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ESTIMATION OF POPULATION IN INFORMAL SETTLEMENT COMMUNITIES
USING HIGH RESOLUTION SATELLITE IMAGE
Florence A. Galeon
University of the Philippines, Diliman, Quezon City 1102 Philippines -
florence.galeon@up.edu.ph
KEY WORDS: High Resolution; Quickbird; Informal Settlement; Estimation; Mapping; Urban
ABSTRACT:
This paper envisioned the creation of a highly accurate base map from high resolution QuickBird satellite imagery for the University
of the Philippines. A compilation of land titles was used to define the extent of university property. The lots are plotted using CAD
software then overlayed on the base map image. There were two identified qualified categories of informal settlements for this study
such as the “slum” and the “semi-formal” type. Fieldworks ensued to validate and update the mapping result with the aid of GPS.
Stratified random sampling was employed to verify samples and a high 95% identification accuracy was achieved. Base from the
QuickBird satellite image, around 16% of the total 493 hectares UP Campus or roughly 79 hectares may be labeled as informal
settlements. This 2004 UP Campus informal settlements map will serve as the baseline data for monitoring further encroachment.
Individual houses were digitized and a fieldwork was conducted to gather sample data for the regression analysis. A total of 160
samples were collected and processed using the Grid and Theme Regression in the AVENUE programming language. The result
show that estimation of the number of residents in informal settlements is possible for slum areas but not in semi-formal areas.
Likewise, population of informal settlement communities can be estimated from a high resolution satellite image using first order
equation.
1. INTRODUCTION
Urban areas in the world are the most dynamic region on earth.
They serve as the social and economic centers of our modem
life. They promise a secured and much better life conditions as
compared to the opportunities found in rural areas. As a
consequence, the population of cities and urban centers has
tremendously increased in the past and have become the densest
populated regions in the world over the past few decades.
Meinel et al (2001) has observed this strong trend of urban
migration which is much experienced in less developed
countries. The Philippines, with its peace and order problems in
the countryside, has witnessed the exodus of people to the urban
centers particularly the National Capital Region. The Metro
Manila Urban Services for the Poor Project (MMUSP) reported
in 2002 that Metro Manila has joined the small group of mega
cities worldwide with populations of more than 10 million. This
concentration of people in very dense populated urban areas
presents tremendous challenge to managers and planners. It
requires the introduction of sophisticated monitoring systems
for planning purposes such as a satellite acquired data providing
a regularly observed synoptic overview of large areas.
High resolution satellite images offer abundance of information
of the earth’s surface for remote sensing applications including
mapping and monitoring of urban areas. Hoffman (2001),
Herold (2002), and Shackelford and Davis (2003) are just some
of the works done in this particular field. Thomson and Hardin
(2000) integrated remote sensing and GIS to identify site
specific information on land cover for mapping urban
residential land use. Although a number of experiments have
been performed for urban areas, the number of applications
dealing with informal settlements is very limited. One possible
reason for this seemingly lack of attention and interest for
informal settlement studies is the fact that most researchers
come from developed countries that does not experience
housing shortage. To illustrate the housing problem in Metro
Manila, approximately 3.5 million residents live in depressed
neighborhoods across the nation’s capital (MMUSP Report,
2002). Most of them remain undocumented by the government
making it difficult to gather demographic data. Information
particularly on the number of people living in informal
settlements is often limited, since inhabitants are often
inadequately covered by formal censuses (Uzun and Cete 2004).
This paper envisioned the creation of a highly accurate large-
scale natural color image map from high resolution satellite
imagery to be used as a base map suitable for the University of
the Philippines as a reference for physical planning,
management and other mapping purposes. In addition, this
paper aim to map from the established base map the informal
settlements inside the campus and determine if population of
these communities can be effectively estimated using the high
resolution satellite image.
2. LITERATURE REVIEW
Studies in the past have demonstrated the ability of remotely
sensed data to extract socio-economic attributes directly or
indirectly by means of surrogate informations. According to
Cowen and Jensen (1998), population estimates are being made
every 5-7 years in western countries requiring the need for
high-spatial resolution remotely sensed data. They described
various uses of remote observation including measuring the area,
height and volume of buildings, measuring traffic patterns and
road conditions, estimation of residential energy demand and
building predictive models of residential expansion utilizing
high-spatial resolution (0.3-0.5 m) panchromatic and/or color
infrared aerial photography.
The operational potential of high resolution satellite data
depends on its ability to respond to the requirements of the