Submission: ADEH 2013 Call for Papers, X Conference of ADEH

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Submission: ADEH 2013 Call for Papers, X Conference of ADEH,
Albacete, Spain. June 18-21 2013
Completed Paper
Title: A Framework for a Spatial Analysis Model for Homeland Security
Título: Quadro de referência de Análise Espacial Aplicado à Segurança Interna
Authors: Marco Painho (1, [email protected]); Teresa Ferreira Rodrigues (2,
[email protected]); Tiago H. Moreira de Oliveira (1, [email protected]);
Alexandre Alves Coimbra (3, [email protected]); Luís Fiães Fernandes (3,
[email protected]); Pedro Cabral (1, [email protected]); Roberto Henriques
(1, [email protected]); Miguel Neto (1, [email protected]); Flávio Alves (3,
[email protected]).
Institutions: 1) Instituto Superior de Estatística e Gestão de Informação, Universidade
Nova de Lisboa (ISEGI-NOVA); 2) Centro de Estudos da População, Economia e
Sociedade (CEPESE/UP); 3) Sistema de Segurança Interna (SSI).
Corresponding Author:
Marco Octávio Trindade Painho
Email: [email protected]
Address: Instituto Superior de Estatística e Gestão de Informação Universidade
Nova de Lisboa (ISEGI-NOVA); Campus de Campolide; 1070-312 Lisboa;
Portugal
Phone: +351 213 828 616 | Fax: +351 213 828 611
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Title: A Framework for a Spatial Analysis Model for Homeland Security
Título: Quadro de referência de Análise Espacial Aplicado à Segurança Interna
Authors: Marco Painho (1); Teresa Ferreira Rodrigues (2); Tiago H. Moreira de
Oliveira (1); Alexandre Alves Coimbra (3); Luís Fiães Fernandes; Pedro Cabral (1);
Roberto Henriques (1); Miguel Neto (1); Flávio Alves (3).
ADEH 2013, X Conference of ADEH,
Albacete, Spain. June 18-21 2013
Abstract:
This Paper aims to suggest an approach to build a scientific tool to support decision
making, based on a geographic information system, and on the development of future
scenarios regarding issues related with security forces, taking the Portuguese case as an
example, until 2030.
Security is a public good and the use of this instrument will allow the political power to
rationalize public spending in the security sector, making a better and effective security
resources management and allocation, considering the diversity and specificity of each
area, crime levels and public perceptions about security.
In this context, we pretend to propose and discuss the creation of a model that aims to
create a optimized distribution of the public security resources throughout the territory,
considering the population distribution and its dynamics over time, optimizing the racio
police / citizen. It will allow the evaluation and assessment of the effectiveness of the
dual-system model of security forces (civil / military), for understanding and assessment
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purposes, aiming to list entropies and issues related with systemic functions of the
security sector.
This Model, based on a Web Geographic Information System application, provides
relevant means to support planning and decision-making by providing the institutions
responsible for public policies within the homeland security sector, with the ability of
creating scenarios, by using demographic forecasting together with spatially dynamic
tools. Such model would allow the achievement of a optimized distribution of the public
security resources throughout the territory, considering the population distribution and
its characteristics.
In the actual context of unstable balance between investment in internal security forces
and urgency of reducing criminality and its impacts, we pretend to diagnose the past and
the present to forecast the medium and long term future, taking into account a)
demographic dynamics; b) the typology of criminal cases; c) the way in which police
Organization responds to threats; d) urban land use dynamics.
Keywords: Homeland Security; Forecasting Analysis; Dynamic and Spatial Clustering;
Public Policies; Geographic Information Systems.
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Resumo:
Este artigo tem como propósito sugerir uma metodologia de construção de um
instrumento científico de apoio à decisão baseado no desenvolvimento de um modelo
SIG e na elaboração de cenários prospetivos aplicados às forças de segurança e à
população portuguesa no horizonte de 2030.
A segurança é um bem público e a utilização deste instrumento permitirá ao poder
político racionalizar os custos face a segurança dos cidadãos e fazer uma gestão mais
eficaz dos meios humanos de que dispõe, nomeadamente considerando a diversidade
local existente em termos de sentimento de segurança e de vitimização por tipologia
criminal.
No atual contexto de equilíbrio instável entre o investimento em forças de segurança e a
redução dos fatores crime e sentimento de insegurança, pretende-se simultaneamente
diagnosticar o passado e o presente para prospectivar o futuro a médio e longo prazo
tendo em consideração a) as características e dinâmicas demográficas; b)a tipologia das
ocorrências criminais; c) a organização do dispositivo policial de resposta às ameaças;
d) e as dinâmicas do uso do solo.
Palavras-chave: Segurança Interna; Análise Prospetiva; Dinâmica e Agregação
Espacial; Políticas Públicas; Sistemas de Informação Geográfica.
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Title: A Framework for a Spatial Analysis Model for Homeland Security
Acknowledgements:
We would like to thank the contributions of every author to this Paper, as well as the
represented institutions.
1. Introduction:
This Paper aims to suggest an approach to build a scientific tool to support decision
making, based on a geographic information system, and on the development of future
scenarios regarding issues related with security forces and the Portuguese population
until 2030.
Security is a public good and the use of this instrument will allow the political power to
rationalize public spending in the security sector, making a better and effective security
resources management and allocation, considering the diversity and specificity of each
area, crime levels and public perceptions about security. This model will allow to
locally create a symmetric and optimized distribution of the public security resources
throughout the territory, considering the population distribution, optimizing the racio
police / citizen. It will also allow the evaluation and assessment of the effectiveness of
the dual-system model of security forces (civil / military), for understanding and
assessment purposes, aiming to list entropies and issues related with systemic functions
of the security sector. However the safety of citizens cannot be removed from the
concerns of the visibility of state authorities throughout the national territory, and there
will be a concern in order to clarify urban and rural areas, to confirm the need for such a
dichotomy or possible interest in creating new classifications.
This WebGIS-based application and model will offer special and potentially important
means to support planning and decision-making support by providing the institutions
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responsible for public policies within the internal security sector, with the ability of
creating scenarios, by using demographic forecasting together with spatially dynamic
tools and models. Such model will allow the achievement of a symmetric and optimized
distribution of the public security resources throughout the territory, considering the
population distribution.
The Model will comply with a set of rules and procedures in order to represent and
predict a specific outcome. This model, integrated and supported by the WebGIS
application will allow users to easily simulate, emulate and handle impacts generated by
possible changes, where a change of a parameter, variable or factor will provide distinct
dynamic population distribution scenarios, visible on a map, aiming to assist planning
issues and location-allocation problems related to the internal security sector, such as: 1)
suitability of the police offer distribution according to population characteristics; 2)
study of risk groups spatial and temporal dynamics and impact assessment in police
distribution; 3) deployment of police forces; 4) estimation of security agents for a given
area; 5) number and type of professionals. All of these examples have spatial expression
and they will differ according to the developed scenarios. This application will solve
some location-allocation problems, which stands as one of the great advantages in using
predictive models with spatial interaction.
In the actual context of unstable balance between investment in internal security forces
and urgency of reducing criminality and its impacts, our approach seeks to diagnose the
past and the present to forecast the medium and long term future, taking into account a)
demographic dynamics; and b) the typology of criminal cases and c) the way in which
police Organization responds to threats; d) urban land use dynamics.
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Many of these questions have already been answered elsewhere, but not in Portugal,
what justifies this application that is based on a design research new in national terms.
Overall, we aim to provide an extensive and comprehensive assessment and spatial
analysis of the security sector versus population needs that has never been performed to
date for Portugal.
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2. Methodology:
Our approach could be structured in 5 major parts: 1) Study, Analysis, and Diagnosis of
the current national situation, regarding population and public security; 2) Demographic
Forecast and Scenario development: population; risk groups; 3) Development and
Implementation of a Geographic Information System and Design of a dynamic
geoprocessing Model – GIS Model; 4) Implementation of Advanced Spatial Analysis
Methods: Implementing Spatially Dynamic Clusters and Modeling Urban Land Cover
Change, prediction and modeling; 5) Modeling the spatial distribution of Internal
Security Forces (number of officers and facilities location) according to the developed
scenarios.
Figure 1 – Plan & Methodology Structure
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Two main problems we considered are: 1) distribution optimization of human resources
and infrastructures of the security forces; 2) awareness of the dynamic character of the
territorial reorganization of the police forces system, which must follow the change of
volume and movement of the urban fabric. As such, we rely on the location of the
security forces in proximity of the population to be served by the public security service
and to be guaranteed the presence of authority, sending to the background the placement
of such forces near political and administrative power. We will use an innovative
multifactor simulation platform.
As stated before, another essential component is related with the development of a
dynamic database and model, and supported by a Geographic Information System
(GIS), on the Web.
The WebGIS application and model will offer special and potentially important means
to support planning and decision-making, providing the responsible institutions for
public policies within national security sector with the ability of creating scenarios by
crossing demographic forecasting with spatially dynamic tools and models. Such model
will allow achieving a balanced and optimized distribution throughout the territory of
public security forces and facilities according to population evolution. Several studies
show that the ratio police / population vary in a non-linear way according to population
size. In Portugal there are no studies on this issue. To overcome the current problem, we
propose to build an algorithm that optimizes that ratio in order to (i) establish the ratio
police/citizen, (ii) build the simulation platform and (iii) estimate the future needs of
public safety.
The problem is important and interesting because Portugal has dual system of security
forces and in the current economic and financial context it needs to make the best use of
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available public resources. Security forces must know the exact boundaries of their
jurisdiction and have the resources to tackle crime. In addition to what has just been
said public security is an inseparable prerequisite from the exercise of the right to
freedom. The academics and the security professionals could be are interested in sharing
experiences and efforts, in order to achieve a safer Portugal and therefore more
economically competitive systems.
In order to aim this goal, review of the literature of crime theories and public security
management models, should be necessary, as well as a comparative study of the
solutions found by police in several countries with a similar matrix to Portugal.
Demographic characteristics of a population always interact in a complex way with
internal security system. We aim to cross a set of methodologies in order to promote a
better understanding of the impact of ageing in next decades, taking into account that
age structure will influence the nature of most public policies. Population characteristics
change in demographic, social, economic and biological terms. It is therefore relevant to
identify these characteristics at national and regional level so as to be able to offer
possible scenarios to decision makers and regional planners in what regards future
“users” of security services characteristics. Portuguese population major trends are
known. What is new in this case is that we will do demographic projections by sex and
age disaggregated by parish (2011-2030), in order to predict microanalysis distribution
trends, giving special attention to specific vulnerable groups, such as youngsters and
seniors, and cross the output scenarios with wealth local standards and residence
vulnerability, according to security classification (Urban Sensitive Areas-ZUS). We will
use demographic cohort and survival analysis in order to: (a) identify and characterize
Portuguese population dynamics main trends until 2030 (b) consider ageing
phenomenon as inevitable and forecast its impact on population’s distribution; c)
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understand and relate these demographic dynamics with socioeconomic changes and
wealth micro regional pattern and migratory trends; (d) forecast future changes in
demographic structures by age, sex and educational level and the way they will
influence security risks and perceptions.
Another relevant component to this study is related with the implementation of a Land
User and Cover Change (LUCC) model to study urban growth. This model will be
validated and will enable to create scenarios of future urban growth. LUCC models are
one potentially important way of understanding the urban growth phenomena. These
models can be very useful for researchers who want to understand urban growth, for
politicians and urban planners as an educational tool to visualize different scenarios of
urban change. Currently there are dozens of LUCC models and the criteria to
distinguish between them is very diverse: the aggregation level, the use of discrete or
continuous mathematics, the type of data, the methods employed in the state of cells
definition, the types of outputs, etc. Developing efforts to compare modelling results is
an important topic in the LUCC research agenda. The rapid expansion of urban areas is
related to the economic, political and cultural reality of the territory. Urban sprawl
generates a chain of problematic issues, which can be prevented with planning and land
management strategies. We pretend to cross demographic forecast results along with
land use maps forecast. Using this information as input, the goal is to create spatially
contiguous or near-contiguous regions using several criteria such as the resident
population, socio-economic attributes or total area. This can be also seen as a specific
type of clustering where instead of using only a similarity criterion some other criteria
are used in the process. This process is usually known as Zone design (ZD) and it can
be defined as the task of grouping a set of basic areal units into a smaller number of
zones which are in some sense optimal. Some examples of the criteria used in the
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grouping process might include combinations of the number of zones required,
constraints on the population size, the compactness of zone shape, etc. This task is
usually associated with the use of computation and automatic procedures. This problem
can also be seen as an optimization problem, where an initial configuration of zones is
presented and the process tries to improve it by swapping basic units between zones
while optimizing the objective function. We propose two different approaches for
solving this optimization problem: the first uses Self-Organizing Maps, a particular
artificial neural network while the second approach uses genetic algorithms to achieve
good solution. The use of the DELPHI methodology may contribute to confirm the new
needs that are identified, since security experts are heard [19]
Though the creation of an algorithm that establishes the relationship between public
security resources and population, in order to optimize the distribution of security. We
will generate a model that assures: (i) adequacy of the distribution of police resources
according to the characteristics of the population; (ii) spatial dynamic and demographic
subgroups prospective scenarios and impact assessment of security forces territorial
distribution.
In order to accomplish these objectives we intend to study the following subjects:
1. Study, analysis and diagnosis of the current national situation, regarding
population and public security:
a. Population dynamics;
b. Security Forces (resources and location);
c. Characterization of the distribution and typology of the security forces
according to population characteristics.
2. Demographic Forecast and Scenario development: Population Risk Groups:
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a. Population projections (2011-2030) by sex, age and micro simulation of
risk groups (according to previously identified criteria of age, sex,
national origin, place of residence) scenarios;
b. Distribution Model of the Security Forces strength and equipment
location.
3. Development and Implementation of a Geographic Information System and
design of a dynamic geoprocessing Model:
a. Development and Implementation of a WebGIS application;
b. Making
available
a
WebGIS
application
for
mobile
devices
(smartphones and tablets).
4. Implementation of Advanced Spatial Analysis Methods (spatially dynamic
clusters and modeling land cover change predictive model).
5. Modeling the distribution of Security Forces (number of officers and facilities
location) according to the developed scenarios.
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3. Main Results:
We aim to provide a comprehensive assessment and spatial analysis linking security
policies and population needs which has never been performed in Portugal.
Emerging security threats and risks forces the State to establish an appropriate
institutional framework for internal security action and resources allocation [14, 3, 6, 1,
and 2]. As new duties are attributed to security actors, population’s safety became a
central issue and demographics a strategic vector [15, 24, and 29]. Despite the problems
already identified in Portuguese homeland security system [33, 32 and 25] the analysis
and evaluation of decision-making policies about public security resources distribution
and needs has never been made in a systematic way. The Police/inhabitants ratio
influences citizens’ safety but it varies in a nonlinear way with population’s volume [31,
16, and 17].
However, public security capabilities are not only human resources. The search for the
best optimization of public resources distribution gains importance considering
increasingly scarce budgets and the need to maintain standards. Portuguese recent
demographic and social changes redraw population distribution [18, 27 and 11], but
most of the importance of demographic factor for security policies has to be seen from
its endogenous characteristics (sex, age, distribution) which influences collective
perceptions in a context of the human security concept [34, 30 and 12].
National strategy in terms of territorial distribution of the 2 security forces (GNR, PSP)
assumes demographic criteria defined in the 90’s [21, 13 and 22].Taking into account:
recent demographic dynamics, mostly in terms of volume, mobility and structure and
their impact on vulnerable groups, it is urgent to guarantee for the coming decades:
1. The adequacy of the current security forces distribution model and,
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2. Study the possible scenarios linked to demographic trends and the emergence of
more plural risk groups [22].
Our proposed model aims to assist planning issues and optimize resources:
1. Adequacy of police offer distribution to local residents’ characteristics;
2. Study of spatial and temporal dynamics of groups at risk and impact assessment
in police offer;
3. Deploying police forces;
4. Number and type of effectives needed for each area.
A main component of the model is related with the development of a dynamic database
and model supported by a Geographic Information System (GIS). The fusion between
Internet and GIS evolved rapidly in the Web 2.0 era, resulting in WebGIS applications
and changed the way geospatial information is acquired, transmitted, shared and
visualized [20]. This offers special and potentially important means to support planning
and decision-making process, providing the responsible institutions for public security
policies with the ability of creating scenarios by using forecasting and spatially dynamic
tools and models. This application will solve some location-allocation problems, issues
that typically involve where to locate and how to allocate demand for a service [20],
taking into account several factors (as the number of facilities available, cost, maximum
impedance from a facility). This stands as one of the great advantages of using
predictive models with spatial interaction.
The application aims to create several location-allocation scenarios and population
forecasting. Another relevant component is the possibility of projecting high
dimensional data into lower dimensional spaces. It will be possible to cluster population
forecasting data from parishes into regions and we wish to follow how forecasted
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population is distributed within each spatial unit and to understand the best method to
spatially aggregate these units, using spatial clustering methods, in order to create police
action regions for parishes.
As for the implementation of land use and land use cover change (LUCC) models, in
order to predict future urban populated land use [9, 10, 23 and 36], we suggest an
integrated approach of remote sensing (to obtain information about urban phenomenon),
GIS (the integrating element for all the data and the vehicle for output analysis) and
modeling. Urban land use patches generated by remote sensing classification procedures
need to be aggregated into meaningful regions for national security. Spatial clustering is
one of the most important tasks in data analysis.
In geographic knowledge discovery the aim is to explore and let spatial patterns surface.
The size and dimensionality of the existing and future databases stress the need for
efficient and robust clustering algorithms but geographic knowledge discovery can
benefit from better tools to integrate spatial and spatial variables.
As stated before, we pretend to use a Land Transformation Model (LTM). This is an
LUCC model based on GIS, Artificial Neural Networks (ANN) routines, remote sensing
and geospatial analysis tools. LTM provides the dynamic modelling of social, political
and environmental factors, such as the distance to public transportation and road
networks, proximity to natural resources such as rivers and lakes, agricultural and forest
densities, identification of exclusionary zones and population growth.
LTM is an LUCC model based on ANN routines that “learn” about complex spatial
relationships of factors that correlate with urban development. The ANN are employed
in studies about urban growth because they learn about the relationships that exist
between urban growth factors and the site attributes. LTM studies demonstrated that
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dynamic modelling and the scenario prediction are essential to planning and territorial
management. Due to LTM land use modelling and forecasting capabilities, we decided
to use this model in this study.
It would be interesting to model urban growth over the study area using the LTM. The
urban areas could be obtained from CORINE Land cover (CLC) map of years 2000 and
2006. The LUCC model will use distance to roads, slope and distance to city centers as
drivers of urban growth of urban growth.
A Demographic Forecast and some Scenario development will be presented while in the
last, forecast maps of land use for the next 10, 20 and 30 years will be produced. In
another moment we aim to combine these two datasets allowing a more detailed
analysis of the population spatial-temporal. Since the demographic forecast will be
aggregated by administrative regions (parish) it assumes that any outputted statistics
have a homogenous distribution. To get a higher detailed this is combined with urban
versus non- urban maps allowing heterogeneous administrative regions regarding the
forecasted variables. The goal here is to create spatially contiguous or near-contiguous
regions using several criteria such as the resident population, socio-economic attributes
or total area. To achieve this goal, we will apply two different approaches. In the first
approach an artificial neural network called SOM will be used to cluster the input data
into spatially consistent regions of similar socio-economic attributes. Several
restrictions can be added to this optimization analysis, such as the total area or the
number of inhabitants per region.
The second approach will take advantage of evolutionary computation methods, more
specifically Genetic Algorithms (GA) to present several possible regional grouping
solutions. GA have been successfully used in optimization tasks and are considered one
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of the most powerful optimization strategies available. Nevertheless, GA remains
unexplored in this field and further research is necessary to develop an appropriate
model.
The resulting output will be a clustering model capable of creating regions where
similar security approaches should be undertaken easing the definition and
implementation of policy measures.
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4. Conclusions:
Why should we use predictive and dynamic models? First of all, a model has the
capability to support a decision or design process in which a user wishes to find a
solution to a spatial problem, perhaps a solution that optimizes some objective, by
giving the possibility to experiment on a world replica. Lastly, a model allows users to
examine dynamic outcomes by viewing the modeled system as it evolves and responds
to inputs [20]. Scenarios evaluated with dynamic models are thus a very effective way
of motivating and supporting debates over policies and decisions.
Our proposed Model will have to comply with a set of rules and procedures in order to
represent and predict a specific outcome. This model, integrated and supported by the
WebGIS application will allow users to easily simulate, emulate and handle impacts
generated by possible changes, where a simple change of a parameter, variable or factor
will provide distinct dynamic scenarios, visible on a map, aiming to assist planning
issues and location-allocation problems related to the public security sector, such as:
1. Suitability of
the
police
offer
distribution
according
to
population
characteristics;
2. Study of risk groups spatial and temporal dynamics and impact assessment in
police distribution;
3. Deploying police forces;
4. Estimation of public security needs for a given area;
5. Number and type of professionals.
All of these examples have spatial expression and they will differ according to the
developed scenarios. This application will try to solve some location-allocation
problems, issues that involve two types of decisions: where to locate and how to
20
allocate demand for a service. , taking into account several factors, the number of
facilities available, their cost, and maximum impedance from a facility, for instance.
This stands as one of the great advantages in using predictive models with spatial
interaction, since it aims to contribute to the creation of a symmetric and optimized
distribution of the public security resources throughout the territory, considering the
population distribution, optimizing the racio police / citizen.
The GIS application, which will be available in a restricted and secure web application,
will be the key interface between users and the model, in which, besides using basic
spatial visualization, navigation and spatial tools, will also gave them the freedom to
manipulate and change parameters/factors, allowing them to visualize its changes,
effects and impacts produced on a dynamic map, aiming to create several scenarios and
population forecasting for 2030. It would allow users to dynamically simulate, emulate
and handle impacts generated by scenarios and population distribution, aiming to assist
planning issues and before-mentioned location-allocation problems, regarding the
internal security sector.
With this information, there could be to conducted studies that may gave some hints and
clues on how to make a better and effective security resources management and
allocation, considering the diversity and specificity of each area, crime levels and public
perceptions about security.
The integrated and multidisciplinary approach we propose, using quantitative and
qualitative methods is innovative and constitutes a valuable tool for decision-making,
institutional and educational purposes. To accomplish our goal, we combine several
fields and scientific areas, namely, demographic analysis, security, political science,
21
statistics and spatial analysis, using specific methodological approaches and techniques
(LUCC mapping and analysis, spatial clustering, modeling).
22
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