Remote Sensing in Mangroves II
Mangrove forests are in constant flux due to both natural and anthropogenic forces. The changing mangroves will have significant consequences to coastal communities. Observation and monitoring of the distribution and dynamics of mangroves is central to a wide range of scientific investigations condu...
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| Format: | Online |
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| Language: | English |
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MDPI - Multidisciplinary Digital Publishing Institute
2023
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| Online Access: | ONIX_20231130_9783036588865_11 |
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| collection | Directory of Open Access Books |
| description | Mangrove forests are in constant flux due to both natural and anthropogenic forces. The changing mangroves will have significant consequences to coastal communities. Observation and monitoring of the distribution and dynamics of mangroves is central to a wide range of scientific investigations conducted in both terrestrial and marine ecosystems. Recent advancements in remote sensing data availability, image-processing methodologies, computing and information technology, and human resource development have provided an opportunity to observe and monitor mangroves from local to global scales on a regular basis. The spectral, spatial, and temporal resolution of remote sensing data and their availability have improved, making it possible to observe and monitor mangroves with unprecedented spatial thematic and temporal details. This journal Remote Sensing Special Issue reprint dedicated to the observation and monitoring of mangroves using remote sensing from local to global scales. The Issue broadly covers the application of remote sensing using optical (multi-spectral and hyperspectral), radar, and Lidar data obtained from multiple platforms including ground, air, and space. The research papers published use the latest techniques to acquire, manage, exploit, process, and analyze a wide variety of remote sensing data for mangrove forest applications. Both research papers and innovative review papers are included. |
| format | Online |
| id | doab-20.500.12854ir-128559 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1285592024-03-28T03:31:02Z Remote Sensing in Mangroves II Giri, Chandra mangrove natural recovery artificial neural network Sentinel-2 transfer learning change detection coastal region remote sensing fragmentation productivity land cover change mangrove ecosystem random forest (RF) Google Earth Engine (GEE) Sentinel synthetic aperture radar (SAR) optical aerial roots global sensitivity analysis PAWN canopy reflectance model vegetation index (VI) mangroves Landsat mangrove forests time series Google Earth Engine random forests phenology TIMESAT climate monitoring Great Barrier Reef Hainan Island CLUE-S spatio-temporal simulation future change trends mangrove species spectrometer spectral reflectance WorldView-2 dendrogram extent mapping sentinel-2 global mangrove watch remote sensing-based monitoring plantation restoration dieback Bay of Bengal Red River Delta Vietnam vegetation index mangrove index mangrove forest mangrove above ground biomass carbon sink bibliometric analysis Sembilang National Park (Indonesia) machine learning satellites images geoprocessing rehabilitation program of mangroves n/a thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science::PS Biology, life sciences thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNA Agribusiness and primary industries::KNAL Forestry industry Mangrove forests are in constant flux due to both natural and anthropogenic forces. The changing mangroves will have significant consequences to coastal communities. Observation and monitoring of the distribution and dynamics of mangroves is central to a wide range of scientific investigations conducted in both terrestrial and marine ecosystems. Recent advancements in remote sensing data availability, image-processing methodologies, computing and information technology, and human resource development have provided an opportunity to observe and monitor mangroves from local to global scales on a regular basis. The spectral, spatial, and temporal resolution of remote sensing data and their availability have improved, making it possible to observe and monitor mangroves with unprecedented spatial thematic and temporal details. This journal Remote Sensing Special Issue reprint dedicated to the observation and monitoring of mangroves using remote sensing from local to global scales. The Issue broadly covers the application of remote sensing using optical (multi-spectral and hyperspectral), radar, and Lidar data obtained from multiple platforms including ground, air, and space. The research papers published use the latest techniques to acquire, manage, exploit, process, and analyze a wide variety of remote sensing data for mangrove forest applications. Both research papers and innovative review papers are included. 2023-11-30T20:31:40Z 2023-11-30T20:31:40Z 2023 book ONIX_20231130_9783036588865_11 9783036588865 9783036588872 https://directory.doabooks.org/handle/20.500.12854/128559 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/8008 https://mdpi.com/books/pdfview/book/8008 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-8887-2 10.3390/books978-3-0365-8887-2 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036588865 9783036588872 268 Basel open access |
| spellingShingle | mangrove natural recovery artificial neural network Sentinel-2 transfer learning change detection coastal region remote sensing fragmentation productivity land cover change mangrove ecosystem random forest (RF) Google Earth Engine (GEE) Sentinel synthetic aperture radar (SAR) optical aerial roots global sensitivity analysis PAWN canopy reflectance model vegetation index (VI) mangroves Landsat mangrove forests time series Google Earth Engine random forests phenology TIMESAT climate monitoring Great Barrier Reef Hainan Island CLUE-S spatio-temporal simulation future change trends mangrove species spectrometer spectral reflectance WorldView-2 dendrogram extent mapping sentinel-2 global mangrove watch remote sensing-based monitoring plantation restoration dieback Bay of Bengal Red River Delta Vietnam vegetation index mangrove index mangrove forest mangrove above ground biomass carbon sink bibliometric analysis Sembilang National Park (Indonesia) machine learning satellites images geoprocessing rehabilitation program of mangroves n/a thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science::PS Biology, life sciences thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNA Agribusiness and primary industries::KNAL Forestry industry Remote Sensing in Mangroves II |
| title | Remote Sensing in Mangroves II |
| title_full | Remote Sensing in Mangroves II |
| title_fullStr | Remote Sensing in Mangroves II |
| title_full_unstemmed | Remote Sensing in Mangroves II |
| title_short | Remote Sensing in Mangroves II |
| title_sort | remote sensing in mangroves ii |
| topic | mangrove natural recovery artificial neural network Sentinel-2 transfer learning change detection coastal region remote sensing fragmentation productivity land cover change mangrove ecosystem random forest (RF) Google Earth Engine (GEE) Sentinel synthetic aperture radar (SAR) optical aerial roots global sensitivity analysis PAWN canopy reflectance model vegetation index (VI) mangroves Landsat mangrove forests time series Google Earth Engine random forests phenology TIMESAT climate monitoring Great Barrier Reef Hainan Island CLUE-S spatio-temporal simulation future change trends mangrove species spectrometer spectral reflectance WorldView-2 dendrogram extent mapping sentinel-2 global mangrove watch remote sensing-based monitoring plantation restoration dieback Bay of Bengal Red River Delta Vietnam vegetation index mangrove index mangrove forest mangrove above ground biomass carbon sink bibliometric analysis Sembilang National Park (Indonesia) machine learning satellites images geoprocessing rehabilitation program of mangroves n/a thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science::PS Biology, life sciences thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNA Agribusiness and primary industries::KNAL Forestry industry |
| topic_facet | mangrove natural recovery artificial neural network Sentinel-2 transfer learning change detection coastal region remote sensing fragmentation productivity land cover change mangrove ecosystem random forest (RF) Google Earth Engine (GEE) Sentinel synthetic aperture radar (SAR) optical aerial roots global sensitivity analysis PAWN canopy reflectance model vegetation index (VI) mangroves Landsat mangrove forests time series Google Earth Engine random forests phenology TIMESAT climate monitoring Great Barrier Reef Hainan Island CLUE-S spatio-temporal simulation future change trends mangrove species spectrometer spectral reflectance WorldView-2 dendrogram extent mapping sentinel-2 global mangrove watch remote sensing-based monitoring plantation restoration dieback Bay of Bengal Red River Delta Vietnam vegetation index mangrove index mangrove forest mangrove above ground biomass carbon sink bibliometric analysis Sembilang National Park (Indonesia) machine learning satellites images geoprocessing rehabilitation program of mangroves n/a thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science::PS Biology, life sciences thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNA Agribusiness and primary industries::KNAL Forestry industry |
| url | ONIX_20231130_9783036588865_11 |