The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B4. Beijing 2008 
planners and how it is integrated with other secondary data 
related with everyday activities. Jain (2007) presented a study 
for linking remotely sensed data with property tax related issues 
and evaluated the capabilities of remote sensing technology to 
measure these attributes accurately at parcel level. Quincey et al. 
(2007) in his study has demonstrated that fine spatial resolution 
imagery facilitates land cover mapping at an unprecedented 
level of detail. 
Other works focused directly on the possible extraction of 
population using remotely sensed data. Rindfuss et al. (1996) 
used remotely sensed data for population migration and social 
change, mainly with micro level data sets in which 
individual/households are the unit of analysis. Lo (2003) 
evaluated the use of satellite data for zone-based estimation of 
population and housing units from land use/land cover maps. 
Dasymetric mapping using the land use/land cover information 
extracted from remotely sensed images to obtain an improved 
estimation of where people actually live was done by Liu (2004). 
Mennis (2003) applied an areal interpolation technique to 
disaggregate census population data into spatial units with 
homogenous land use. 
3. STUDY AREA 
The study area is the University of the Philippines, Diliman 
which is the flagship campus and the largest Constituent 
University of the University of the Philippines System. It is 
located in Quezon City, the most populated city in the nation’s 
capital, making its 493 hectares prime property a hot 
commodity. 
According to an official paper of the university, the squatting 
problem in the campus started in 1970. It was initially tolerated 
and continued to grow until it became a complex problem to the 
administration. One inescapable fact which partly explains this 
occurring problem is that land will always have a market value 
simply because it is an increasingly finite resource in urban 
areas. The shanties left unattended in the 1970s was 
commodified by market forces so that with each transfer of 
ownership, it has increased its market value until eventually, it 
approximated prevailing real estate market values, 
notwithstanding that the land on which it stands has been 
indefinitely reserved by law exclusively for education and 
education-related uses. Several years ago official reports 
estimate over 20,000 squatter families occupy 66 hectares, 
approximately 13 percent of the 493 hectare property claiming 
15 major areas of the campus. 
4. DATA AND SOFTWARES USED 
The satellite data available and suitable for this research was 
QuickBird Satellite Image acquired on April 25, 2004. Imagery 
resolution is sub-meter with the panchromatic (Pan) band 
having an effective ground resolution of 0.61 meters and 2.44 
meters for the four multispectral (XS) bands. 
The image that was purchased from DigitalGlobe for basemap 
production is a ‘Standard Product ’ type Level 2A which means 
that standard radiometric and sensor corrections have been 
applied to the raw imagery by the image supplier. This product 
has also been geometrically corrected and referenced to a 
standard local map projection- in this case a Universal 
Transverse Mercator Zone 51 projection compatible with 
accepted map standards in the Philippines. A coarse DEM was 
used together with RPC (Rational Polynomial Coefficients) 
values in a special polynomial rectification process to correct 
for geometric distortions. 
In this study, ENVI 4.1 software has been used to carry out 
sophisticated image processing operations such as image fusion, 
enhancement, and georeferencing. The initial digitization of 
informal settlements has been done using an open source GIS 
software called fGIS. Arc view 3.2, a GIS software with 
extensive analytical tools and customized regression analysis 
capability have been used for the later works. 
5. METHODOLOGY 
Figure 1 illustrates the detailed methodology adapted in this 
study. 
Figure 1. Methodology flow diagram 
5.1 Image Fusion 
Image fusion is the process of combining multiple images into a 
composite product of which some desired characteristic or 
property of the original images is preserved in the resulting 
image. For this research project, it is desired to combine a 
higher spatial (ground) resolution panchromatic (B/W) image 
with a lower resolution but multi-spectral (natural color and N1) 
image to create a composite image which has the higher 
resolution of the panchromatic image while retaining the multi 
spectral properties required to produce a natural color image 
map. 
There are only several methods that have been developed over 
the past few decades to accomplish data fusion effectively. Each 
of these methods has their own advantages and disadvantages. 
These different methods have been tried and visually evaluated. 
Most remote sensing image processing systems common in the 
market lack the proper tools for image editing and retouching 
and those that have are of high cost. Using improved methods 
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