Mapping land slide occurrence zones using Remote Sensing and GIS techniques in Kelantan state, Malaysia

2017 International Conference on Space Science and Communication

物理学;无线电电子学

Hashim, M.^1 ; Pour, A.B.^1,2 ; Misbari, S.^1

Geoscience and Digital Earth Centre (Geo-DEC), Research Institute for Sustainability and Environment (RISE), Universiti Teknologi Malaysia (UTM), Malaysia^1

Korea Polar Research Institute (KOPRI), Songdomirae-ro, Yeonsu-gu, Incheon

21990, Korea, Republic of^2

关键词: Analytical Hierarchy Process;    Landslide susceptibility;    Landslide susceptibility mapping;    Normalized difference vegetation index;    Phased array type l-band synthetic aperture radars;    Remote sensing and GIS;    Remote sensing satellites;    Satellite remote sensing data;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/852/1/012023/pdf
DOI  :  10.1088/1742-6596/852/1/012023

来源: IOP

【 摘 要 】

Integration of satellite remote sensing data and Geographic Information System (GIS) techniques is one of the most applicable approach for landslide mapping and identification of high potential risk and susceptible zones in tropical environments. Yearly, several landslides occur during heavy monsoon rainfall in Kelantan river basin, Peninsular Malaysia. In this investigation, Landsat-8 and Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) remote sensing data sets were integrated with GIS analysis for detect, map and characterize landslide occurrences during December 2014 flooding period in the Kelantan river basin. Landslides were determined by tracking changes in vegetation pixel data using Landsat-8 images that acquired before and after December 2014 flooding for the study area. The PALSAR-2 data were used for mapping of major geological structures and detailed characterizations of lineaments in the state of Kelantan. Analytical Hierarchy Process (AHP) approach was used for landslide susceptibility mapping. Several factors such as slope, aspect, soil, lithology, Normalized Difference Vegetation Index (NDVI), land cover, distance to drainage, precipitation, distance to fault, and distance to road were extracted from remote sensing satellite data and fieldwork to apply AHP approach. Two main outputs of this study were landslide inventory occurrences map during 2014 flooding episode and landslide susceptibility map for entire the Kelantan state. Modelled/predicted landslides with susceptible map generated prior and post flood episode, confirmed that intense rainfall in the Kelantan have contributed to weightage of numerous landslides with various sizes. It is concluded that precipitation is the most influential factor that bare to landslide event.