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Remote Sensing of Natural Hazards

Resumen/Descripción – provisto por la editorial

No disponible.

Palabras clave – provistas por la editorial

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

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Información

Tipo de recurso:

libros

ISBN electrónico

978-3-0365-4307-9

País de edición

Suiza