Earth Observation Applications to Landslide Mapping and Monitoring: Cutting-Edge Approaches with Machine Learning, Aerial and Satellite Imagery

Earth Observation Applications to Landslide Mapping and Monitoring: Cutting-Edge Approaches with Machine Learning, Aerial and Satellite Imagery is focused on the applications of drone and satellite imagery for mapping landslides. Topics covered include the use of ultra-high aerial imagery, obtained with drones, for mapping and predicting landslide activity (like runoff, volume displacement, exposure to risk, etc.). Subjects related to EO data assimilations into landslide hazard prediction models are also included. The primary aim of this book is to advance the scientific understanding and application of technologies to address a variety of fields related to landslide mapping and monitoring for a robust and sustainable development. Because of the intensification of the catastrophic events in the last 20 years, landslide monitoring gained considerable interest from the geoscience community. Earth Observation Applications to Landslide Mapping and Monitoring: Cutting-Edge Approaches with Machine Learning, Aerial and Satellite Imagery book will be beneficial for the postgraduates, PhD research scholars, professors and scientists, geospatial experts, modelers, oceanography scientists and conservation communities, environmental consultants, big data compilers, and computing experts. Covers the latest trends in algorithms for the observation and mapping of landslides Features clear and detailed case studies and methods that can be easily reproduced and implemented in landslide monitoring systems Includes detailed methods for the application of research to the observation and mapping of landslides INDICE: Part 1 Satellite imagery: Optical and Radar 1. New algorithms for SBAS and PS and their applications to landslide 2. The use of Optical EO data for monitoring landslide. Recent studies demonstrated the use of Sentinel-2 for landslide activity monitoring in French Alps. 3. The fusion of Optical and Radar EO data 4. SAR applications with Deep Learning - focused on DL (CNN) application to SAR and SAR fusion with Optic applications 5. Deep learning applications to EO data for landslide mapping and monitoring - including landslide feature mapping Part 2 Drone applications for landslide mapping and monitoring 6. Landslide activity monitoring using optical ultra-high image resolutions; especially the volume and runoff estimations. 7. Thermal drone imagery for mapping surface soil moisture as a proxy for landslide monitoring 8. Deep learning applications for landslide feature mapping 9. Geocoded video for mapping elements exposed to risk induced by a landslide Part 3 EO data assimilations in landslide susceptibility and hazard mapping 10. Natural hazards mapping and modelling 11. Self-learning algorithms in earth observation applied for landslide mapping and monitoring

• ISBN: 978-0-12-823868-4
• Editorial: Elsevier
• Encuadernacion: Rústica
• Páginas: 400
• Fecha Publicación: 01/04/2023
• Nº Volúmenes: 1
• Idioma: Inglés