Advances in Remote Sensing-based Disaster Monitoring and Assessment

Remote sensing data and techniques have been widely used for disaster monitoring and assessment. In particular, recent advances in sensor technologies and artificial intelligence-based modeling are very promising for disaster monitoring and readying responses aimed at reducing the damage caused by d...

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Detalles Bibliográficos
Otros Autores:	Im, Jungho (Editor), Park, Haemi (Otro), Takeuchi, Wataru
Formato:	Libro electrónico
Idioma:	Inglés
Publicado:	Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2020
Materias:	Research & information: general 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
Ver en Biblioteca Universitat Ramon Llull:	https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009655017706719