Remote Sensing of Natural Hazards

Each year, natural hazards such as earthquakes, cyclones, flooding, landslides, wildfires, avalanches, volcanic eruption, extreme temperatures, storm surges, drought, etc., result in widespread loss of life, livelihood, and critical infrastructure globally. With the unprecedented growth of the human...

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Year of Publication:2022
Language:English
Physical Description:1 electronic resource (314 p.)
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(oapen)https://directory.doabooks.org/handle/20.500.12854/92046
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spelling Ahmed, Bayes edt
Remote Sensing of Natural Hazards
Basel MDPI Books 2022
1 electronic resource (314 p.)
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
Each year, natural hazards such as earthquakes, cyclones, flooding, landslides, wildfires, avalanches, volcanic eruption, extreme temperatures, storm surges, drought, etc., result in widespread loss of life, livelihood, and critical infrastructure globally. With the unprecedented growth of the human population, largescale development activities, and changes to the natural environment, the frequency and intensity of extreme natural events and consequent impacts are expected to increase in the future.Technological interventions provide essential provisions for the prevention and mitigation of natural hazards. The data obtained through remote sensing systems with varied spatial, spectral, and temporal resolutions particularly provide prospects for furthering knowledge on spatiotemporal patterns and forecasting of natural hazards. The collection of data using earth observation systems has been valuable for alleviating the adverse effects of natural hazards, especially with their near real-time capabilities for tracking extreme natural events. Remote sensing systems from different platforms also serve as an important decision-support tool for devising response strategies, coordinating rescue operations, and making damage and loss estimations.With these in mind, this book seeks original contributions to the advanced applications of remote sensing and geographic information systems (GIS) techniques in understanding various dimensions of natural hazards through new theory, data products, and robust approaches.
English
Research & information: general bicssc
Geography bicssc
sequential estimation
InSAR time series
groundwater
land subsidence and rebound
earthquake
rapid mapping
damage assessment
deep learning
convolutional neural networks
ordinal regression
aerial image
landslide
machine learning models
remote sensing
ensemble models
validation
ice storm
forest ecosystems
disaster impact
post-disaster recovery
ice jam
snowmelt
flood mapping
monitoring and prediction
VIIRS
ABI
NUAE
flash flood
BRT
CART
naive Bayes tree
geohydrological model
landslide susceptibility
Bangladesh
digital elevation model
random forest
modified frequency ratio
logistic regression
automatic landslide detection
OBIA
PBA
random forests
supervised classification
landslides
uncertainty
K-Nearest Neighbor
Multi-Layer Perceptron
Random Forest
Support Vector Machine
agriculture
drought
NDVI
MODIS
landslide deformation
InSAR
reservoir water level
Sentinel-1
Three Gorges Reservoir area (China)
peri-urbanization
urban growth boundary demarcation
climate change
climate migrants
natural hazards
flooding
land use and land cover
night-time light data
Dhaka
3-0365-4308-2
3-0365-4307-4
Alam, Akhtar edt
Ahmed, Bayes oth
Alam, Akhtar oth
language English
format eBook
author2 Alam, Akhtar
Ahmed, Bayes
Alam, Akhtar
author_facet Alam, Akhtar
Ahmed, Bayes
Alam, Akhtar
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author2_role HerausgeberIn
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title Remote Sensing of Natural Hazards
spellingShingle Remote Sensing of Natural Hazards
title_full Remote Sensing of Natural Hazards
title_fullStr Remote Sensing of Natural Hazards
title_full_unstemmed Remote Sensing of Natural Hazards
title_auth Remote Sensing of Natural Hazards
title_new Remote Sensing of Natural Hazards
title_sort remote sensing of natural hazards
publisher MDPI Books
publishDate 2022
physical 1 electronic resource (314 p.)
isbn 3-0365-4308-2
3-0365-4307-4
illustrated Not Illustrated
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