03439nam 2201009z- 450 991055776500332120210501(CKB)5400000000045711(oapen)https://directory.doabooks.org/handle/20.500.12854/69282(oapen)doab69282(EXLCZ)99540000000004571120202105d2020 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierAdvances in Remote Sensing-based Disaster Monitoring and AssessmentBasel, SwitzerlandMDPI - Multidisciplinary Digital Publishing Institute20201 online resource (232 p.)3-03943-322-9 3-03943-323-7 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 disasters. This book contains eleven scientific papers that have studied novel approaches applied to a range of natural disasters such as forest fire, urban land subsidence, flood, and tropical cyclones.Research and information: generalbicsscaccelerometer sensoranomaly detectionBeijing urban areabuilding constructionburn indexchaparral ecosystemChinacompressible sediment layerdebris flowdeep learningdeep neural networkdisaster monitoringdryness monitoringempirical model functionflash floodfloodplain delineationforest fireforest recoverygross primary productiongroundwater levelHimawari-8Himawari-8 AHIinaccessible regionland subsidenceLandsat-8live fuel moistureLSSVMmachine learningMODISn/aNIR-Red spectral spacePEPS-InSARrandom forestremote sensingrisksatellite remote sensingsatellite vegetation indicesSDEsoil moistureSouth KoreaSouthern Californiathreshold-based algorithmtotal precipitable watertropical cyclone formationuneven settlementvegetation indexwildfireWindSatwireless sensor networkXGBoostXinjiang province of ChinaResearch and information: generalIm Junghoedt1309870Park HaemiedtTakeuchi WataruedtIm JunghoothPark HaemiothTakeuchi WataruothBOOK9910557765003321Advances in Remote Sensing-based Disaster Monitoring and Assessment3029684UNINA