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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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Enregistré dans:
Format: Online
Langue:anglais
Publié: MDPI - Multidisciplinary Digital Publishing Institute 2021
Sujets:
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
thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
Accès en ligne:ONIX_20210501_9783039433223_1028
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