Full text: Proceedings of the Symposium on Global and Environmental Monitoring (Part 1)

HAZARD RISK MAPPING 
THROUGH SATELLITE IMAGES 
Azmi Hassan, Lecturer 
Faculty of Surveying 
Universiti Teknologi Malaysia 
Skudai Johor Malaysia 
Shattri Mansor, Lecturer 
Faculty of Engineering 
Universiti Pertanian Malaysia 
Serdang Selangor 
ABSTRACT 
Hazards such as floods can be predicted using the appropriate 
combinations of data. This paper will discussed a method of 
flood prediction using the concept of risk probability analysis. 
The heart of this method is to take into account the changing of 
hydrological characteristics of an area through satellite images. 
From this analysis a map will be produced which provides 
information of areas that are prone to flood. Satellite images 
from MSS band 4, 5, 6 and 7 for the year 1985 was used as case 
study. 
INTRODUCTION 
The effective management of flood plains consist of more than 
building detention reservoirs and levees. As urban pressure are forcing 
more and more developments on flood plains, such devices as flood-plain 
regulations and flood proofing are coming into wider use. These devices, 
however, require information as to what areas are likely to be flooded. 
Flood-hazard mapping is a means of providing flood-plain information 
for planning and management programs. Such information should be designed 
to assist officials and private interests in making decisions and 
alternative plans concerning the development of specific lands subject to 
flooding. 
Hydrological models, especially those having parameters defined in 
terms of land cover and other characteristics, are becoming increasingly 
important tool in the development of water resource planning and 
management strategies. Even when the area involved is small, the 
quantification of the spatial distribution of the land covers, soil types 
and topographic variables is extremely tedious and time consuming when 
approached with conventional methods. Fortunately, the efficiency of the 
hydrologic model parameter defination tasks can be increased through the 
used of satellite images, as well as the digital elevation models. 
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