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Earth Observation Applications to Landslide Mapping, Monitoring and Modeling. Cutting-edge Approaches with Artificial Intelligence, Aerial and Satellite Imagery

  • Book

  • November 2024
  • Elsevier Science and Technology
  • ID: 5917379
Earth Observation Applications to Landslide Mapping, Monitoring and Modeling: Cutting-edge Approaches with Artificial Intelligence, Aerial and Satellite Imagery focuses on the application of drone and satellite imagery for landslide mapping, monitoring, and modeling. The topics covered include the use of ultrahigh spatial resolution imagery acquired by UAVs (Unmanned Aerial Vehicles) for mapping and predicting landslide activity, the use of satellite imagery for monitoring landslide activity, the assimilation of EO (Earth Observation) data into landslide susceptibility and hazard prediction models, and the building of landslide inventories. The primary objective of this book is the advancement of the scientific understanding and application of technologies to address a variety of areas related to landslide mapping and monitoring for robust and sustainable development. Earth Observation Applications to Landslide Mapping, Monitoring and Modelling be useful for PhD students, postdoctoral researchers, professors, and scientists in geoscience.

Table of Contents

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

Authors

Ionut Sandric Associate Professor, University of Bucharest, Bucharest, Romania; Researcher, Esri Romania, Bucharest, Romania.

Ionu? ?andric, currently an Associate Professor at the Faculty of Geography, University of Bucharest, has extensive experience in over 17 research and commercial projects and specializes in combining geospatial knowledge with software engineering to develop geospatial environmental models. His research focuses on spatial and temporal modeling of landslides, including tools for assessing the propagation of uncertainty in landslide hazards. He has led projects on multihazard and multirisk assessment, drone-based landslide feature mapping, agricultural pathogen detection using drone imagery, urban climate applications using satellite imagery, and soil moisture satellite product analysis for Romania.

Viorel Ilinca Researcher, Geological Survey of Romania, Romania.

Viorel Ilinca has a background in physical geography. He joined the Geological Institute of Romania in 2010 and works in the Geological Mapping Group, where he focuses on landslide research, geomorphological and geological mapping, GIS, cartography, and geoheritage. During the last 14 years, he has been involved in several national and international research projects. As a member of these projects, he has focused on various applications of geomorphology and geological mapping for natural hazard (geohazard) assessment. In the field of landslides, he studies different types of landslides using field surveys and earth observation techniques.

Zenaida Chitu Researcher, National Institute of Hydrology and Water Management, Romania.

Zenaida Chi?u is an experienced Geoscience Researcher specializing in the integration of physically based modeling, GIS, earth observation, and ground measurement networks. Her expertise includes hydrology, climatology, and geomorphology, with a particular focus on landslides. She has led national research projects aimed at improving our understanding of landslide occurrence by combining methods from geomorphology, engineering geology, hydrology, and meteorology. Her current research focuses on the estimation of soil moisture using a combination of hydrological modeling, remote sensing and in situ measurements, and the impact of climate change on various sectors.