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Remotely sensed data integration for landslide vulnerability mapping

Lookup NU author(s): Dr Meredith Williams


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Landslides in Vietnam have been on the increase in the recent years. They have both social and economic impacts. To understand the behaviour of seasonal soil moisture and geological characteristics that influence landslides multi-sources satellite image integration had been used. The Eastern part of Caobang province (Vietnam) has been selected as the study area. This research site matches the requirement of research, namely mountainous area, complex terrain, and land cover typical of a tropical country. A method based on the modelling of vegetation cover and backscatter coefficient derived from radar data has produced promising initial results for mapping soil moisture using Envisat ASAR images, ALI images, and soil properties. In this model, the effects of vegetation and soil temperature were taken into account and calculated from satellite images and field measurements. The result shows that there is no linear relationship between the backscatter coefficient of Radar data and the soil moisture measured in vegetated areas. The linear relationship between backscatter coefficient and soil moisture measured for bare soil sites is weak, due to the influence of a surface roughness. The Debauchies two dimension discrete wavelet function was used to investigate the usefulness of multisensor image fusion for geological mapping and lineament structure extraction. Recent results show that the wavelet function could be a promising tool. Products fused using a range of difference fusion rules were capable of enhancing several key features. The fused product of ASAR and ASTER PCA 2,3,4 Detail coefficients could be used for lithological interpretation, whilst the fused product of ASAR Approximation coefficient and ASTER PCA 2,3,4 Detail coefficient produced good results for lineament extraction. The final landslide susceptibility model, using the above input parameters, is currently being developed.

Publication metadata

Author(s): Le TCH, Williams M

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Annual Conference of the Remote Sensing and Photogrammetry Society

Year of Conference: 2005