About this Research Topic
Earthquakes have long been recognized as one of the main triggers for landslides across the Earth. The earthquakes we experienced in the last few decades (e.g., the 1994 Northridge, USA, the 2008 Wenchuan, China, the 2015 Gorkha, Nepal, and the 2018 Hokkaido, Japan, earthquakes) have shown that moderate and large earthquakes in mountainous terrain, can produce clusters of several hundred to thousands of landslides in a very short period. In turn, the earthquake-triggered landslides threaten our society by their direct and indirect, long-term effects such as damaged infrastructure, increased debris flows and floods associated with landslide dam failures and downstream river aggradations. As a result, the investigations of earthquake-triggered landslides have received much attention in recent years, due to their probable results of the tragic loss of life and economic devastation.
With the rapid development of GIS and remote sensing technologies, valuable progress has been made in the earthquake-triggered landslides research field. The ability and efficiency of extracting large-scale and massive earthquake-triggered landslide data has been greatly improved. The number and quality of earthquake-triggered landslide records are increasing. The susceptibility, hazard, and risk assessment models of earthquake-triggered landslides are becoming more advanced and precise, and the ability to process large-scale and high-precision data is more robust. Remote sensing and GIS technologies have greatly improved the ability of information acquisition and big data analysis of earthquake-triggered landslides. Furthermore, remote sensing and GIS technologies have significantly promoted the progress of identification, mapping, monitoring and early warning and risk evaluation of earthquake-triggered landslides.
However, there are still several key issues that need further analysis, such as the non-uniform methods for landslide mapping, the roles of various ground motion characteristics in landslide initiation mechanisms, factors controlling landscape evolution in post-seismic periods and the development of better susceptibility and hazard models, especially in data-scarce environments.
We call researchers to contribute Original Research Articles and Review Articles related to the application of remote sensing and GIS in earthquake-triggered landslides. Although we have focused this Research Topic on the application of remote sensing and GIS in earthquake-triggered landslides, other excellent studies related to earthquake-triggered landslides are also welcome.
Potential topics include, but are not limited to:
•Inventory mapping of earthquake-triggered landslides;
•Field investigations, descriptions, and cause mechanism analysis of individual, large-scale earthquake-triggered landslides;
•Applications of new GIS, remote sensing, and GPS technologies in earthquake-triggered landslides;
•Susceptibility and hazard modeling for earthquake-triggered landslides;
•Use of data mining techniques on earthquake-triggered landslides;
•In-depth controlling factor analysis of earthquake-triggered landslides;
•Monitoring and modeling earthquake-triggered landslide-derived debris flow and sediment flux events and their dynamics;
•Post-earthquake recovery in earthquake struck hillslopes.
With the rapid development of GIS and remote sensing technologies, valuable progress has been made in the earthquake-triggered landslides research field. The ability and efficiency of extracting large-scale and massive earthquake-triggered landslide data has been greatly improved. The number and quality of earthquake-triggered landslide records are increasing. The susceptibility, hazard, and risk assessment models of earthquake-triggered landslides are becoming more advanced and precise, and the ability to process large-scale and high-precision data is more robust. Remote sensing and GIS technologies have greatly improved the ability of information acquisition and big data analysis of earthquake-triggered landslides. Furthermore, remote sensing and GIS technologies have significantly promoted the progress of identification, mapping, monitoring and early warning and risk evaluation of earthquake-triggered landslides.
However, there are still several key issues that need further analysis, such as the non-uniform methods for landslide mapping, the roles of various ground motion characteristics in landslide initiation mechanisms, factors controlling landscape evolution in post-seismic periods and the development of better susceptibility and hazard models, especially in data-scarce environments.
We call researchers to contribute Original Research Articles and Review Articles related to the application of remote sensing and GIS in earthquake-triggered landslides. Although we have focused this Research Topic on the application of remote sensing and GIS in earthquake-triggered landslides, other excellent studies related to earthquake-triggered landslides are also welcome.
Potential topics include, but are not limited to:
•Inventory mapping of earthquake-triggered landslides;
•Field investigations, descriptions, and cause mechanism analysis of individual, large-scale earthquake-triggered landslides;
•Applications of new GIS, remote sensing, and GPS technologies in earthquake-triggered landslides;
•Susceptibility and hazard modeling for earthquake-triggered landslides;
•Use of data mining techniques on earthquake-triggered landslides;
•In-depth controlling factor analysis of earthquake-triggered landslides;
•Monitoring and modeling earthquake-triggered landslide-derived debris flow and sediment flux events and their dynamics;
•Post-earthquake recovery in earthquake struck hillslopes.
Keywords: remote sensing, GIS, spatial distribution, earthquake-triggered landslides, modeling
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
