Earth Observation Applications to Landslide Mapping, Monitoring and Modeling
Cutting-edge Approaches with Artificial Intelligence, Aerial and Satellite Imagery
- 1st Edition - November 8, 2024
- Imprint: Elsevier
- Editors: Viorel Ilinca, Zenaida Chitu, Ionuţ Şandric
- Language: English
- 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 Approacheswith 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 Approacheswith 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 (EarthObservation) 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 Modeling 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
- Title of Book
- Cover image
- Title page
- Table of Contents
- Copyright
- List of contributors
- Section 1: Introduction
- Chapter one. A review of UAV-based data applications for landslide mapping and monitoring
- Abstract
- Introduction
- Regulation
- Unmanned aerial vehicle types and their sensors
- Unmanned aerial vehicle data acquisition
- Unmanned aerial vehicle application to landslides
- Landslide monitoring and assessment
- Bibliometric analysis
- Conclusions
- References
- Chapter two. A review of the state-of-the-art use of satellite Earth observation data for landslide mapping and monitoring
- Abstract
- Introduction
- Earth observation data for landslide mapping
- Machine learning for landslide detection
- Conclusion
- References
- Section 2: Satellite data in landslide mapping and monitoring
- Chapter three. On the use of the EGMS data for studying landslides in Great Britain
- Abstract
- Highlights
- Introduction
- Study area
- Datasets and methodology
- Results
- Discussion
- Conclusions
- Acknowledgments
- References
- Chapter four. Deciphering the kinematics of urban landslides through SAR imagery analysis
- Abstract
- Introduction
- Synthetic aperture radar imagery processing and landslide analysis
- DInSAR application to urban landslides
- Advances, limitations, and perspectives
- Conclusions
- References
- Chapter five. Artificial intelligence applications for landslide mapping and monitoring on EO data
- Abstract
- Introduction
- Earth observation sensors
- Artificial intelligence models
- Artificial intelligence models in landslide mapping
- Artificial intelligence models for landslide monitoring and early warning
- Discussion
- References
- Chapter six. Mapping landslides on Earth, Moon, and Mars using satellite imagery and deep learning techniques
- Abstract
- Introduction
- Popular convolutional neural networks architectures and training strategies
- Semantic segmentation of landslides on earth
- Object detection of planetary rockfalls
- Summary
- References
- Section 3: Drone applications for landslide mapping and monitoring
- Chapter seven. Landslide volume and runoff monitoring using UAV photogrammetry
- Abstract
- Introduction
- Materials and methods
- Landslide monitoring site case study
- Results and discussion
- Conclusions
- Funding
- References
- Chapter eight. Landslide 3D reconstruction and monitoring using oblique and nadiral drone aerial imagery
- Abstract
- Introduction
- Study area
- Methods
- Results
- Discussions and conclusions
- References
- Chapter nine. Geomorphic monitoring and assessment of debris flows using drone-based structure from motion
- Abstract
- Introduction
- Overview of debris flow monitoring and assessment by drone-based SfM survey
- Progress in the spatial resolution of topographic data
- Progress in the measurement frequency
- Applications of orthophotos in monitoring and assessment of debris flow-related phenomena
- Management of errors in DEMs and perspective of drone-based SfM surveys for debris flows
- Acknowledgment
- Conflicts of interest
- Funding
- References
- Chapter ten. Machine learning and object-based image analysis for landside mapping using UAV-derived data
- Abstract
- Introduction
- Background
- Object-based mapping of landslide zones
- Discussion
- Conclusion
- References
- Chapter eleven. Estimating kinematic uncertainties of landslides using UAV time series
- Abstract
- Introduction
- Study area
- Data and methods
- Results
- Discussions
- Conclusions
- Acknowledgments
- References
- Chapter twelve. Detailed landslide kinematics mapping using short-term UAV time-series. Case study: Livadea landslide, Romania
- Abstract
- Introduction
- Results
- Discussions
- Conclusions
- Acknowledgment
- References
- Section 4: EO data assimilations in landslide susceptibility, hazard mapping and risk assessment
- Chapter thirteen. Building landslide inventory with LiDAR data and deep learning
- Abstract
- Introduction
- Study area
- Data
- Methodology
- Results and discussion
- Conclusion
- References
- Chapter fourteen. Landslide susceptibility mapping using machine-learning algorithms and earth observation data
- Abstract
- Introduction
- Materials and methods
- Results and discussion
- Conclusion
- References
- Chapter Fifteen. Microwave remote sensing for investigating hydrological preconditions triggering landslides: a case study: Ialomita Subcarpathians, Romania
- Abstract
- Introduction
- Results and discussions
- Conclusions
- References
- Chapter sixteen. Use of UAV imagery for the detection and measurement of damages to road networks in landslide areas
- Abstract
- Introduction
- Road deformation monitoring: from in-situ measurements to remote sensing techniques
- Sensors for assessing road damage and condition
- UAV platforms for pavement damage assessment in landslide-affected areas
- Pavement damage detection and classification using a UAV-integrated camera: a case study in North Italy
- Final remarks
- References
- Section 5: Future challenges and future outlook
- Chapter seventeen. Mapping the existing challenges and pathway forward
- Abstract
- Current state
- Current challenges
- What future holds
- Conclusions
- AI Disclosure
- References
- Index
- Edition: 1
- Published: November 8, 2024
- No. of pages (eBook): 400
- Imprint: Elsevier
- Language: English
- eBook ISBN: 9780128241981
VI
Viorel Ilinca
Viorel Ilinca, PhD in Geography, has a rich background in physical geography and geology. Since joining the Geological Institute of Romania in 2010, he has been an integral part of the Geological Mapping Group, where he focuses on landslide research, geomorphological and geological mapping, GIS, cartography and geoheritage. With extensive experience in both national and international research projects, he has worked on various applications of geomorphology and geological mapping for natural hazard assessment. In the field of landslides, he uses field surveys and earth observation to study different types of landslides.
Affiliations and expertise
Geological Institute of Romania, Bucharest, RomaniaZC
Zenaida Chitu
Zenaida Chițu, PhD in Geography, has expertise in the integration of physical modeling, GIS, earth observation and ground measurement networks in the monitoring of landslide activity. Her work covers hydrology, climatology and geomorphology, with a special focus on landslides. She has led national research projects aimed at improving our understanding of landslides by combining methods from different disciplines including geomorphology, engineering geology, hydrology and meteorology. Her recent research includes estimating soil moisture using a mix of hydrological modelling, remote sensing and field measurements, and investigating the impact of climate change on different sectors.
Affiliations and expertise
National Meteorological Administration, Bucharest, RomaniaIŞ
Ionuţ Şandric
Ionuț Șandric, currently an Associate Professor at the Faculty of Geography, University of Bucharest, brings extensive experience in research and commercial projects. He specializes in combining geospatial knowledge with software engineering to develop geospatial environmental models. His research focuses on the spatial and temporal modeling of landslides, including tools for assessing the propagation of uncertainty in landslide hazards. He has led projects on multi-hazard and multi-risk 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
Faculty of Geography, University of Bucharest, Bucharest , RomaniaRead Earth Observation Applications to Landslide Mapping, Monitoring and Modeling on ScienceDirect