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...

Full description

Saved in:
Bibliographic Details
HerausgeberIn:
Sonstige:
Year of Publication:2022
Language:English
Physical Description:1 electronic resource (314 p.)
Tags: Add Tag
No Tags, Be the first to tag this record!
LEADER 04607nam-a2201129z--4500
001 993560436704498
005 20231214133144.0
006 m o d
007 cr|mn|---annan
008 202209s2022 xx |||||o ||| 0|eng d
035 |a (CKB)5680000000080829 
035 |a (oapen)https://directory.doabooks.org/handle/20.500.12854/92046 
035 |a (EXLCZ)995680000000080829 
041 0 |a eng 
100 1 |a Ahmed, Bayes  |4 edt 
245 1 0 |a Remote Sensing of Natural Hazards 
260 |a Basel  |b MDPI Books  |c 2022 
300 |a 1 electronic resource (314 p.) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
520 |a 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. 
546 |a English 
650 7 |a Research & information: general  |2 bicssc 
650 7 |a Geography  |2 bicssc 
653 |a sequential estimation 
653 |a InSAR time series 
653 |a groundwater 
653 |a land subsidence and rebound 
653 |a earthquake 
653 |a rapid mapping 
653 |a damage assessment 
653 |a deep learning 
653 |a convolutional neural networks 
653 |a ordinal regression 
653 |a aerial image 
653 |a landslide 
653 |a machine learning models 
653 |a remote sensing 
653 |a ensemble models 
653 |a validation 
653 |a ice storm 
653 |a forest ecosystems 
653 |a disaster impact 
653 |a post-disaster recovery 
653 |a ice jam 
653 |a snowmelt 
653 |a flood mapping 
653 |a monitoring and prediction 
653 |a VIIRS 
653 |a ABI 
653 |a NUAE 
653 |a flash flood 
653 |a BRT 
653 |a CART 
653 |a naive Bayes tree 
653 |a geohydrological model 
653 |a landslide susceptibility 
653 |a Bangladesh 
653 |a digital elevation model 
653 |a random forest 
653 |a modified frequency ratio 
653 |a logistic regression 
653 |a automatic landslide detection 
653 |a OBIA 
653 |a PBA 
653 |a random forests 
653 |a supervised classification 
653 |a landslides 
653 |a uncertainty 
653 |a K-Nearest Neighbor 
653 |a Multi-Layer Perceptron 
653 |a Random Forest 
653 |a Support Vector Machine 
653 |a agriculture 
653 |a drought 
653 |a NDVI 
653 |a MODIS 
653 |a landslide deformation 
653 |a InSAR 
653 |a reservoir water level 
653 |a Sentinel-1 
653 |a Three Gorges Reservoir area (China) 
653 |a peri-urbanization 
653 |a urban growth boundary demarcation 
653 |a climate change 
653 |a climate migrants 
653 |a natural hazards 
653 |a flooding 
653 |a land use and land cover 
653 |a night-time light data 
653 |a Dhaka 
776 |z 3-0365-4308-2 
776 |z 3-0365-4307-4 
700 1 |a Alam, Akhtar  |4 edt 
700 1 |a Ahmed, Bayes  |4 oth 
700 1 |a Alam, Akhtar  |4 oth 
906 |a BOOK 
ADM |b 2023-12-15 05:44:30 Europe/Vienna  |f system  |c marc21  |a 2022-09-22 08:09:39 Europe/Vienna  |g false 
AVE |i DOAB Directory of Open Access Books  |P DOAB Directory of Open Access Books  |x https://eu02.alma.exlibrisgroup.com/view/uresolver/43ACC_OEAW/openurl?u.ignore_date_coverage=true&portfolio_pid=5340300400004498&Force_direct=true  |Z 5340300400004498  |b Available  |8 5340300400004498