An objective absence data sampling method for landslide susceptibility mapping.

The accuracy and quality of the landslide susceptibility map depend on the available landslide locations and the sampling strategy for absence data (non-landslide locations). In this study, we propose an objective method to determine the critical value for sampling absence data based on Mahalanobis distances (MD). We demonstrate this method on landslide susceptibility mapping of three subdistricts (Upazilas) of the Rangamati district, Bangladesh, and compare the results with the landslide susceptibility map produced based on the slope-based absence data sampling method. Using the 15 landslide causal factors, including slope, aspect, and plan curvature, we first determine the critical value of 23.69 based on the Chi-square distribution with 14 degrees of freedom. This critical value was then used to determine the sampling space for 261 random absence data. In comparison, we chose another set of the absence data based on a slope threshold of < 3°. The landslide susceptibility maps were then generated using the random forest model. The Receiver Operating Characteristic (ROC) curves and the Kappa index were used for accuracy assessment, while the Seed Cell Area Index (SCAI) was used for consistency assessment. The landslide susceptibility map produced using our proposed method has relatively high model fitting (0.87), prediction (0.85), and Kappa values (0.77). Even though the landslide susceptibility map produced by the slope-based sampling also has relatively high accuracy, the SCAI values suggest lower consistency. Furthermore, slope-based sampling is highly subjective; therefore, we recommend using MD -based absence data sampling for landslide susceptibility mapping.

Has the IPCC's revised vulnerability concept been well adopted?

In the Third and Fourth Assessment Reports (TAR and AR4, respectively) by the Intergovernmental Panel on Climate Change (IPCC), vulnerability is conceived as a function of exposure, sensitivity, and adaptive capacity. However, in its Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX) and Fifth Assessment Report (AR5), the IPCC redefined and separated exposure, and it reconceptualized vulnerability to be a function of sensitivity and capacity to cope and adapt. In this review, we found that the IPCC's revised vulnerability concept has not been well adopted and that researchers' preference, possible misinterpretation, possible confusion, and possible unawareness are among the possible technical and practical reasons. Among the issues that need further clarification from the IPCC is whether or not such a reconceptualization of vulnerability in the SREX/AR5 necessarily implies nullification of the TAR/AR4 vulnerability concept as far as the IPCC is concerned.

IPCC's current conceptualization of 'vulnerability' needs more clarification for climate change vulnerability assessments.

In this Short Communication, we raise the concern that the existing conceptualization of 'vulnerability', introduced in the IPCC Fifth Assessment Report (AR5), is not facilitative for standalone vulnerability assessments and that this conceptualization has not been well accepted by the vulnerability researchers. We identify three key reasons for low adoption of the AR5 conceptualization in climate change vulnerability assessments, and urge the IPCC Working Group II to clarify how the current conceptualization of 'vulnerability' can facilitate standalone climate change vulnerability assessments. We propose treating 'exposure' not only as a precondition for vulnerability but also as a secondary driver of vulnerability to capture the influence of differential exposure.