Analyzing the posterior predictive capability and usability of landslide susceptibility maps: a case of Kerala, India

Abstract Landslide susceptibility maps serve as the basis for hazard and risk assessment, as well as risk-informed land use planning at various spatial scales. Researchers create these maps aiming to fulfil a variety of purposes, including infrastructure planning and restrictive land use zoning. These applications require accurate and specific information to fulfil these purposes, as decisions based on these maps have the potential to cost lives and cause infrastructure damage. The usability of the maps depends on whether they provide the required information and their accuracy to be utilized for the intended purpose. Therefore, assessing the usability and predictive accuracy of landslide susceptibility maps is of paramount importance. Typically, the accuracy of the maps is evaluated using the same landslide inventory that was used to create the map, which does not actually test the predictive ability of the maps in future situations. In this study, we briefly reviewed the purposes of the map creation using literature and stakeholder interviews and assessed the accuracy of three landslide susceptibility maps in a posterior manner. We generated a multi-temporal landslide event inventory after the creation dates of these landslide susceptibility maps. We devised a method to evaluate classified maps by making use of Unique Conditions Units (UCUs) to compare the posteriorly predicted susceptibility classes and the new landslide occurrences. Interviews with stakeholders revealed a disconnection between the aims set forth by map producers and the specific needs of the end users. Our posterior assessment shows that overall predictions of the maps provide plausible results; however, their interpretations for different use cases make them less likely to be used. When comparing the maps using UCUs, landslide densities overlap between the different susceptibility classes, indicating low predictive performance of the maps. Direct comparison of all maps shows a low agreement between susceptibility classes, which pinpoints the uncertainties in data and methods used to create different maps. This study highlights the need for purpose-oriented landslide susceptibility mapping and posterior assessment of the predictive capabilities of these maps aiming to fulfil respective purposes.