Advances in Remote Sensing-based Disaster Monitoring and Assessment

Advances in Remote Sensing-based Disaster Monitoring and Assessment


English[eng]


wildfire||satellite vegetation indices||live fuel moisture||empirical model function||Southern California||chaparral ecosystem||forest fire||forest recovery||satellite remote sensing||vegetation index||burn index||gross primary production||South Korea||land subsidence||PS-InSAR||uneven settlement||building construction||Beijing urban area||floodplain delineation||inaccessible region||machine learning||flash flood||risk||LSSVM||China||Himawari-8||threshold-based algorithm||remote sensing||dryness monitoring||soil moisture||NIR–Red spectral space||Landsat-8||MODIS||Xinjiang province of China||SDE||PE||groundwater level||compressible sediment layer||tropical cyclone formation||WindSat||disaster monitoring||wireless sensor network||debris flow||anomaly detection||deep learning||accelerometer sensor||total precipitable water||Himawari-8 AHI||random forest||deep neural network||XGBoost||n/a