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Earth Observation Applications to Landslide Mapping, Monitoring and Modeling
Cutting-edge Approaches with Artificial Intelligence, Aerial and Satellite Imagery
- 1st Edition - November 1, 2024
- Editors: Ionut Sandric, Viorel Ilinca, Zenaida Chitu
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 2 3 8 6 8 - 4
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 2 4 1 9 8 - 1
Earth Observation Applications to Landslide Mapping, Monitoring and Modeling: Cutting-edge Approaches with Artificial Intelligence, Aerial and Satellite Imagery focuses on the ap… Read more
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Request a sales quoteEarth 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.
- Recent developments in landslide monitoring and mapping algorithms
- Provides clear and detailed case studies and methods that can be easily replicated and implemented in landslide monitoring systems
- Provides detailed methods for applying research to landslide monitoring and mapping
Geologist, geomorphologists, researchers and practitioners working in environmental modelling and remote sensing Environmental engineers and government and NGOs working on prevention of landslides
I. Introduction
i. A review of state of the art in algorithms for SBAS and PS
ii. A review of state of the art in applications for landslides monitoring using drone data
iii. A review of state of the art in the use of EO data from satellites regarding applications in landslides monitoring
II. Satellite data in landslide mapping and monitoring
i. Mapping landslide activity using SAR Data – SBAS and PS
ii. Employing EO datasets to produce event-based landslide inventories
iii. Mapping, monitoring and analysis of the behaviour of urban landslides with SAR imagery
iv. Deep learning applications to EO data for landslide mapping and monitoring
v. Development of semi-automated mapping routines from EO-based landslide mapping on HR and VHR optical satellite imagery
III. Drone applications for landslide mapping and monitoring
i. Landslide volume and runoff monitoring using drone aerial imagery
ii. Landslide 3D reconstruction and monitoring using oblique and nadiral drone aerial imagery
iii. Rapid assessment of damages to infrastructures caused by landslides
iv. Using drone SfM for mapping slopes prone to rockfall
v. Deep learning applications for landslide mapping and detection
IV. EO data assimilations in landslide susceptibility, hazard mapping and risk assessment
i. Multitemporal landslide inventory with EO data as a support for landslide hazard assessment
ii. Landslide susceptibility modelling by remote sensing
iii. Landslide hazard mapping and modelling with EO data
iv. Self-learning algorithms in EO applied for landslide mapping and monitoring
v. Landslide risk assessment with EO data
V. Future challenges and future outlook
i. Mapping the existing challenges and pathway forward
ii. Emerging and potential future applications
i. A review of state of the art in algorithms for SBAS and PS
ii. A review of state of the art in applications for landslides monitoring using drone data
iii. A review of state of the art in the use of EO data from satellites regarding applications in landslides monitoring
II. Satellite data in landslide mapping and monitoring
i. Mapping landslide activity using SAR Data – SBAS and PS
ii. Employing EO datasets to produce event-based landslide inventories
iii. Mapping, monitoring and analysis of the behaviour of urban landslides with SAR imagery
iv. Deep learning applications to EO data for landslide mapping and monitoring
v. Development of semi-automated mapping routines from EO-based landslide mapping on HR and VHR optical satellite imagery
III. Drone applications for landslide mapping and monitoring
i. Landslide volume and runoff monitoring using drone aerial imagery
ii. Landslide 3D reconstruction and monitoring using oblique and nadiral drone aerial imagery
iii. Rapid assessment of damages to infrastructures caused by landslides
iv. Using drone SfM for mapping slopes prone to rockfall
v. Deep learning applications for landslide mapping and detection
IV. EO data assimilations in landslide susceptibility, hazard mapping and risk assessment
i. Multitemporal landslide inventory with EO data as a support for landslide hazard assessment
ii. Landslide susceptibility modelling by remote sensing
iii. Landslide hazard mapping and modelling with EO data
iv. Self-learning algorithms in EO applied for landslide mapping and monitoring
v. Landslide risk assessment with EO data
V. Future challenges and future outlook
i. Mapping the existing challenges and pathway forward
ii. Emerging and potential future applications
- No. of pages: 400
- Language: English
- Edition: 1
- Published: November 1, 2024
- Imprint: Elsevier
- Paperback ISBN: 9780128238684
- eBook ISBN: 9780128241981
IS
Ionut Sandric
Ionuț Șandric, 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.
Affiliations and expertise
Associate Professor, University of Bucharest, Bucharest, Romania; Researcher, Esri Romania, Bucharest, RomaniaVI
Viorel Ilinca
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.
Affiliations and expertise
Researcher, Geological Survey of Romania, RomaniaZC
Zenaida Chitu
Zenaida Chițu 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.
Affiliations and expertise
Researcher, National Institute of Hydrology and Water Management, Romania