Spatial variations of landslide severity with respect to meteorological and soil related factors

Title

Spatial variations of landslide severity with respect to meteorological and soil related factors

Creator

Dutta K.; Poddar A.; Middya A.I.; Roy S.

Description

Landslides, a prevalent natural disaster, wreak havoc on both human lives and vital infrastructure, making them a significant global concern. Their devastating impact is immeasurable, necessitating proactive measures to minimize their occurrence. The ability to accurately forecast the severity of a landslide, including its potential fatality rate and the scale of destruction it may cause, holds tremendous potential for prevention and mitigation to reduce the risk and the damage caused by a landslide to infrastructure and life. In this study, the spatial variability in severity of landslides (in terms of mortality rates) and its dependence on various meteorological, geographical and soil composition has been attempted to be established. To do this, Ordinary Least Squares (global) and various Geographically Weighted (local) models have been employed to observe the varying relation between mortality rates and its various causative factors. Existence of geographical heterogeneity in the relationships is also investigated. The spatial pattern of landslide mortality and its associations with various causative variables in the South Asian Region are investigated and analysed. Through this, insights into targeting of prevention and mitigation measures for landslides based on a given location can be obtained by studying the various forms of heterogeneous spatial associations observed. The outcomes highlight that the local models in the form of Gaussian GWR and Poisson GWR outperform their global counterparts by a huge margin with better R2 and Adj R2 values. In comparison with Poisson GWR and Gaussian GWR, it is seen that Poisson GWR outperforms Gaussian GWR in terms of Mean Absolute Error, Mean Squared Error and Corrected Akaike Information Criterion. Furthermore, several intriguing local relationships patterns are also noted. The Author(s), under exclusive licence to Springer Nature B.V. 2024.

Source

Natural Hazards

Date

2024-01-01

Publisher

Springer Science and Business Media B.V.

Subject

GWR; Landslide; Meteorological factors; Soil variables; Spatial heterogeneity

Coverage

Dutta K., Department of Statistics and Data Science, Christ (Deemed to be) University, Bengaluru, India; Poddar A., Department of Statistics and Data Science, Christ (Deemed to be) University, Bengaluru, India; Middya A.I., Department of Computer Science and Engineering, Jadavpur University, Kolkata, India; Roy S., Department of Computer Science and Engineering, Jadavpur University, Kolkata, India

Rights

Restricted Access

Relation

ISSN: 0921030X

Format

Online

Language

English

Type

Article

Identifier

https://doi.org/10.1007/s11069-024-06930-5

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204785694&doi=10.1007%2fs11069-024-06930-5&partnerID=40&md5=965acfafddc0206acce8d038e28a3815