Abstract
Abstract. An area that located in Kundasang which in Ranau district in Sabah, Malaysia that lies along the bank of Kundasang valley was chosen for comparing the reliability of frequency ratio (FR) and weight of evidence (WoE) methods for landslide activity probability mapping by using related vegetation anomalies indicator. The locations of 47 and 189 of active and dormant landslides respectively were identified using 4 raster layers (topographic openness, hillshade, colour composite and high resolution orthophoto). Each landslide activites were randomly divided into two groups as training (70%) and testing (30%) datasets. Tree height irregularities, DVI, NDVI, SAVI, and OSAVI were considered as landslide bio-indicator. The landslide activity probability maps were prepared using the FR and WoE method. The generated maps were validated by calculating the success and prediction rates from area under receiver operating characteristics (ROC) curve. The results of WoE method were relatively reliable (AUC > 0.8) for dormant landslide while only about 40% of active landslide have been predicted accurately. Similar trend yielded for FR method where least accuracy for active landslide prediction.
Highlights
Landslide is major problem that required attention
The results indicate that dormant activity recorded much better result than active landslide of the landslide activity probability map generated using frequency ration and weight of evidence approach were evaluated using success rate and prediction rate
The results revealed that vegetation anomalies as the indicator of analysing landslide activity is reliable as it gave good value for success rate especially for dormant landslide
Summary
Landslide is major problem that required attention. Landslide is rapid movement downward cause by collapse of a mass of rock or earth from mountain or cliff. It can be triggered by natural activity i.e. earthquake, heavy rainfall or human intervention such as deforestation. Snowmelt or heavy rainfall may affect the structure and mechanical stability of the ground and human activity such as mining and deforestation may cause landslide by making the soil vulnerable to oversaturation and erosion. Landslides are predict to happen in the future under the same conditions (Guzzetti et al, 1999; Lepore et al, 2012; Skilodimou et al, 2018). Landslide inventory map considered as one of the most important elements for landslide studies
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