Application of Remote Sensing Data to Landslide Mapping in Hong Kong

Abstract

Rapid encroachment of Hong Kong’s urban areas into natural terrain creates a considerable potential risk from landslides. In recent years, considerable effort has been directed towards identifying geological parameters that pre-dispose natural terrains to landsliding and the assessments of landslide risk. There has, however, been little investigation of other possible causative factors, specifically, the role of vegetation type and disturbance, particularly hill fires, in promoting shallow landsliding. Fire-denuded hill slopes may be subject to more frequent landsliding events. Today, much of Hong Kong’s hill slopes are covered in fire-prone grasslands, and hill fires associated with cultural festivals are common place. This paper presents an approach to using remote sensing techniques to model areas of disturbed vegetation and detect associated shallow landslides in natural terrain. The research uses data from two satellites, LANDSAT TM and IKONOS. LANDSAT TM is used to detect disturbed vegetation using visible, near and mid-infrared bands and to obtain vegetation indices NDVI and NDMIDIR that indicate plant vigor. IKONOS high resolution multispectral data are used to prepare a color composite image to locate shallow landslides, that are correlated to LANDSAT depicted vegetation indices. Results show that this approach can be used to correlate landslides to areas of disturbed vegetation. Potentially this work has application in defining landslide prone regions.