Multi-temporal Analysis of Land Use in Northwest Paraná

Multi-temporal Analysis of Land Use in
Northwest Paraná - Brazil: Application of
Remote Sensing Techniques and Geoprocessing
Sandra Lessa da Silva Ferreira 1
Simone Kozciak 2
Chisato Oka-Fiori 3
¹ Doctoral Student in Geography- Universidade Federal do Paraná – UFPR [email protected]
² Doctor in Geology and Autonomous Researcher–Curitiba-PR [email protected]
³ Doctor Professor in Geography - Universidade Federal do Paraná – UFPR [email protected]
1- Introduction
• Technological advances in the last decade;
• methodologies and techniques to remote sensing and
GIS;
• The present study aims:
- to analyze the dynamics of land use and vegetation
cover in a limited area,
- multitemporal studies determined from historical
and socio-economic aspects: 1963, 1985 and 2010.
• 1963 was defined as the year representing the beginning
of the territorial occupation;
• In 1985 there was a significant transition from
agricultural land usage to livestock;
• The year 2010 provided data for the analysis of current
conditions of water resources and land usage.
2 – LOCATION
AND GENERAL
DESCRIPTION
latitude:
23°45’00”S
24°00'00"S
Longitudes:
53°40'00"W
54°10'00“ W
• the soil formation of the study area is associated
with the Caiuá sandstone covering;
According to EMBRAPA (1984) and Nimer (1979)
Photo by Author
• The local climate: subtropical humid mesothermal with
hot and humid summers, winters with infrequent frosts
and dry seasons which are not clearly defined;
• The annual rainfall reaches values ​close to 1500 mm;
according to the “Paranacidade data”
• The enclosed basins, according to analysis by Maack
(2002), were originally tropical rain forest;
• Currently there are only strips of native forest protected
by law, and in some areas of riparian vegetation.
Photo by Author
3 – WORKING METHODOLOGY
• Interposition of maps;
• soil usage from aerial photographs dated 1963, and
•
supervised classification of satellite images from 1985
and 2010.
monochrome aerial
photographs;
- scale of 1:70.000;
taken by Cruzeiro do Sul
SA; Aerophotogrammetric
Services, (May /1963),
provided by ITCG of Paraná
(Institute of Lands, Mapping
and Geoscience).
- Aerial photographs
obtained on paper
were initially
converted to a digital
form through raster
scanning;
- This digital record
has been corrected
geometrically and;
- georeferenced
using ERDAS
IMAGINE software.
-Through
vectorialisation “on
screen” with the
ESRI ArcGIS
software, database
polygons were
created for different
soil uses observed in
the study area.
- The most important
photographic
parameters
observed were:
-tone, texture,
pattern, shape, size,
shadow, colour,
topography and
related factors (Santos
et al., 1980)
Automatic classification
techniques, for the years
1985 and 2010.
- Bands 1,2,3,4, 5 and 7 of the
images contained in the
point/orbit 244-76 and 244-77,
-For image processing ERDAS
Imagine 9.2 software was
used.
taken by INPE website (National Institute
for Space Research), for the dates of
June 19, 1985 and June 24, 2010.
- Four key steps were followed
to obtain maps of the soil
coverage of 1985 and 2010:
-the production of the
preliminary photo-interpreted
maps;
- field control;
- supervised classification ;
- and the final draft, through
photo-interpretation of the
databases.
4 – CLASSIFICATION SYSTEM OF LAND USE
• The classification system as per “Use and Land Cover”
from IBGE (Brazilian Institute of Geography and
Statistics),
• - Anthropogenic Non-agricultural areas: is associated
with all types of land use for non-agricultural sectors,
• Anthropogenic
agricultural areas: can
be heterogeneous or, in
agricultural areas
represent large planting
areas.
•
In the present study,
areas for crops and
pastures were identified.
Detail of the classification of soil
usage, Landsat Image RGB 457Photo by Author (class: crops and
pasture)
• Areas of natural
vegetation were
organized into
two categories:
• the arboreal
forest and
• the shrub and
herbaceous
vegetation.
Detail of the classification of soil usage,
Landsat Image RGB 457- Photo by Author
(class: forest and shrub)
5 – ANALYSIS OF THE RESULTS
Multi-temporal Analysis of Land Use in Northwest Paraná – Brazil
Class
1963
1985
2010
Km2
%
Km2
%
Km2
%
Urban Areas
0,48
0,12
2,53
0,61
4,07
0,99
Crops
79,56
19,29
324,05
78,63
227,93
55,30
Pastures
11,44
2,77
64,28
15,60
109,93
26,67
Forests
310,1
75,19
14,55
3,53
38,78
9,41
Shrub
7,44
1,80
3,67
0,89
29,26
7,10
-The chart of 1963 presented an extensive area covered by
native vegetation;
- However, in deforested areas there was a total absence of
protective vegetation on the banks of watercourses.
Multi-temporal Analysis of Land Use in Northwest Paraná – Brazil
Class
1963
1985
2010
Km2
%
Km2
%
Km2
%
Urban Areas
0,48
0,12
2,53
0,61
4,07
0,99
Crops
79,56
19,29
324,05
78,63
227,93
55,30
Pastures
11,44
2,77
64,28
15,60
109,93
26,67
Forests
310,1
75,19
14,55
3,53
38,78
9,41
Shrub
7,44
1,80
3,67
0,89
29,26
7,10
- Based on automatic image classification 1985, It is noted
that agricultural usage of the land was the main factor
responsible for the sharp decline of native vegetation.
Multi-temporal Analysis of Land Use in Northwest Paraná – Brazil
Class
1963
1985
2010
Km2
%
Km2
%
Km2
%
Urban Areas
0,48
0,12
2,53
0,61
4,07
0,99
Crops
79,56
19,29
324,05
78,63
227,93
55,30
Pastures
11,44
2,77
64,28
15,60
109,93
26,67
Forests
310,1
75,19
14,55
3,53
38,78
9,41
Shrub
7,44
1,80
3,67
0,89
29,26
7,10
-However, on the automatic classification of image 2010 it
can be seen that forest and pasture areas have increased
considerably.
Multi-temporal Analysis of Land Use in Northwest Paraná – Brazil
Class
1963
1985
2010
Km2
%
Km2
%
Km2
%
Urban Areas
0,48
0,12
2,53
0,61
4,07
0,99
Crops
79,56
19,29
324,05
78,63
227,93
55,30
Pastures
11,44
2,77
64,28
15,60
109,93
26,67
Forests
310,1
75,19
14,55
3,53
38,78
9,41
Shrub
7,44
1,80
3,67
0,89
29,26
7,10
- The use of Geographic Information Systems, combined with
geomorphological studies, is fundamental resources for case
studies;
- However, the search for solutions or attenuating measures
directly and indirectly involves different segments of society.
Thank
you
all
Sandra Lessa
6 – REFERENCES (used in the article)
EMPRESA BRASILEIRA DE PESQUISA AGROPECUÁRIA – EMBRAPA. FUNDAÇÃO INSTITUTO AGRONÔMICO DO
PARANÁ – IAPAR. Levantamento de Reconhecimento dos solos do estado do Paraná. Londrina, 1984.
FREITAS FILHO, M. R.; MEDEIROS, J. S. Analise multitemporal da cobertura vegetal em parte da chapada do Araripe – CE,
utilizando técnicas de sensoriamento Remoto e Geoprocessamento. In_ SIMPOSIO BRASILEIRO DE SENSORIAMENTO
REMOTO, 7, 1993 – São Jose dos Campos: INPE, 1993. p. 73-80.
Instituto Brasileiro de Geografia e Estatística – IBGE. Manual Técnico de Uso da Terra - 2ª edição. Rio de Janeiro, 2006.
MAACK, R. Geografia Física do Estado do Paraná. Curitiba: Imprensa Oficial, 2002.
MENESES, P. R.; ASSAD, E. D.; SANO, E. E. Introdução de imagens digitais de satélites de Sensoriamento Remoto. Brasília,
editora Universidade de Brasília, 1991.
NIMER, E. Climatologia do Brasil. Rio de Janeiro: IBGE, 1979.
NOVO, E. M. L. M. Sensoriamento Remoto – Princípios e Aplicações – Editora Edgard Blücher Ltda. São Paulo – SP. 2a
Edição, 308p. – 1992.
NOVO, E. M. L. M. Projeto UTVA- Análise comparativa entre Fotografias Aéreas convencionais e Imagens do LANSAT
para fins de levantamento do uso de Terra. São José dos Campos, INPE, 1978 (INPE- 1337-NTI/113).
PEREIRA, M. N.; KURKDJIAN, M. N. O. DE; FORESTI, C. Cobertura e uso da terra através de Sensoriamento Remoto. São Jose
dos Campos: Instituto nacional de Pesquisas Espaciais, 1989.
ROSS, J. L. S. Geomorfologia ambiental. in: CUNHA, S.B.da e GUERRA, A. J. T. Geomorfologia do Brasil. São Paulo: Bertrand
Brasil, 1998.
SANTOS, A.P.; NIERO, M.; LOMBARDO, M.A. Interpretação de dados de sensoriamento remoto no uso da terra. In: Introdução
às técnicas de sensoriamentp remoto e aplicação: curso de treinamento. São José dos Campos: Instituto Nacional de
Pesquisas Espaciais, 1980.
Sites Consultados
Paranacidade - http://www.paranacidade.org.br/municipios/municipios.php?id_municipio=6
Instituto Nacional de Pesquisas Espaciais – INPE - http://www.dgi.inpe.br