forest
0
68
0
2
0
70
Savanna
0
11
36
10
6
63
Grassland
1
6
10
38
0
55
Bareland
0
0
0
0
5
5
Total
5
86
46
51
11
199
Overall Accuracy: 75.88%
KHAT Statistic: 0.6563
User's
Accuracy
(%)
Class
Open Water
Forest
Savanna
Grassland
Bareland
Producer's
Accuracy
(%)
80.00
79.07
78.26
74.51
45.45
66.67
97.14
57.14
69.09
100.00
Table 10. Comparison of classification approaches.
Parameter
Error matrix
One-date
approach
Two-date
approach
KHAT
0.5066
0.6563
Variance
0.0016
0.0018
Z statistic
12.67
15.51
Accuracy
63.32%
75.88%
One-date versus two-date approach
Z statistic: 2.5722
Finally, the two-date approach has a greater KHAT statistic (0.66 versus 0.51) and
overall accuracy (76 versus 63%), indicating not only that this classification approach is
more accurate when compared to the one-date method, but also in regard to random
classification (Lillesand and Kiefer 2000).
The Z test (Congalton and Green 1999)
63
comparing the KHAT statistic values of the error matrices confirms that the accuracy
results of the two classification approaches differ significantly at the 95% confidence
level (Z = 2.57) (Table 10).
C ONCLUSIONS
This study standardizes the language of disparate land cover/vegetation classification
schemes into one integrated system for the entire UPRB. The proposed system is open
ended, has a clear hierarchical structure of three levels, and presents classification
criteria for flooding that permits the addition of other land cover and vegetation types
and levels of finer scale.
In the classification of vegetation, hierarchical priority was
given to physiognomy, which is present in the structure of the majority of the
classification schemes reviewed, and has proven to be, in this study, one parameter that
allows clear separability of vegetation classes in the visual interpretation and automated
classification of Landsat imagery.
The image processing results, limited to the pilot area, clearly indicate that the
seasonality of vegetation and flooding must be taken into account; multitemporal data
are particularly important for the identification and differentiation of savannas and
grasslands, which are highly variable in the region, presumably a result of the
alternation of contrasting seasons.
The two-date unsupervised classification approach
has a significantly greater overall accuracy and KHAT statistic in comparison to the onedate approach, which indicates that a single scene cannot provide data to properly
classify the land cover in the pilot area. Of all classes, the most problematic is “bare
land,” which designates areas recuperating from natural or anthropogenic disturbances
(e.g., fire, flood). The two-date classification shows greater accuracy mainly because of
the better classification of bare land and savanna. However, the two-date classification
still presents an overall accuracy below the 85% acceptable for mapping (Anderson et al.
1976).
The addition of images from intermediate seasons could provide a better
characterization of the seasonality of vegetation and improve the classification results,
especially in the grassland and savanna areas.
The methods suggested consider the characteristics of the pilot area and the results
achieved are specific to this area.
It cannot be generalized that the land cover
classification system and/or the multispectral classification method are appropriate for
other areas of the UPRB; it can only be suggested that these methods will work in areas
presenting similar environmental conditions and land cover types. In areas such as the
uplands, where flooding and vegetation seasonality may not be an issue, the temporal
variability might not be as important. In areas subjected to seasonal changes where, for
example, bare land can be associated specifically with only one vegetation type, a
multitemporal classification will not be as critical.
64
In the pilot area, the multitemporal aspect proved to be fundamental for land cover
classification. Although the differentiation of the savanna and grassland physiognomies
was not supported by strong values of accuracy, the comparison of the two classification
approaches demonstrated that large extents of the savanna and grassland classes were
not recognized when only one date of imagery was used.
Also noted is that the
overestimated bare land class generated in the one-date classification approach cannot
be indisputably associated with a single land cover type, which reinforces the
importance of using multiple dates to depict intra-annual variability of land cover even
in a single classification. Further research should experiment with the addition of more
dates of imagery and other classification procedures to enhance discrimination between
savannas and grasslands.
A CKNOWLEDGEMENTS
For revisions and important suggestions, thanks to Richard Kempka (Ducks Unlimited),
Thad Wasklewicz (The University of Memphis), Montserrat Carbonell (Ducks Unlimited),
Kelley Crews-Meyer (The University of Texas at Austin) and Kenneth Young (The
University of Texas at Austin). This study was conducted with the financial and logistic
support of the U.S. Forest Service, the U.S. Fish and Wildlife Service, Ducks Unlimited
and the University of Memphis.
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68
2C. U P P E R P ARAGUAY RIVER INUNDATION P REDICTION USING RAINFALL AND NDVI: B ASIN AND
S IX S UB B ASIN M ODELS
WILLIAM T. LIU14 AND FÁBIO M. AYRES15
A BSTRACT
Inter annual variation of monthly River Water Level (RWL) at Ladário Hydrological Station
(LHS) was used to study the flood conditions of the entire Upper Paraguay River Basin
(UPRB). Six sub basin models were also constructed to investigate the contribution of
water collected in the upper sub basins on individual sub basin RWL estimations. The
responses of RWL to Precipitation (PCP) and to Normalized Difference Vegetation Index
(NDVI) were analyzed. A combined use of PCP and NDVI data is proposed to predict RWL
at LHS, which monitors the water collected from the upper UPRB watershed. Inundation
area estimation as a function of RWL proposed by Hamilton et al. (1996) was applied to
predict Pantanal inundation area using both recorded and predicted RWL data of 1981 to
2000.
Our technique demonstrated that by applying RWL prediction model and the inundation
area estimation model proposed by Hamilton et al. (1996), the Pantanal inundation area
extent could be predicted one month in advance with reasonable success. Therefore, the
statistical approach presented herewith may provide a useful tool to predict RWL and,
hence, prevent flood damage in high RWL periods as well as control river transportation
traffic in order to prevent riverbank erosion during low RWL periods. For future studies,
an adequate hydrological simulation model based on a high accuracy digital elevation
model and a rainfall forecasting system, such as a radar system, are needed to fulfill a
real time flood advancing prediction and mitigation tasks.
I NTRODUCTION
The Pantanal wetland is one of the world’s largest continental wetlands, and collects the
drainage water from the Upper Paraguay River Basin (UPRB). The Pantanal holds one of
the most diversified human patrimonies, housing innumerous flora and fauna. The
distinct annual cycle of inundation provides rich natural resources for economically
important fish and wildlife species, and more recently, ecological tourism.
Fish yields
may vary from the alteration of their life cycle caused by seasonal and annual variation
of inundation patterns (Welcomme, 1985). Animals may have difficulties finding dry
refuges during unpredicted high flood years (Mittermeier et al., 1990). Therefore the
occasional unpredicted high floods and severe droughts affect fish and wildlife as well
as important cattle production areas. During the past 30 years, agricultural activities and
14
Universidade Católica Dom Bosco, Campo Grande, MS, Brazil. E-mail address: [email protected]
15
OIKOS (Cooperativa de Trabalho Sócio-ambiental), Campo Grande, MS, Brazil; [email protected]
69
cattle production in the catchment have increased considerably. Improper land
management on predominantly sandy soils in the upper basin continues to cause
serious erosion and acceleration of sediment load in the flood plain. In addition to the
gradual loss of ranchlands, unpredicted floods often result in serious cattle loss. Also,
due to recent increase of river transportation, riverbanks erosion in low water level
periods becomes a more serious issue every year. Therefore, the purpose of this study is
to develop an alternative river water level prediction model in order to predict the
occurrences of high flood for suitable mitigation planning and low river water level for
river traffic controls.
Several researchers have investigated Pantanal inundation behaviors. Giddlings and
Choudhury (1989) have observed that the Pantanal normal maximum water surface
occurs
in
temperature
April,
which
images
was
collected
detected
from
by
the
Nimbus-7
microwave
37
GHz
polarization difference
Scanning
Multifrequency
Microwave Radiometer (SMMR) data from 1979 to 1985. Galdino and Clarke (1997)
predicted the possible peak RWL occurrence month based on the probability analysis of
6 RWL classes obtained from the RWL data for the period of 1990 to 1996. They
observed that the annual occurrence of maximum monthly RWL at LHS shifted gradually
from April to July while the monthly RWL decreased from over 6 meters to lower than 4
meters.
Hamilton et al. (1996) presented a Pantanal inundation area estimation approach using
passive
microwave
remote
sensing
data
obtained
from
Nimbus-7 SMMS. They
constructed a mixing model that calculated typical fractions of water, inundation area
and no-inundation area from representative cells and then extended to the whole region
using Landsat TM images. They observed that the maximum inundation occurred as
early as February in the north and as late as June in the south, reflecting the gradually
delayed drainage time in responding to rainfall from the upper to the lower part of the
UPRB. They also presented an inundation area estimation equation that calculates the
inundation area as a function of the previous two-month averaged RWL monitored at
LHS. The equation is described as follows:
Equation 1
INUNDAt = 18.52 (RWL t+1 + RWL t+2 )/2 – 17.309
(1)
Where:
INUNDAt = Inundation area of month t (km);
RWL
t+1
and RWL
t+2
= river water level (m) of second and third month after month t,
respectively.
Although the inundation area estimation equation proposed by Hamilton et al. (1996) is
very useful for long-term hydrology and climate diagnosis, it is not for prediction
70
purposes, since the estimation is based on the RWL data two months after the
inundation occurrence. Normalized Difference Vegetation Index (NDVI) is an index that
provides a standardized method of comparing vegetation greenness between satellite
images, also provides a measure of surface soil moisture conditions (Liu et al., 1994; Liu
and Kogan, 1996; Liu and Juarez, 2001). NDVI reaches its maximum value at a threshold
rainfall amount beyond which further increase of rainfall will not increase surface
greenness or the NDVI value. Therefore, NDVI fails to indicate high RWL caused by
excesses of rainfall. In order to overcome this, a combination of both rainfall and NDVI
data are suggested for developing a RWL prediction model.
A combined use of the
inundation area estimation method proposed by Hamilton et al. (1996) and the RWL
prediction model constructed in this study will be demonstrated and may provide a
useful tool for climatic statistical modeling for flood extent prediction.
M ETHODS
Study Area
The UPRB has a catchment area of 485,000 km2 and is located in central South America,
covering parts of western Brazil, eastern Bolivia and northeastern Paraguay. Annual
mean temperature stays relatively constant ranging from 24.5°C to 25.6°C. Annual
precipitation (PCP) ranges from 1100 mm in the west to 1650 mm in the east with a
distinct wet (October to April) and dry season (June to August). Monthly rainfall in the
dry season is generally less than 50 mm/month and in the wet season is usually higher
than 100mm/month. Monthly rainfall in both transit months (May and September) varies
between
50
to
100
mm/month.
Table
1
shows
the
climate
data
of
several
meteorological observation stations located in the UPRB (DNMET, 1992).
Table 1 – Climatic data of the Upper Paraguay River Basin (Data source: DNMET, 1992)
________________________________________________________________________________
Station Name
Latitude
Longitude
Mean
Total Rainfall
temperature
°C/mm/year
________________________________________________________________________________
Corumbá
19.05°S
57.30°W
25.0
1118
Coxim
18.30°S
54.46°W
24.5
1501
Cáceres
16.03°S
57.41°W
25.2
1460
Cuiabá
15.33°S
56.07°W
25.6
1315
Diamantino
14.24°S
56.27°W
25.2
1619
________________________________________________________________________________
Figure 1 illustrates the UPRB boundary that extends from latitude 14°S to 23°S and
longitude 52°W to 61°W. The Pantanal wetland depression (Figure 1) occupies an area of
71
137,000 km2 and is formed by a mosaic of alluvial fans of Pleistonncene origin
(Klammer, 1982), collecting the drainage water from the UPRB watershed. The Pantanal
flat plains have a gentle slope of 2.5 cm/km with a gradual increase of elevation from
west (80 m) to east and north (250 m). The upland drainage basin consists of flat plains
to the west and elevated plateaus and low mountains to the north and east with
elevation ranging from 250 m to 1200 m. The UPRB has very distinct hydrological
features. First, some of its tributaries may change their course from year to year, which
is caused by the high velocity of river water acting on a fragile and curved sandy
riverbank.
Figure 1. Location of the Upper Paraguay River Basin (UPRB) with its upper and lower
divisions and Ladário Hydrological Station and six rainfall stations, including Arenapólis,
Quebo, Porto Estrela, Ponte Cabaçal, N. S. Livramento and Barão de Melgaço.
Figure 2 shows numerous intersecting tributaries. Second, due to the Pantanal
depression formed by a mosaic of alluvial fans, inundated sub basins often invade
adjacent sub basin flood plains instead of discharging into the river. Third, there is a
distinct flood wave delay of one to five months from north to south due to slow ground
water drainage in the flat floodplains (Hamilton et al. 1996).
72
Figure 2. Aerial photo of the Upper Paraguay River tributaries in the Pantanal Nabileque
River region.
Data Used
River Water Level Data
RWL data recorded at the LHS (Latitude: 19° 05´S; Longitude: 57° 30´W) for the period of
January 1981 to December 2000 provided by the Brazilian Marine Corps at Corumbá,
Mato Grosso do Sul State, were used in this study. The RWL measured at the LHS
monitors the total water drained from the upper part of the UPRB. For the same period,
monthly PCP data of six rainfall stations, including Arenápolis (14.51°S, 56.1°W), Quebo
(14.65°S, 56.11°W), Porto Estrela (15.31°S, 56.23°W), Ponte Cabaçal (15.47°S, 57.9°W), N.
S. Livramento (15.77°S, 56.35°W) and Barão de Melgaço (16.19°S, 55.95°W), provided by
the Brazilian National Water Agency (Agencia Nacional de Agua, ANA) were used. All six
rainfall stations are located outside the Pantanal wetland area and are concentrated in
the northern part of the sub basin. Averaged values of six station rainfall data were used
to represent the rainfall amount received in the upper part of the UPRB.
NDVI data
NDVI monthly maximum value composite data (Holben, 1986) with a resolution of 8 km
by 8 km for the period of August 1981 to December 2000, provided by the Distributed
Active Archive Center at Goddard Space Flight Center (DAAC/GSFC) of NASA were used
in this study (AVHRR-Advanced Very High Resolution Radiometer). According to
Eidenshink et al. (1997), these data have already been processed with radiometric
calibration, using the NOAA standard method (Kidwell, 1995; Rao and Chen, 1995), and
73
atmospheric corrections including Raleigh scattering using method of Gordon et al.
(1988) and ozone absorption using the method of Fleig et al. (1983). NDVI is a ratio of
the reflectance values of AVHRR channels 2 (Ch2: 0.725 -1.10 µm ) and 1 (Ch1: 0.580.68 µm Ch1: 0.58-0.68 µm), and is expressed by the following equation:
Equation 2.
NDVI=(Ch2-Ch1)/(Ch2+Ch1).
(2)
The watershed drainage area monitored by LHS was used to obtain average monthly
NDVI. In the present study, only the upper part of the basin was used to construct the
RWL prediction model. The heavy black line in the middle of Figure 1 shows the division
of the UPRB. Only the area north of this line was under consideration since the RWL at
LHS collects all water drained from this catchment area. The interflow effect between
sub basins outside this area was not considered
BAP Model Construction and Validation
According to Hamilton et al. (1996), there is a delay of 2 to 6 months for the peak
monthly RWL at LHS in response to peak rainfall in the Pantanal. The progressive flood
wave along regional hydrological flow paths starts in the northern and eastern parts of
the Pantanal and progressively moves towards the southern regions. Therefore,
correlation analysis between RWL and PCP was carried out to estimate the delay of RWL
responding to PCP. Correlation analysis between RWL and NDVI was also carried out to
estimate the delay in variation of RWL responding to NDVI.
The months with the higher correlation coefficients between RWL and PCP and between
RWL and NDVI were used as independent variables for model construction. A stepwise,
multiple linear regression technique was applied to construct the model. Due to the lack
of NDVI data for 1994, the available data were divided into in two periods: August 1981
to December 1993 and January 1995 to December 2000. The NDVI data for August
1981 to December of 1993 were used for model construction. Usually, the modelpredicted RWL values obtained from the data set used for model construction are called
simulated values. These simulated values were not real predicted values but were
adjusted values obtained from the model construction process using a statistical bestfit curve approach. Therefore, for the purpose of validating the model, an independent
NDVI data set of January 1995 to December 2000 was used to run the model and to
compare the predicted and observed RWL values. The inundation area estimation
method presented by Hamilton et al. (1996) was used to estimate the inundation area
for the period of 1981 to 2000 (Equation 1). Further, Equation 1 and the RWL prediction
model were used to predict the inundation area. The results were compared to the
inundation area estimation using observed RWL data.
74
D ISCUSSION
AND
R ESULTS
River Water Level Analysis
Table 2 summarizes the occurrence of both maximum and minimum RWL for the period
of 1981 to 2000. From the comparison of 20 annual cycles of RWL monitored at the LHS,
it was observed that the occurrence of maximum RWL month shifted from April in higher
flood years to July in lower flood years. This means that in high rainfall years, a higher
rainfall amount in the wet season causes higher surface runoff water. On the other hand,
the minimum RWL occurred mostly in December but in some years it occurred in either
November or January. It was found that in the wet season, the highest RWL of 6.57 m
occurred in April of 1988 and the lowest RWL of 4.2 m occurred in July of 1986. In the
dry season, the highest RWL (3.30 m) occurred in December of 1992 and the lowest RWL
(1.19 m) occurred in November of 1999.
Table 2. Maximum and minimum River Water Level (RWLmax and RWLmin) at Ladário
Hydrological Station for the period of January 1981 to 2000. (Data Sources: Brazilian
Navy at Corumbá, MS)
Year
RWLmax (m)
Month
RWLmin (m)
Month
1981
5.43
5
1.95
12
1982
6.41
4
2.52
12
1983
5.35
5
2.39
12
1984
5.04
6
2.47
11
1985
6.04
4
1.56
13
1986
4.22
7
1.32
12
1987
4.94
6
1.40
11
1988
6.57
4
1.41
12
1989
6.10
5
1.87
13
1990
4.45
6
1.95
12
1991
5.40
5
2.37
12
1992
5.35
6
3.25
13
1993
5.13
5
1.42
12
1994
3.91
7
1.42
11
1995
6.50
4
2.02
12
1996
5.05
6
1.97
12
1997
5.66
5
2.13
13
1998
4.61
6
2.17
11
1999
4.58
6
1.19
11
2000
4.62
6
1.21
11
River Water Level Responses to PCP and NDVI
75
Inter-annual and seasonal hydrological variability were analyzed by comparing the time
series plots of RWL, PCP and NDVI from 1981 to 1993. Figures 3 to 6 show the time
series plots of four years representing four extreme RWL cases:
−
A maximum RWL of 6.57m in the wet season occurred in April 1988 (Figure 3);
−
A minimum RWL of 1.19m in the dry season occurred in November 1999 (Figure 4);
−
A maximum RWL of 3.30m in the dry season occurred in December 1992 (Figure 5);
−
A minimum RWL of 4.20 in the wet season occurred in July 1986 (Figure 6).
Water Level (10m), NDVI and PCP (m)
0,7
0,6
0,5
0,4
0,3
0,2
Water Level (10)
0,1
NDVI
PCP (mm)
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Time Period (month)
Figure 3. Time series plot of monthly water level at Ladário Hydrological Station
regional averaged monthly NDVI and precipitation for the UPRB from 01/1988 to
02/1989
0,7
0,6
0,5
Water Level (10)
0,4
NDVI
PCP (mm)
0,3
0,2
0,1
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Time Period (month)
Figure 4. Time series plot of monthly water level at Ladário Hydrological Station and
regional averaged monthly NDVI and precipitation of UPRB for the period of 01/1999 to
02/2000
76
0,7
0,6
0,5
Water Level (10)
NDVI
0,4
PCP (mm)
0,3
0,2
0,1
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Time Period (month)
regional averaged monthly NDVI and precipitation of UPRB for the period of 01/1992 to
02/1993
0,7
0,6
0,5
0,4
Water Level (10)
NDVI
0,3
PCP (mm)
0,2
0,1
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Time Period (month)
regional averaged monthly NDVI and precipitation of UPRB from 01/1986 to 02/1987.
It was observed that NDVI reached a value of around 0.6 mostly in November and
remained above this value for a period as long as 8 to 9 months (November to June or
July). This indicates that the vegetation surface reaches its maximum greenness right
after the beginning of the wet season. Further increase of rainfall amount in the
following months does not increase NDVI. NDVI maintains its maximum value for 2 to 3
months after the end of the wet season (May to July) and drops to its minimum at the
end of dry season (mostly in September). In the Pantanal, with a smooth slope of
77
2.5cm/km, a higher soil moisture condition indicated by vegetation greenness generally
persists for a longer period of time. The slow discharge of subsurface groundwater
caused the RWL at LHS to decrease to 1.19 m in 1999, the driest year. Therefore, NDVI
during the drying phase behaves similarly to RWL at its decreasing phase. Because free
surface water absorb both visible and near infrared bands, such as AVHRR bands 1 and
2, values of NDVI close to zero (shallow water) or negative NDVI values (deep water)
occur in the wet season. In the Pantanal, NDVI saturates at a low value of around 0.6,
due to the larger flooded area and innumerous small shallow ponds. This limits the
application of NDVI to infer a high RWL in the wet season. However, in peak rainfall
seasons, monthly PCP data from December to March were mostly higher than 150 mm.
Considering an evapotranspiration rate of 150 mm/month in the region, most of the
excess water (PCP over 150 mm) contributes to surface runoff, which results in a higher
than anticipated RWL. Therefore, in the wet season, PCP provides better high RWL
estimates. In contrast, the dry season monthly PCP was lower than 50 mm/month or
close to zero for several months, which does not provide a fair amount of low RWL
values maintained by the ground water. Due to the fact that PCP provides better
estimates in the wet season and NDVI provides better estimates in the dry season, both
PCP and NDVI were used to develop the RWL prediction model.
The six rainfall stations used for calculating PCP data are located in the upper part of the
basin, approximately 400 km north of the RWL station. Therefore, a correlation process
was carried out to find the RWL delay responding to the rainfall received in the upper
part of the basin. The correlation process was also performed for NDVI to RWL and PCP
to NDVI. Table 3 shows the correlation coefficient (r) of RWL to PCP and RWL to NDVI
with a time lag of RWL from zero to the particular month showing the highest r-value.
The highest r-value of 0.809 was obtained for RWL responding to 5 months of PCP and
a highest r-value of 0.624 was obtained for RWL in responding to after 3 months. Table
3 also shows that the highest r-value of 0.579 was obtained for NDVI in responding to
PCP with a time lag of 2 months.
78
Table 2. Occurrence of maximum and minimum River Water Level (RWLmax and
RWLmin) at Ladário Hydrological Station for the period of January 1981 to 2000. (Data
Sources: Brazilian Navy at Corumbá, MS)
Year
RWLmax (m)
Month
RWLmin (m)
Month
1981
5.43
5
1.95
12
1982
6.41
4
2.52
12
1983
5.35
5
2.39
12
1984
5.04
6
2.47
11
1985
6.04
4
1.56
13
1986
4.22
7
1.32
12
1987
4.94
6
1.40
11
1988
6.57
4
1.41
12
1989
6.10
5
1.87
13
1990
4.45
6
1.95
12
1991
5.40
5
2.37
12
1992
5.35
6
3.25
13
1993
5.13
5
1.42
12
1994
3.91
7
1.42
11
1995
6.50
4
2.02
12
1996
5.05
6
1.97
12
1997
5.66
5
2.13
13
1998
4.61
6
2.17
11
1999
4.58
6
1.19
11
2000
4.62
6
1.21
11
Table 3. Correlation Coefficients (r) of PCP x RWL; NDVI x RWL and PCP x NDVI with 1
month time lag of either RWL or NDVI for each step of correlation.
Correlation Coefficient (r )
Time Lag (month)
RWL x NDVI
RWL x PCP
NDVI x PCP
Parameter
RWL
RWL
NDVI
0
0,083
-0,553
0,277
1
0,364
-0,200
0,494
2
0,572
0,189
0,579
3
0,624
0,543
0,531
4
0,500
0,769
-
5
-
0,807
-
6
-
0,652
-
79
River Water Level Prediction
The parameters with a correlation coefficient value higher than 0.5 were considered
suitable for model construction. By examining the correlation coefficients presented in
Table 3, three correlation coefficients of PCP and three of NDVI (Table 3) were used as
independent variables.
By applying the Stepwise Multiple Linear Regression technique,
the model with the highest R2 was selected as a candidate model, which is presented in
the following equation:
Equation 3.
RWLt = 1.19 + 2.89PCP t-6 + 3.30PCP t-5 + 6.05PCP t-4 + 1.59NDVI
t-4
(3)
Where:
RWLt
= River water Level of month t (m);
PCP
= monthly precipitation (m);
NDVI
= monthly NDVI (dimensionless);
Subscripts t-6, t-5 and t-4 represent 6, 5 and 4 months before the month t
respectively.
The model was constructed using RWL, PCP and NDVI data for the period of 1981 to
1993. The model had a R2 value of 0.79 with MSE of 0.36 and SD of 0.60 (P < 0.002). An
averaged absolute error of 15.22% was obtained from model simulation. Figure 7 shows
the comparison of observed and simulated RWL for the period of November 1981 to
April 1994. The model simulated the occurrences and magnitudes of maximum and
minimum RWL relatively well, but failed to simulate the occurrence of peak RWL in 3
years. The peaks of RWL in 1982, 1985 and 1988 occurred in April as opposed to the
simulated peaks that occurred in July. Based on the RWL data, it was observed that these
3 years had maximum RWL over 6 m. This indicates that a larger volume of surface
runoff water caused by intense summer precipitation may contribute significantly to the
RWL peak value 1 to 3 months earlier than in normal rainfall years. The model also failed
to simulate peak RWL in 1984, 1989 and 1993. Instead of a peak in July, the simulated
RWL dropped and then rose again in the following month. A lower NDVI caused by a
larger flood area may have contributed to this error.
Therefore, further research on
rainfall patterns should be conducted in order to detect the anticipation of peak RWL in
high rainfall years and correct the abnormal drop of RWL caused by a low NDVI in the
peak rainy season.
80
7
Observed
simulated
6
River Water Level (m)
5
4
3
2
1
mar/9
jul/93
nov/93
mar/9
jul/92
nov/92
mar/9
jul/91
nov/91
mar/9
jul/90
nov/90
mar/9
jul/89
nov/89
mar/8
jul/88
nov/88
mar/8
jul/87
nov/87
mar/8
jul/86
nov/86
mar/8
jul/85
nov/85
mar/8
jul/84
nov/84
mar/8
jul/83
nov/83
mar/8
jul/82
nov/82
mar/8
nov/81
0
July/1981 - April/1994 (month)
Figure 7. Comparison of observed and simulated river water level for the period of July,
1981 to April, 1994 at Ladário Hydrological Station.
RWL Model Validation
The independent data set of 1995 to 2000 was used for RWL prediction model
validation. The results of model validation showed an average absolute error of 14.45%.
This indicates that the RWL model was relatively stable since this value was within the
simulated error (15.22%). Figure 8 shows the comparison of observed and predicted RWL
for the period of May 1995 to September 2000. There were 39 out of 65 months with
absolute error within 10%, and 19 months with absolute error between 10 to 30%. The
remaining 7 months had error higher than 30%. In 1999, a lowest RWL of 1.19 m was
recorded due to minimal rainfall from May to August and low rainfall recorded in
September (40 mm) and October (80 mm). This demonstrates that the model was not
able to predict this extreme drought event
81
7
Observed
Predicted
6
River Water Level (m)
5
4
3
2
1
m
ai/
95
jul/
95
se
t/9
5
no
v/9
5
jan
/96
m
ar/
96
ma
i/96
jul/
96
se
t/9
6
no
v/9
6
jan
/97
m
ar/
97
ma
i/97
jul/
97
se
t/9
7
no
v/9
7
jan
/98
m
ar/
98
m
ai/
98
jul/
98
se
t/9
8
no
v/9
8
jan
/99
m
ar/
99
m
ai/
99
jul
/99
se
t/9
9
no
v/9
9
jan
/00
m
ar/
00
ma
i/00
jul
/00
se
t/0
0
0
May/1995 - September/2000 (month)
Figure 8. Comparison of observed and predicted river water level for the period of May,
1995 to September, 2000 at Ladário Hydrological Station.
The RWL model tends to predict the yearly maximum RWL with one to three months
delay depending on the maximum RWL value. This error is inevitable since the model
was based on a statistical linear regression approach, which selected the best
correlation of RWL to PCP and RWL to NDVI at fixed months. Table 2 demonstrates that
the maximum RWL month was closely related to the increase of RWL.
Galdino and
Clarke (1997) have also observed this relationship. Therefore, it is possible to improve
the prediction of the maximum RWL occurrence month using RWL data. The occurrence
of annual maximum RWL month as a function of annual maximum RWL value was then
included to improve the model prediction under higher maximum RWL year, which is
presented in Equation 4 as following:
Equation 4.
Mmax = integer (11.4143 – 1.14167RWL)
(4)
Where:
Mmax = the month in which annual maximum RWL (month) occurs;
RWL = annual maximum River Water Level (m)
Equation 4 was constructed using maximum RWL data for the period of 1981 to 2000.
The model had a R2 value of 0.8674 with MSE of 0.1237 and SD of 0.3518 (P <
0.00001). The calculated Mmax value was rounded up to an integer value to obtain the
maximum RWL occurrence month. Table 4 shows the comparison of the observed and
predicted annual maximum RWL month at LHS. The results show that for 12 out of 20
82
years, the equation correctly predicted the annual maximum RWL month. It must be
noted that for the remaining 8 years, the equation’s estimation was one month early,
and none of the estimated maximum RWL months was later than the observed month.
Therefore, the equation can be applied safely to predict the occurrence of annual peak
RWL months. Considering the complexity of water flow between sub basins in this
considerably flat river basin, the combined use of the RWL prediction model (equation 3)
and the maximum RWL month occurrence model (equation 4) works sufficiently for
predicting the maximum RWL month. This simple approach may provide a useful tool to
predict RWL and, hence, prevent flood damage in high RWL periods as well as control
river transportation traffic in order to prevent riverbank erosion during low RWL periods.
Table 4. Comparison of observed and predicted annual maximum RWL month as a
function of annual maximum RWL at Ladário Hydrological Station
Year
RWLmax (m)
Month obs
Month pred
Error
01-12(1981)
5,43
5
5
0
01-12(1982)
6,41
4
4
0
01-12(1983)
5,35
5
5
0
01-12(1984)
5,04
6
5
-1
01-12(1985)
6,04
4
4
0
01-12(1986)
4,22
7
6
-1
01-12(1987)
4,94
6
5
-1
01-12(1988)
6,57
4
4
0
01-12(1989)
6,1
5
4
-1
01-12(1990)
4,45
6
6
0
01-12(1991)
5,4
5
5
0
01-12(1992)
5,35
6
5
-1
01-12(1993)
5,13
5
5
0
01-12(1994)
3,91
7
6
-1
01-12(1995)
6,5
4
4
0
01-12(1996)
5,05
6
5
-1
01-12(1997)
5,66
5
4
-1
01-12(1998)
4,61
6
6
0
01-12(1999)
4,58
6
6
0
01-12(2000)
4,62
6
6
0
Inundation Area Prediction
Hamilton et al. (1996) presented the inundation area estimation model (equation 1),
which estimated well the inundation area using two month averaged RWL at LHS after
83
the inundation had occurred. The RWL prediction model (equation 3), using PCP and
NDVI, can be applied to predict RWL three months before the event occurs. Therefore,
with the combined use of these two models, the inundation area can be predicted one
month before it occurs. Figure 9 shows the comparison of the inundation area
calculated from observed and predicted RWL for the period of 1981 to 2000. An
averaged absolute error of 23.65% was obtained. The error was acceptable since it was a
sum of two estimation errors, that of the RWL prediction model (14.45%) and the other
from the inundation area estimation equation (12%).
120000
Inundation Area Observed
Inundation Area Predicted
Pantanal Inundation Area (km²)
100000
80000
60000
40000
jul/00
dez/99
mai/99
mar/9
out/98
jan/97
ago/97
jun/96
abr/95
nov/95
set/94
jul/93
fev/94
dez/92
mai/92
mar/9
out/91
jan/90
ago/90
jun/89
abr/88
nov/88
set/87
jul/86
dez/85
mai/85
mar/8
out/84
jan/83
ago/83
jun/82
nov/81
0
fev/87
20000
Time Period (month)
Figure 9. Comparison of Pantanal inundation area estimation by Hamilton Method for
the period of November 1981 to July 2000, using observed and predicted RWL at Ladário
Hydrological Station.
C ONCLUSION
AND
S UGGESTIONS
This study presented a RWL prediction model using rainfall and NDVI data and applying
statistical regression approaches. The RWL prediction model had an averaged absolute
error lower than 15%, which is considered acceptable. An annual maximum RWL
occurrence month model was constructed to improve the prediction of maximum RWL
occurrence month. This study also demonstrated that the inundation area extent could
be predicted one month before its occurrence through a combined use of RWL
prediction model (Liu et al., 2002) and the inundation area estimation model proposed
by Hamilton et al. (1996). For further study, it is suggested that several sub basin
models should be constructed to evaluate the consistency of the method as well as to
improve the prediction accuracy. Moreover, a high resolution Digital Elevation Model is
needed to better understand the detailed interflows between sub-basins caused by
84
spatial variation of rainfall. In order to better understand this complicated hydrology, a
high accuracy digital elevation model and a high precision rainfall forecasting system
such as a radar system are needed to fulfill a real time flood advancing prediction.
Before an adequate hydrological simulation model is developed to predict Pantanal
inundation on an operational scale, the statistical approach presented here may provide
a useful tool to predict RWL and, hence, prevent flood damage in high RWL period as
well as control river transportation traffic in order to prevent riverbank erosion during
low RWL period.
A CKNOWLEDGEMENTS
This study is in part research under taken in association with the Ducks Unlimited
Pantanal-GIS Pilot Project financed by the US Forest Service International Program. The
authors wish to thank the Brazilian Marine Corp at Corumbá and National Water Agency
(ANA, Agencia Nacional de Aqua) for providing the river water level and precipitation
data. The authors also wish to thank the Distributed Active Archive Center (Code 902.2)
at the Goddard Space Flight Center, Greenbelt, MD, 20771, for producing the data in
their present form and distributing them. The original data products were produced
under NOAA/NASA Pathfinder program, by a processing team headed by Ms. Mary James
of the Goddard Global Change Data Center; and the science algorithms were established
by the AVHRR Land Science Working Group, chaired by Dr. John Townshend of the
University of Maryland. Goddard's contributions to these activities were sponsored by
NASA's Mission to Planet Earth program.
RE F E R E N C E S
DNMET,
1992.
Normais
Climatológicas
(1961-1990).
Departamento
Nacional
de
Meteorologia, Ministério da Agricultura e Reforma Agrária, Brasília, Brasil. 83pp.
Eidenshink, J.C. and Faundeen, J.L. 1997.
The 1-km AVHRR global land data set: first
stages in implementation. International Journal of Remote Sensing. 51:39-56.
Fleig, A. J., Heath, D. F., Klenk, K. F., Oslik, N., Lee, K. D., Park, H., Bartia, P. K., and
Bartia, D., 1983, User’s Guide for the Solar Backscattered Ultraviolet (SBUV) and the Total
Ozone Main Spectrometer (TOMS) RUT-S and RUT-T Data Set: October 31, 1978 to
November 1980. NASA Reference Publication Nº 1112, 51p.
Galdino, S. and Clarke, R.T. 1997. Probabilidade de ocorrência de cheia no Rio Paraguai,
em Ladário. MS – Pantanal. 1997. Circulação Técnica N° 23, EMBRAPA-CPAP, Corumbá,
MS. 58p.
85
Gordon, H.R., Brown, J.W. and Evans, R.H. 1988. Exact Rayleigh scattering calculations
for use with the Nimbus-7 coastal zone colour scanner. Applied Optics, 27:2111-2122.
Hamilton, S.K., Sippel, S. J. and Melack, J. M. 1996. Inundation patterns in the Pantanal
wetland of South America determined from passive microwave remote sensing. Arch.
Hydrobiology. 137: 1-23.
Kidwell, K. B. 1995. NOAA Polar Orbiter Data Users Guide. Satellite Data Service Division,
NESDIS/NOAA, Washington D.C., USA. 435p.
Liu, W.T.H., Massambani, O. and Nobre, C. 1994. Satellite Vegetation response to
drought in Brazil. International Journal Climatology, 14:343-354.
Liu, W.T.H., Ayres, F.M., Salles, A.T. and Padovani, C. 2002. Upper Paraguay River water
level prediction using NOAA AVHRR NDVI. Proceeding of the 1º International Symposium
“Recent Advances in Quantitative Remote Sensing”, Valencia, Spain, 2002.
Mittermeier, R.A., Camara, I.G., 1990. Padua, M.T.J., and Blanck, J. Conservation in the
Pantanal of Brazil. Oryx 24: 103-112.
Rao, C.R.N. and J., 1995. Chen Inter-satellite calibration linkages for the visible and
near-infrared channels of the Advanced Very High Resolution Radiometer on the NOAA7, -9, and -11 spacecrafts. International
Journal
of Remote Sensing. 16, 1931-1942,
1995.
Silva, J. dos S. V. da; Abdon, M. 1998. Delimitação do Pantanal Brasileiro e suas subregiões. Pesquisa Agropecuária Brasileira, Brasília, v. 33, Número Especial, p. 1703 –
1711.
Welcomme, R.L. 1995. River fisheries.-Food and Agriculture Organization of the United
Nations, Rome, Italy: FAO Fisheries Technical Paper N° 262.
86
3. FURTHER CONSERVATION EFFORTS IN THE UPRB
3A .
B OLIVIA : RESULTS
OF THE
P ANTANAL P ROGRAM
IN
B OLIVIA (WWF B OLIVIA )
HEIDI RESNIKOWSKI1 AND P AMELA REBOLLEDO2
R ESULTS
−
Copies of the UPRB GIS Database Development Project Phase I final report have been
distributed to the Forestry Superintendence, National Protected Areas Service, Agrarian
Superintendence, Noel Kempff Mercado Natural History Museum, Municipalities, Cattle
Federation and private companies that are interested in investing in the Puerto Busch
project.
−
The flooded area grids and final report have been used as reference in the
Management Plan of the Otuquis National Park.
−
The project results will be used as reference to complete a project proposal to be
presented to the International Tropical Timber Organization (ITTO), called “Fire Fight –
Sur Project,” developed by the World Conservation Union (IUCN) in collaboration with
WWF International.
−
Three papers have been presented:
a) Resnikowski H. (2002). “Dynamics of Change in the Landscape of the Pantanal
Otuquis National Park Caused by Fires, Biomass Changes, Roads and Fluctuations
of the Flood Levels Between 1988, 1997, 1998 and 1999”.
Paper presented at
the X International Symposium SELPER (Society of Latin American Experts in
Remote Sensing), Cochabamba, Bolivia. November 2002.
b) Resnikowski H. (2003). “Upper Paraguay River Basin GIS Database – Pilot Project I”
Invited to give a presentation at the X Latin-American GIS Users Conference.
Santa Cruz, Bolivia. September 10.
c) Resnikowski H. (2003). “Fires in the Bolivian Pantanal”. Presentation provided as a
consultant to the WWF Bolivia’s Pantanal Program at the Workshop Fires in the
Bolivian Pantanal. Puerto Suárez, Bolivia. January 16.
−
Flooded area maps and digitized roads were presented in the Forum called Puerto
Busch.
1
WWF Bolivia, Santa Cruz, Bolivia; [email protected]
2
WWF Bolivia, Santa Cruz, Bolivia; [email protected]
87
−
The results will be distributed to the members of the Pantanal Coordinator
(“Coordinadora Pantanal”) as reference information.
−
Since the project was finished, the compilation of metadata is a common process in
the GIS work developed in WWF Bolivia.
−
A technical proposal to expand the flooded area map was sent to SWS Ramsar
Support Framework Funding. The same methodology was suggested.
88
3 B .B RAZIL : P LANNING AND MANAGEMENT OF THE “NASCENTES DO RIO T AQUARI” S TATE P ARK
SYLVIA T ORRECILHA3, WILLIAM T. LIU4 AND FÁBIO M. AYRES5
I NTRODUCTION
As part of the strategy of the state government of Mato Grosso do Sul to develop a
system for conservation units through the “Secretaria Estadual de Meio Ambiente” (State
Ministry of the Environment) and the “Instituto de Meio Ambiente Pantanal” (Institute of
the Environment for the Pantanal), studies were conducted and a management plan was
implemented to guarantee biodiversity conservation in the state’s most significant
ecosystems, especially through the establishment of new conservation units. In order to
select locations representative of the environmental (geological, edaphic, climatic and
biological) and socioeconomic diversity of the state’s territory, studies in the area of the
river Taquari headwaters were prioritized, in the municipalities of Costa Rica and
Alcinópolis.
As a result, the state park “Nascentes do Rio Taquari” was created, which
constitutes the first state conservation unit established in the section of the Upper
Paraguay River Basin included in Mato Grosso do Sul. This park is strategically located
for the implementation of the corridor of biodiversity Cerrado-Pantanal, in one of the
core zones of the Pantanal Biosphere Reserve (Figure 1).
P URPOSE
The purpose of this study was to characterize and analyze the structure of the study
area’s
landscape
(including
physical,
biological
and
ecological
aspects)
for
the
environmental zoning of the state park “Nascentes do Rio Taquari,” using geographic
information systems (GIS) and remote sensing techniques for the development of a
formal management plan. The conservation parameters considered in this study include
biodiversity, recreation, environmental education, ecotourism, watershed protection,
scientific research, and monitoring of environmental quality.
The study area was
subdivided taking into account physical and natural characteristics, but also considering
cultural, recreational and research factors. The management plan of the park was based
on the guidelines established by IBAMA and official documents such as the law of
number 9,985/2000 and its regulating decree of number 4,340 from August 22, 2002.
Additionally, land surveys, data from the “Conservation Plan of the Upper Paraguay River
Basin” (PCBAP), interpretation of a Lansat-7 image, botanical characterization conducted
by the “Ecological Corridor Cerrado-Pantanal” project and field data were also
considered.
Workshops were conducted in Campo Grande (August 21, 2003), Costa
3
Universidade Católica Dom Bosco, Campo Grande, MS, Brazil; [email protected]
4
Universidade Católica Dom Bosco, Campo Grande, MS, Brazil; [email protected]
5
OIKOS (Cooperativa de Trabalho Sócio-ambiental), Campo Grande, MS, Brazil; [email protected]
89
Rica (September 18, 2003) and Alcinópolis (September 19, 2003) to discuss the
management planning of the park with all the interested stakeholders.
Figure 1. Biosphere reserve of the Pantanal (text in Portuguese).
S TUDY A R E A
The State Park “Nascentes do Rio Taquari,” created by the decree of number 9,662 on
October 19, 1999, encompasses 30,619 hectares (ha) located in the state of Mato
Grosso do Sul between the coordinates 17º 59’-18º 15’ S and 53º10’-53º 26’ W, with
26,850 ha in the municipality of Alcinópolis and 3.769 ha in the municipality of Costa
Rica (Figure 2). The park is 50 kilometers (km) from the urban center of Costa Rica and
60 km from that of Alcinópolis. The park’s buffer zone not only includes Costa Rica and
90
Alcinópolis, but also, to the north, part of the municipality of Alto Taquari (from the
state of Mato Grosso).
Figure 2. State Park “Nascentes do Taquari” (text in Portuguese).
M ETHODOLOGY
Data were digitized, processed and analyzed using the programs ArcView 3.2a (with
extensions Image Analysis and Spatial Analysis) and Spring 3.6.03.
To improve the
visualization and delineation of features in the vectorization process using raster data,
contrasting techniques were employed.
Supervised and unsupervised classification
procedures were applied to characterize and quantify land cover.
The classification results were integrated to other GIS data (obtained from topographic
maps and field observations) to develop the environmental zoning of the study area.
The combination of these datasets allowed an integrated analysis and the assessment of
the applicability of GIS for future actions in the evaluation and monitoring of the park’s
91
natural resources. In addition to the environmental zoning, the generated maps include
hydrography, hypsometry, slope, vegetation and land use.
R ESULTS
The buffer zone of the park encompasses the headwaters of three of the streams
forming the Taquari River, namely the Furnas, Mutum and Engano, located near the
borders with the states of Mato Grosso and Goiás. The park is close to the headwaters
of the Araguaia River and National Park “Emas,” and includes scarps of the western
border of the “Planalto Central Brasileiro” (central Brazilian plateau region).
Also
included in the park are “cuesta” formations. The park presents high topographic relief;
elevations (above sea level) vary from 890 meters (m) in the Chapadão dos Baús, to 390
m, at the headwater of Ribeirão Engano, which is a tributary of the Taquari River in the
pre-Pantanal depression, with Canyon formations and abundant geological monuments.
The
vegetation
in
the
park
area
is
represented
by
physiognomic
formations
characteristic of the Cerrado biome: submontane seasonal semideciduous forest and
“cerradão” (Cerrado forest) are found along cuestas, which also present “cerrado sensu
stricto” (Cerrado savanna) and “campo sujo” of Cerrado (Cerrado grassland with few
scattered shrubs and trees) along scarps in the low areas of the plain. In the vegetation
map (Figure 3), similar physiognomic formations were grouped in the same category,
which resulted in three classes: (1) seasonal forest with cerradão (36.57% of the total
area of the park); (2) cerrado sensu strictu with campo sujo of Cerrado and “campo
rupestre” (grassland) (45,74%); and (3) pasture with Brachiaria predominance with small
patches of agricultural fields (17,70%).
This vegetation map is the product of a
supervised classification of Landsat imagery, which followed a preliminary unsupervised
classification procedure.
The main result of the integration of the several GIS datasets generated is the map of
environmental zoning in which six classes are distinguished (Figure 3). Flexible in use
are: (1) zone of especial use (0.9%), (2) zone of recuperation (35.7%), (3) zone of
extensive use (2.90%), and (4) historical/cultural zone (0.48%); while those more
restrictive in use include: (5) intangible zone (13,12%), and (6) pristine zone (46,90%).
Considering the intensive agricultural occupation surrounding the park, a buffer zone
subdivided in two sections was proposed (Figure 4). It is suggested that the buffer zone
section that is adjacent to the park (2 km wide) be restricted to agroforestry systems,
while the outer section of the buffer zone (1 km wide) may include pastures.
92
Figure 3. Vegetation and environmental zoning of the park (text in Portuguese)
93
Figure 4. Buffer zone subdivision (text in Portuguese)
A CKNOWLEDGEMENTS
This study was conducted in association with the “Instituto de Meio Ambiente Pantanal”
(institute of environment for the Pantanal), the municipalities of Costa Rica and
Alcinópolis. Funding was provided by the project GEF/Alto Paraguai (PNUMA/OEA).
94
3C. B RAZIL : F LOOD M ONITORING
IN THE
P ANTANAL W ETLAND 1
C ARLOS R. PADOVANI2, JORGE SAMBRANA3, MARIANE L.
DA
C RUZ4
AND
MANUEL FERREIRA5
I NTRODUCTION
The flood pulse is the driving force of ecological processes and economic activities in
the Pantanal wetland. Wildlife distribution, including that of caimans, marsh deer,
capybaras and waterfowl species, is strongly dependent on the occurrence and
frequency of flooding in wetland areas. The floodplains in the Pantanal play an
important role in water purification, filtering the pollutants coming from the highlands,
which increase every year. These floodplains constitute habitat for fish communities and
encompass significant food and shelter resources that play an important nursery role for
many other species. Embrapa Pantanal has mapped flooded areas in a variety of
Pantanal locations using different satellite imagery (Padovani et al., 2003; Padovani et
al., 2004), but a long-term ecological project such as the Brazilian “Programa Ecológico
de Longa Duração” (Ecological Long-Term Program) (PELD) requires a continuous and
long-term monitoring program.
The main goals of this flood monitoring program are to: (a) quantify and map the flood
dynamics of the Paraguay River floodplain; (b) establish the relationship between water
level, flooded area and stress through the spatial analysis of flooding, wildlife
distribution, water chemistry and other biotic and physical elements of the system; and
(c) perform an integrated analysis of how the inter-annual variations in flooding relate
to the abundance and distribution of terrestrial and aquatic organisms.
M ETHODS
The reflectance bands, NDVI, Enhanced Vegetation Index (EVI) (with 250 m of spatial
resolution) and surface temperature band (with 1 km of spatial resolution) of the
Moderate Resolution Imaging Spectroradiometer (MODIS) sensor have been processed
for flooded area quantification from February 2001 to the present. A MODIS imagery
database that is updated monthly has been created, and an automatic procedure for
image processing has been developed. Paraguay River level data from “Ladário NAVI”
harbor was used to characterize flood events (Figure 1). The study area encompasses
1 Poster presentation. International Symposia on Long-Term Ecological Projects, July 2004. Manaus,
Amazonas, Brazil
2
Empresa Brasileira de Pesquisa Agropecuária (Embrapa) Pantanal, Corumbá, MS, Brazil;
[email protected]
3
Universidade Federal de Mato Grosso do Sul, Corumbá, MS, Brazil
4
5
Universidade Federal de Goiás, GO, Brazil
95
41.53 km2 that correspond to the sub-regions of Corixo Grande (CORI), Paraguay (PARA)
and Nabileque (NABI) as defined by Hamilton (1996).
Figure 1. River level data from Ladário.
R ESULTS
AND
D ISCUSSION
The results of a classification procedure to quantify the area of lowest and highest flood
events in the studied period are presented in Figure 2.
October 2001
Dry period
Image difference
June 2003
High-flood period
Figure 2. River level data from Ladário Flood classification for the dry and high-flood
periods in the area of influence of the Paraguay River. The difference image shows the
areas where the floods increase (pink) or decrease (gold).
96
The maximum flooded area, which occurred in June 2003, was 11.1 km2; while the
minimum flooded area, which occurred in October 2001, was 8.1 km2. This difference of
3 km2 represents the total range in variation of flooded area for the period of 2001 to
2003.
In some regions, unlike what was expected, a decrease in flooded area occurred during
the dry-to-flooded season. It is well known that because of the extensive length (~680
km), sinuosity and “sponge” effect of the Paraguay River, the flood wave takes 3 to 4
months to reach the city of Ladário, where the river level measurement station used in
this study is located. Further analysis of rain data integrated to river water level data will
be conducted to better understand the flood dynamics of the region.
As expected, the flood dynamics of the Paraguay River region are influenced by more
than one water source at different times of the year. With this integrated continuous
long-term monitoring program, the contribution of each factor influencing flood
dynamics in the Pantanal will be better understood.
A CKNOWLEDGEMENTS
To Dr. Rob Longman from the ALTERRA institute, Netherlands, whose project has
partially supported this activity. To Gerard Groenveld for the help with GIS.
RE F E R E N C E S
Hamilton, S. K, S.J., Sippel and Melack. 1996. Inundation patterns in the Pantanal
wetland of South America determined from passive microwave remote sensing. Archives
of Hydrobiology 137 (1): 1-23.
Padovani, C. R., , Moraes, A. S., Resende, E.K. 2003. Banco de dados geográfico da
Estrada-Parque-Pantanal, MS: enfoque na atividade de pesca esportiva. Corumbá:
Embrapa Pantanal (Documentos / Embrapa Pantanal ISSN 1517 – 1973; 44).
Padovani, C.R., Assine, M., Vieira, L.M. 2004. Inundações no leque aluvial do rio Taquari.
Unpublished technical report. Embrapa Pantanal.
97
3 D. B RAZIL : R E - DRAWING
THE
P ANTANAL WETLAND DELINEATION IN BRAZIL, B OLIVIA AND
P ARAGUAY 6
C ARLOS R. PADOVANI7, MARIANE L.
DA
C RUZ8 AND JORGE SAMBRANA9
P ROJECT S UMMARY
Wetland delineation is an important issue in ecological and hydrological studies, and
conservation policymaking. Several authors have delineated the Pantanal wetland. Silva
and Abdon (1998) proposed limits for the Brazilian Pantanal based on previous work,
Landsat imagery, and vegetation, soils and topographic maps at the 1:250,000 scale.
Hamilton et al. (1996) delineated the entire Pantanal (Bolivia, Brazil and Paraguay) using
passive microwave thermal bands (with a spatial resolution of 25 km).
Currently, new remote sensing products are available and actively employed in wetland
delineation. We propose to review the Pantanal limits for Bolivia, Brazil and Paraguay
using MODIS products such as NDVI, Enhanced Vegetation Index (EVI) and reflectance
bands (with 250 m of spatial resolution), and the surface temperature product (with 1
km of spatial resolution). MODIS products have the advantage of being composite
images free of clouds, which permits maximum flood events to be quantified
periodically. The Shuttle Radar Topographic Mission (SRTM) is also a very useful sensor
for the delineation of floodable areas because of the detailed relief data it provides.
Imagery from the new satellite China Brazil Earth Resources Satellite 2 (CBERS-2), which
has a higher spatial resolution (20 m), has also been assessed for use in the
quantification of flooded areas.
The first results obtained applying MODIS, SRTM and CBERS-2 data for wetland
delineation in the study area show their great potential for improving previously
established Pantanal limits. In future research efforts, flood analysis previously
conducted by Embrapa Pantanal and its partners using Landsat and SAC-C imagery will
also be employed.
The following figures (Figures 1 to 6) illustrate the data and
preliminary procedures in use in this project for the re-delineation of the Pantanal.
6
International Symposia on Long-Term Ecological Projects, July 2004. Manaus, Amazonas, Brazil.
7
[email protected]
8
9
98
-52.47
-13.89
-64.41
-26.20
Figure 1. SRTM digital elevation model of the UPRB (Bolivia, Brazil and Paraguay)
-53.30
-14.00
-61.00
-22.00
Figure 2. SRTM digital elevation model of the UPRB in Brazil
99
-56.85
-15.45
-59.40
-17.10
Figure 3. SRTM image of the northwestern portion of the Pantanal showing topographic
data in brown tones (highest height is 200 m). Indicated are the delineation of Hamilton
et al. (1996) (in blue), and that of Silva et al. (1998) (in red).
-56.85
-15.45
-59.40
-17.10
Figure 4. SRTM image of the northwestern portion of the Pantanal combined with a
Landsat image at 30 % of transparency.
100
-56.85
-15.45
-59.40
-17.10
Figure 5. SRTM image of the northwestern portion of the Pantanal combined with the
reflectance MODIS image at 30% transparency.
-54.60
-15.45
N
-60.30
-22.30
Figure 6. SRTM image of the Pantanal (Bolivia, Brazil and Paraguay) combined with the
reflectance MODIS image at 30% transparency.
101
A CKNOWLEDGEMENTS
To Dr. Rob Longman from the Research Institute for our Green Living Environment
(ALTERRA), Netherlands, whose project has partially supported this activity.
To Gerard
Groenveld for the help with GIS.
RE F E R E N C E S
Hamilton, S. K, Sippel, S.J. and Melack. 1996. Inundation patterns in the Pantanal
wetland of South America determined from passive microwave remote sensing. Archives
of Hydrobiology 137 (1): 1-23.
Silva, J.S.V. and Abdon, M. 1998. Delimitação do Pantanal Brasileiro e suas sub-regiões.
Pesquisa Agropecuária Brasileira 33 (Número Especial): 1703–1711.
102
3E . B RAZIL : F IRE
MONITORING AND ANALYSIS FOR THE
C ARLOS ROBERTO P ADOVANI11, MARIANE L.
DA
B RAZILIAN P ANTANAL 1 0
C RUZ12 AND JORGE SAMBRANA13
I NTRODUCTION
The use of fire for pasture management in rural areas is a common practice in the
Brazilian Pantanal. Many areas, in the dry period, present a significant amount of dry
material, which represents available fuel for the ignition and spread of fires. Generally,
farmers intend to use fire in small areas only, but sometimes these small fires
accidentally spread and, as a result, affect large areas.
Uncontrolled fires can be disastrous for wildlife and vegetation in terrestrial and aquatic
environments.
Continuous fire monitoring and the development of strategies for fire
prevention and control are new objectives for the management plan for PELD site 2, in
the Pantanal.
M ETHODS
Data on occurrence of fire were obtained from the “Instituto Nacional de Pesquisas
Espaciais” (National Institute for Spatial Research) (INPE), Brazil. These data were derived
from AVHRR/NOAA imagery as focal points of fire occurrence. Only data from July to
October of each year were considered in this study because this is the period of greatest
incidence of fire. The imagery was subset using the limits of the Brazilian Pantanal as
established by Silva and Abdon (1998). The present study was conducted to determine
fire density (number of fires in relation to area) considering political units (municipalities
and states) and vegetation types.
R ESULTS
AND
D ISCUSSION
The spatial distribution of fires in the Pantanal is better explained with relative
measurements such as fire density (Figure 1). The highest fire density occurs in the
southwestern section of the Pantanal, which is, surprisingly, one of the most frequently
flooded areas in the region. Fire in the Pantanal is an environmental problem that must
be
considered
in
a
policymaking
context.
Because
the
majority
of
fires
are
anthropogenic in origin, the establishment of preventive and controlling measures
10
International Symposia on Long-Term Ecological Projects, July 2004. Manaus, Amazonas, Brazil.
11
[email protected]
12
13
103
(including the implementation of specialized laws and regulations) implies actions in
policy decision-making at the municipality and state levels (Figures 2 and 3).
Figure 1. Fire density in the Brazilian Pantanal
104
State
Fire number
MS
MT
TOTAL
20152
12905
33057
Area of the state in
the Pantanal (Km²)
88866
49152
138018
Fire/area
%
0.23
0.26
46
54
100
Figure 2. Fire distribution and states
105
Municipality
Aquidauana
Barão
Bodoquena
Cáceres
Corumbá
Coxim
Itiquira
Ladário
Lambari
Leverger
Livramento
Miranda
Poconé
Porto Murtinho
Rio Verde
Sonora
TOTAL
Fire
number
2405
3675
7
3327
12744
662
702
13
106
2215
265
844
2595
1919
1376
210
33065
Municipality area
Fires/Area
%
(km²) in the Pantanal
12559
0.19
4
11004
0.33
7
48
0.15
3
14326
0.23
5
62207
0.20
4
2022
0.33
7
1850
0.38
8
49
0.27
6
279
0.38
8
6915
0.32
7
1019
0.26
6
2166
0.39
8
13760
0.19
4
4418
0.43
9
4734
0.29
6
693
0.30
7
138049
100
Figure 3. Fire distribution and municipalities
106
The media (newspapers and television) usually reports fires employing absolute values,
which cause certain misunderstandings. In the news, the municipality of Corumbá is
frequently mentioned as the location with the highest incidence of fires in the state of
Mato Grosso do Sul. However, if the number of fires were reported in relation to area,
Corumbá would generally hold the fifth position in fire occurrence, not the first.
Vegetation structure, phenology and productivity, and their relation to climate, relief,
flood regime and human activities, are the main factors that determine fire occurrence
and spatial distribution in the Pantanal. Unfortunately, because the AVHRR data present
an error of approximately 5 km in georeferencing, only major vegetation types at coarse
scales can be used for spatial analysis. In the Pantanal, the highest number of fires
occurred in the “ honolo estépica” (steppe savanna from the Chaco region) and
“formações pioneiras” (secondary formations) (Figure 4). These vegetation types occur
mainly in the southwestern section of the Pantanal as shown in the fire density map
developed (Figure 4). The open structure, dense herbaceous stratum, high primary
productivity and strong
honological seasonality that characterize the vegetation in this
area can be the main cause for fire occurrence and spread.
C ONCLUSION
The spatial distribution of fire density in the Pantanal is heterogeneous when presented
in relation to major vegetation types. If political units are considered, such as
municipalities and states, the spatial distribution of fire density appears relatively
homogeneous.
R EMARKS
AND
F U R T H E R A NALYSIS
The remote sensing laboratory of Embrapa Pantanal has been building for many years a
GIS database encompassing information on the main factors that determine fire
occurrence, which include vegetation types, phenology and productivity, and climate,
relief, flood regime and human activities. This database constitutes an important
tool/resource for the prevention and control of extensive fires. Fire departments usually
interact with Embrapa Pantanal for assistance in fire control analysis. This database is
constantly growing, gradually improving Embrapa Pantanal’s capabilities for GIS support
in issues of fire control and prevention. Currently, the remote sensing laboratory of
Embrapa Pantanal is working on the quantification of flooded areas and vegetation
honological variability using MODIS imagery. In comparison to AVHRR data, fire
detection using MODIS imagery is more accurate. The spatial analysis being conducted
with these data sources and techniques will be essential in the preparation of precise
risk maps for fire prevention.
107
Main vegetation types
Number of
fires
108

Upper Paraguay River Basin GIS Database

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