Remote Sensing of Natural Hazards

Each year, natural hazards such as earthquakes, cyclones, flooding, landslides, wildfires, avalanches, volcanic eruption, extreme temperatures, storm surges, drought, etc., result in widespread loss of life, livelihood, and critical infrastructure globally. With the unprecedented growth of the human...

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Detalles Bibliográficos
Otros Autores:	Ahmed, Bayes (Editor), Alam, Akhtar (Otro)
Formato:	Libro electrónico
Idioma:	Inglés
Publicado:	Basel MDPI Books 2022
Materias:	Research & information: general Geography sequential estimation InSAR time series groundwater land subsidence and rebound earthquake rapid mapping damage assessment deep learning convolutional neural networks ordinal regression aerial image landslide machine learning models remote sensing ensemble models validation ice storm forest ecosystems disaster impact post-disaster recovery ice jam snowmelt flood mapping monitoring and prediction VIIRS ABI NUAE flash flood BRT CART naive Bayes tree geohydrological model landslide susceptibility Bangladesh digital elevation model random forest modified frequency ratio logistic regression automatic landslide detection OBIA PBA random forests supervised classification landslides uncertainty K-Nearest Neighbor Multi-Layer Perceptron Random Forest Support Vector Machine agriculture drought NDVI MODIS landslide deformation InSAR reservoir water level Sentinel-1 Three Gorges Reservoir area (China) peri-urbanization urban growth boundary demarcation climate change climate migrants natural hazards flooding land use and land cover night-time light data Dhaka
Ver en Biblioteca Universitat Ramon Llull:	https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009683472206719