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Poster Session 3
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Integration of Remote Sensing and GIS Techniques
for Landside Applications
2.3 Land Use Map
A land use map was produced from the Landsat-5 TM data. The land use for the study area is classified into 4 types i.e. forest, bush, agricultural and residential by using the nearest neighbour method of supervised classification techniques. The land use map as shown in figure 4 is then density sliced into different risk zones based on the study of Morgan (1986).
Figure 4 : Land use map.
2.4 Underground Water Level Map
The underground water level map was produced from the combination of the above data which include the slope inclination, elevation, band 6 DN values and Normalised Difference Vegetation Index (NDVI). The result is as shown in figure 5 with other underground water level ranging from 0-18m. Wet and agriculture areas have shallow water. According to Takagi [1991], most landslides occur at ground level of 3-6m.
Figure 5: Underground water level map
3.0 Results and Discussions
All the data were manipulated by using the ILWIS 2.02 software. The data were classified into different risks zones and the risk maps were combined to produce final risk maps (figure 6 & 7). Figure 7 shows the most of the risk areas are located in areas near the road side and at agricultural areas. These areas have temperatures between 24-26°C, slope inclination between 400m-500m and underground water level between 3-6m. Although there is no evidence to prove that these areas are riskily, the combination of the above factors indicate that these areas are more risky than other areas in the study area.
Figure 6: GIS spatial database.
Figure 7 : Landslide risk map from combination of all factors.
4.0 Conclusion
The study shows that remote sensing techniques when integrated with GIS can provide a useful tool to study potential landslide areas. However, the accuracy of the final results depends in the parameters that are included in the data set. In this study, no all the necessary parameters have been included due to lack of data.
References
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Gao, J. Lo, C. P. (1995), Micro-Scale Modelling of Terrain Susceptibility to Landsliding from a DEM : A GIS Approach, Geocarto International, Vol. 10, No. 4, ms. 15-30.
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Morgan, R. P. C. (1986), Soil Erosion and Conservation, Longman Group UK Limted
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Shikada, M. Kusaka, T., Kawata, Y. and Miyaki, K., (1994), Extraction of Characteristic Properties in Landslide Areas Using Thematic Mapper Data And Surface Temperature, Geoscience and Remote Sensing Sym., (IGARSS), Vol. V, ms. (103)-105.
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Takagi, M. and Murai, S. (1991), Inference of Landslide Area from Landsat TM and DTM data, Proc. of The 12th Asian Conf. on Remote Sensing, Singapore, ms. J-4-1-J-4-5.
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