Abstract
Abstract. Event-based landslide inventories are important for analyzing the relationship between the intensity of the trigger (e.g., rainfall, earthquake) and the density of the landslides in a particular area as a basis for the estimation of the landslide probability and the conversion of susceptibility maps into hazard maps required for risk assessment. They are also crucial for the establishment of local rainfall thresholds that are the basis of early warning systems and for evaluating which land use and land cover changes are related to landslide occurrence. The completeness and accuracy of event-based landslide inventories are crucial aspects to derive reliable results or the above types of analyses. In this study, we generated a relatively complete landslide inventory for the 2018 monsoon landslide event in the state of Kerala, India, based on two inventories that were generated using different methods: one based on an object-based image analysis (OBIA) and the other on field surveys of damaging landslides. We used a collaborative mapping approach based on the visual interpretation of pre- and post-event high-resolution satellite images (HRSIs) available from Google Earth, adjusted the two inventories, and digitized landslides that were missed in the two inventories. The reconstructed landslide inventory database contains 4728 landslides consisting of 2477 landslides mapped by the OBIA method, 973 landslides mapped by field survey, 422 landslides mapped both by OBIA and field methods, and an additional 856 landslides mapped using the visual image (Google Earth) interpretation. The dataset is available at https://doi.org/10.17026/dans-x6c-y7x2 (van Westen, 2020). Also, the location of the landslides was adjusted, based on the image interpretation, and the initiation points were used to evaluate the land use and land cover changes as a causal factor for the 2018 monsoon landslides. A total of 45 % of the landslides that damaged buildings occurred due to cut-slope failures, while 34 % of those having an impact on roads were due to road cut-slope failures. The resulting landslide inventory is made available for further studies.
Highlights
Landslides are a significant type of natural hazard occurring worldwide and incurring serious losses to human society
This paper focuses on the generation of the dataset consisting of a detailed landslide inventory with land use and land cover (LULC) information for two periods: shortly before the event and almost a decade before
The results show that more than half of the damaging landslides (613) surveyed by Geological Survey of India (GSI) were very small (< 500 m2)
Summary
Landslides are a significant type of natural hazard occurring worldwide and incurring serious losses to human society. Critical elements of analysis include their spatial distribution pattern (Duman et al, 2005; Galli et al, 2008; Xu, 2015), their occurrences with respect to landform evolution (Guzzetti et al, 2012; Rosi et al, 2018), and a range of other environment factors (Duman et al, 2005), susceptibility mapping (van Den Eeckhaut et al, 2009), triggering factors (Li et al, 2016), community risk assessment and mitigation (Marcelino et al, 2009), and land use planning and risk management (Colombo et al, 2005). Landslide inventory maps can be generated by compiling existing historical landslide data or acquiring new landslide data using a variety of technical approaches (Rosi et al, 2018; Santangelo et al, 2015)
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