LANDSLIDE SUSCEPTIBILITY ZONATION OF SIGI BIROMARU AND SURROUNDING AREAS, SIGI REGENCY, CENTRAL SULAWESI PROVINCE USING FREQUENCY RATIO (FR), WEIGHT OF EVIDENCE (WOE), LOGISTIC REGRESSION (LR), AND COMBINATIONS METHODS

• Main Author: Albern Telaumbanua, Jevon
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/54070
• Institution: Institut Teknologi Bandung

The Sigi Biromaru area and its surroundings are part of the Palu wartershed in Sigi Regency, Central Sulawesi Province. Based on lanslide susceptibility map of Central Sulawesi, this area has medium to high landslide susceptibility. Morphological conditions in the form of steep hills are one of the controlling factors for landslides. The landslide susceptibility maps currently available is still at a provincial scale. This study aims to determine the susceptibility of landslides for more detailed scale, which is the sub-catchment scale. The method used to analyze the susceptibility of landslides consists of two types, a single statistical method, and a combination statistical method. Single statistical methods consist of bivariate methods, namely frequency ratio (FR), weight of evidence (WoE), and multivariate, namely logistic regression (LR). Combined statistical methods consist of FR-LR and WoE-LR. The combination of the bivariate and multivariate methods is expected to be able to take advantage of the strengths and overcome the weaknesses of each method. Based on remote sensing identification on drone aerial photos, Google Earth, and Sentinel 2B imagery, there were 265 landslides between 2009-2019 in the study area. The landslide event data is then divided randomly into two groups, training data as much as 70% or (186 landslides) and test data as much as 30% (79 landslides). Twenty-one parameters were tested for their influence on landslides, there are slope gradient, aspect, plan curvature, profile curvature, total curvature, elevation, flow direction, terrain ruggedness index (TRI), topographic wetness index (TWI), stream power index (SPI), distance from lineament, lineament density, distance from the river, river density, lithology, soil type, soil texture, clay content (< 0.002 mm), peak ground acceleration, rainfall, and land cover. Based on the value of the area under curve (AUC), the dominant parameters that affect the occurrence of landslides in the study area using the FR and WoE methods are slope, elevation, slope direction, flow direction, peak ground acceleration, clay content (< 0.002 mm), land cover, terrain ruggedness index (TRI), river density, soil type, lineament density, lithology, rainfall, and stream power index (SPI). The dominant parameters that influence the occurrence of landslides in the study area using the LR method are slope gradient, elevation, clay content (< 0.002 mm), river density, lineament density, SPI, rainfall, and TRI. The dominant parameters that affect the occurrence of landslides in the study area using the FR-LR and WoE-LR methods are slope gradient, elevation, aspect, flow direction, clay content (<0.002 mm), land cover, TRI, river density, lineament density, rainfall, lithology, SPI, soil type, and peak ground acceleration. Evaluation results based on area under curve (AUC) value of success rate showed that the WoE-LR (0.849) and FR-LR (0.840) methods are better than the WoE (0.811), LR (0.799), and FR (0.799) methods. The evaluation results based on AUC value of prediction rate showed that the WoE-LR (0.792) and FR-LR (0.790) methods are better than the LR (0.782), WoE (0.756), and FR (0.752) methods. Based on the Seed Cell Area Index (SCAI) analysis, the landslide susceptibility zoning map produced by the combination FR-LR and WoE-LR method has better results in very low and high susceptibility zones. Based on spatial domain analysis, FR-LR and WoE-LR methods produce a higher level of correct pixels than FR, WoE, and LR methods. Based on the results, it is concluded that the FR-LR and WoE-LR methods have better accuracy than the FR, WoE, and LR methods for landslide susceptibility zonation in the Sigi Biromaru area and its surroundings.