Abstract
Despite landslide inventories being compiled throughout the world every year at different scales, limited efforts have been made to critically compare them using various techniques or by different investigators. Event-based landslide inventories indicate the location, distribution, and detected boundaries of landslides caused by a single event, such as an earthquake or a rainstorm. Event-based landslide inventories are essential for landslide susceptibility mapping, hazard modeling, and further management of risk mitigation. In Nepal, there were several attempts to map landslides in detail after the Gorkha earthquake. Particularly after the main event on 25 April 2015, researchers around the world mapped the landslides induced by this earthquake. In this research, we compared four of these published inventories qualitatively and quantitatively using different techniques. Two principal methodologies, namely the cartographical degree of matching and frequency area distribution (FAD), were optimized and applied to evaluate inventory maps. We also showed the impact of using satellite imagery with different spatial resolutions on the landslide inventory generation by analyzing matches and mismatches between the inventories. The results of our work give an overview of the impact of methodology selection and outline the limitations and advantages of different remote sensing and mapping techniques for landslide inventorying.
Highlights
Landslides are the most frequent hazards of mountain regions throughout the world [1]
We evaluated four manually extracted landslide inventory maps of the Gorkha earthquake 2015, Nepal
The landslide inventory map was manually mapped by the authors in the immediate aftermath of the earthquake using a range of earth observation (EO) data sources, including web-hosted high-resolution optical data in GoogleTM Crisis Response (e.g., United Kingdom - Disaster Monitoring Constellation-2 (UK-DMC2), Disaster Monitoring Constellation for the International Charter (DMCii), Worldview, Digital Globe Inc., SPOT National Centre for Space Studies (CNES), imagery accessed via the Disaster Charter, imagery available from United States Geological Survey (USGS) Hazards Data Distribution System
Summary
Landslides are the most frequent hazards of mountain regions throughout the world [1]. The spatial resolution of the available EO data plays a critical role in the quality of the resulting landslide inventory maps [17,18]. Another work by [3] compared photo-interpreted and semi-automatic landslide inventory maps in the Pogliaschina catchment, Italy They compared the quality of rainfall event-based inventories cartographically and statistically. Four different research teams from different parts of the world carried out landslide inventories related to this earthquake and published their resulting maps These studies used various EO data sources, such as very high-resolution WorldView imagery and coarser-resolution used various EO data sources, such as very high-resolution WorldView imagery and coarserimageries.
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