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The purpose of this paper is to show how images from satellite could 
be used to predict flood prone areas based on the hydrological 
characteristics. In order to predict the flood disaster, many 
hydrological methods can be adopted. But the lcwpoint is that most of 
these method neglects the landuse factor. In developing countries where 
deforestation is advancing and the drastic landuse changes takes place 
almost every year, it is difficult to know the latest characteristics of 
the basin. In this sense it is very dangerous to adopt any hydrological 
method without taking into account the changing phase of landuse pattern 
for a particular area. 
Satellite data from the 1985 LANDSAT MSS band 4, 5, 6 and 7 was used. 
The DEM was produced fran interpolation of contour heights at interval 25 
meter from 1:10000 topographical map. Interpolation of every 15 m was 
performed based on the natural cubic spline algorithm. 
The hardware used in this study is the IBM - XT microcomputer with a 
Intel 8088 microprocessor. The microcomputer is connected to a IBM 
Proffessional Graphic Display (PGD). The PGD is equipped with a color 
card called Proffessional Graphic Controller (PGC). The PGC is capable of 
displaying 256 colors at any one time with a resolution of 640 x 480 
pixels. These colors can be remapped out of a palette of 4096 possible 
colors. 
The software used was originally developed for satellite image 
processing at the Faculty of Surveying, Universiti Teknologi Malaysia. 
With a few modification on the current software, it was used for this 
study. 
METHODOLOGY OF STUDY 
The computer and the remotely sensed data is a very useful tool for 
helping decision makers identify potential flood prone areas. The main 
advantage of using this method is that it can readily and inexpensively 
aggregate map overlays. 
The risk probability analysis described here is based on weights 
assigned to factors that are bound to influence the occurence of flood. 
The factors considered in this study are: 
a. Runoff Volume. 
b. Runoff timing. 
b. Interception. 
c. Depression Storage. 
d. Detention Storage. 
e. Channel detention. 
The following assumptions has to be observed before the above factors 
can be considered. The assumptions are: 
a. Area with several soil type will have corresponding number of 
infiltration rate.