GIS-Based Integration of Subjective and Objective Weighting Methods for Regional Landslides Susceptibility Mapping

Abstract

Abstract:The development of landslide susceptibility maps is of great importance due to rapid urbanization. The purpose of this study is to present a method to integrate the subjective weight with objective weight for regional landslide susceptibility mapping on the geographical information system (GIS) platform. The analytical hierarchy process (AHP), which is subjective, was employed to weight predictive factors' contribution to landslide occurrence. The frequency ratio (FR) method, which is objective, was used to derive subclasses' frequency ratio with respect to landslides that indicate the relative importance of a subclass within each predictive factor. A case study was carried out at Tsushima Island, Japan, using a historical inventory of 534 landslides and seven predictive factors: elevation, slope, aspect, terrain roughness index (TRI), lithology, land cover and mean annual precipitation (MAP). The landslide susceptibility index (LSI) was calculated using the weighted linear combination of factors' weights and subclasses' weights. The study area was classified into five susceptibility zones according to the LSI. In addition, the produced susceptibility map was compared with maps generated using the conventional FR and AHP method and validated using the relative landslide index (RLI). The validation result showed that the proposed method performed better than the conventional application of the FR method and AHP method. The obtained landslide susceptibility maps could serve as a scientific basis for urban planning and landslide hazard management.

Landslide susceptibility mapping by using a geographic information system (GIS) along the China–Pakistan Economic Corridor (Karakoram Highway), Pakistan

“…where λ max is the maximum eigenvalue of matrix and n is the number of controlling parameters involved (Zhou et al, 2016). Saaty (1987) produced a table (Table 3) of random consistency index (RI) after calculation from 500 samples.…”

“…ROC is a better choice than other techniques as it is threshold independent and measures both accuracy and error rate (Fawcett, 2006;Vakhshoori and Zare, 2018). Multiple researchers used ROC for validation of produced maps (Ahmed, 2015;Basharat et al, 2016;Lee, 2005;Zhou et al, 2016). In this study, we also used ROC and LDA to estimate the predictive accuracy of the map.…”

Country Selection Model for Sustainable Construction Businesses Using Hybrid of Objective and Subjective Information

“…For these reasons, a hybrid model, which incorporates both objective information and subjective opinion, can provide support that is both strategic and reliable for the decision maker. While, this kind of hybrid model has not been suggested in the construction business sector, several hybrid models have been introduced in other entrepreneurial sectors such as environment, hazard, and supply chain [37][38][39][40]. Thus, this study develops a hybrid model for country selection considering another benchmark model of sectors.…”

Susceptibility Assessments of Landslides in Hulu Kelang Area Using a Geographic Information System-Based Prediction Model

“…Wang et al (2015) conducted a susceptibility assessment of landslides in Boaxing Catchment, Sichuan, China, based on a Geographical Information System (GIS) and an Area Under Receiver operating Characteristic Curve (AUC) [2]. Zhou et al (2016) integrated the subjective weight and objective weight for regional landslides susceptibility analysis based on GIS [3]. Additionally, a study on cost of damage and effect of adaptation to landslides by considering climate change was conducted to relate landslides with climate change [4].…”