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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| Formato: | Online |
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| Idioma: | inglés |
| Publicado: |
2022
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| Subjects: | |
| Acceso en liña: | ONIX_20220916_9783036543086_32 |
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Sen Etiquetas, Sexa o primeiro en etiquetar este rexistro!
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| _version_ | 1869521642724524032 |
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| collection | Directory of Open Access Books |
| description | 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. |
| format | Online |
| id | doab-20.500.12854ir-92046 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| record_format | ojs |
| spelling | doab-20.500.12854ir-920462024-03-28T03:31:35Z Remote Sensing of Natural Hazards Ahmed, Bayes Alam, Akhtar 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 thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography 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. 2022-09-16T13:46:07Z 2022-09-16T13:46:07Z 2022 book ONIX_20220916_9783036543086_32 9783036543086 9783036543079 https://directory.doabooks.org/handle/20.500.12854/92046 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/5919 https://mdpi.com/books/pdfview/book/5919 10.3390/books978-3-0365-4307-9 10.3390/books978-3-0365-4307-9 MDPI - Multidisciplinary Digital Publishing Institute 9783036543086 9783036543079 314 Basel open access |
| spellingShingle | 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 thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography Remote Sensing of Natural Hazards |
| title | 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_short | Remote Sensing of Natural Hazards |
| title_sort | remote sensing of natural hazards |
| topic | 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 thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography |
| topic_facet | 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 thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography |
| url | ONIX_20220916_9783036543086_32 |