LEADER 03398nam 2200985z- 450 001 9910557765003321 005 20231214132953.0 035 $a(CKB)5400000000045711 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/69282 035 $a(EXLCZ)995400000000045711 100 $a20202105d2020 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAdvances in Remote Sensing-based Disaster Monitoring and Assessment 210 $aBasel, Switzerland$cMDPI - Multidisciplinary Digital Publishing Institute$d2020 215 $a1 electronic resource (232 p.) 311 $a3-03943-322-9 311 $a3-03943-323-7 330 $aRemote 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. 606 $aResearch & information: general$2bicssc 610 $awildfire 610 $asatellite vegetation indices 610 $alive fuel moisture 610 $aempirical model function 610 $aSouthern California 610 $achaparral ecosystem 610 $aforest fire 610 $aforest recovery 610 $asatellite remote sensing 610 $avegetation index 610 $aburn index 610 $agross primary production 610 $aSouth Korea 610 $aland subsidence 610 $aPS-InSAR 610 $auneven settlement 610 $abuilding construction 610 $aBeijing urban area 610 $afloodplain delineation 610 $ainaccessible region 610 $amachine learning 610 $aflash flood 610 $arisk 610 $aLSSVM 610 $aChina 610 $aHimawari-8 610 $athreshold-based algorithm 610 $aremote sensing 610 $adryness monitoring 610 $asoil moisture 610 $aNIR-Red spectral space 610 $aLandsat-8 610 $aMODIS 610 $aXinjiang province of China 610 $aSDE 610 $aPE 610 $agroundwater level 610 $acompressible sediment layer 610 $atropical cyclone formation 610 $aWindSat 610 $adisaster monitoring 610 $awireless sensor network 610 $adebris flow 610 $aanomaly detection 610 $adeep learning 610 $aaccelerometer sensor 610 $atotal precipitable water 610 $aHimawari-8 AHI 610 $arandom forest 610 $adeep neural network 610 $aXGBoost 615 7$aResearch & information: general 700 $aIm$b Jungho$4edt$01309870 702 $aPark$b Haemi$4edt 702 $aTakeuchi$b Wataru$4edt 702 $aIm$b Jungho$4oth 702 $aPark$b Haemi$4oth 702 $aTakeuchi$b Wataru$4oth 906 $aBOOK 912 $a9910557765003321 996 $aAdvances in Remote Sensing-based Disaster Monitoring and Assessment$93029684 997 $aUNINA