Remote Sensing in Mangroves
The book highlights recent advancements in the mapping and monitoring of mangrove forests using earth observation satellite data. New and historical satellite data and aerial photographs have been used to map the extent, change and bio-physical parameters, such as phenology and biomass. Research was...
Đã lưu trong:
| Định dạng: | Online |
|---|---|
| Ngôn ngữ: | Tiếng Anh |
| Được phát hành: |
MDPI - Multidisciplinary Digital Publishing Institute
2022
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| Những chủ đề: | |
| Truy cập trực tuyến: | ONIX_20220111_9783036508504_278 |
| Các nhãn: |
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| _version_ | 1869528932156440576 |
|---|---|
| collection | Directory of Open Access Books |
| description | The book highlights recent advancements in the mapping and monitoring of mangrove forests using earth observation satellite data. New and historical satellite data and aerial photographs have been used to map the extent, change and bio-physical parameters, such as phenology and biomass. Research was conducted in different parts of the world. Knowledge and understanding gained from this book can be used for the sustainable management of mangrove forests of the world |
| format | Online |
| id | doab-20.500.12854ir-76542 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-765422024-04-09T23:15:44Z Remote Sensing in Mangroves Giri, Chandra Landsat estuary protected area land use land cover change detection time series Great Barrier Reef Sentinel-2 ALOS-2 PALSAR-2 mangrove above-ground biomass extreme gradient boosting Can Gio biosphere reserve Vietnam LiDAR random forest GLAS aboveground biomass mangrove plantation aboveground biomass estimation optical images SAR DSM vegetation index color RGB accuracy assessment transgression mangrove development machine learning mangrove condition classification remote sensing ecosystem upscaling Worldview-2 Niger Delta Region mangroves land cover dynamics intensity analysis fragmentation spectral-temporal metrics land degradation ALOS PALSAR-2 JERS-1 GLCM Markov chain cellular automata data fusion forest monitoring Google Earth Engine mangrove forests multi-temporal analysis satellite earth observation time series analysis GEEMMM google earth engine Myanmar cloud computing digital earth GAMs Generalized Additive Models EVI phenology n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues The book highlights recent advancements in the mapping and monitoring of mangrove forests using earth observation satellite data. New and historical satellite data and aerial photographs have been used to map the extent, change and bio-physical parameters, such as phenology and biomass. Research was conducted in different parts of the world. Knowledge and understanding gained from this book can be used for the sustainable management of mangrove forests of the world 2022-01-11T13:35:05Z 2022-01-11T13:35:05Z 2021 book ONIX_20220111_9783036508504_278 9783036508504 9783036508511 https://directory.doabooks.org/handle/20.500.12854/76542 eng image/jpeg Attribution 4.0 International https://mdpi.com/books/pdfview/book/3988 https://mdpi.com/books/pdfview/book/3988 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-0851-1 10.3390/books978-3-0365-0851-1 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036508504 9783036508511 292 Basel, Switzerland open access |
| spellingShingle | Landsat estuary protected area land use land cover change detection time series Great Barrier Reef Sentinel-2 ALOS-2 PALSAR-2 mangrove above-ground biomass extreme gradient boosting Can Gio biosphere reserve Vietnam LiDAR random forest GLAS aboveground biomass mangrove plantation aboveground biomass estimation optical images SAR DSM vegetation index color RGB accuracy assessment transgression mangrove development machine learning mangrove condition classification remote sensing ecosystem upscaling Worldview-2 Niger Delta Region mangroves land cover dynamics intensity analysis fragmentation spectral-temporal metrics land degradation ALOS PALSAR-2 JERS-1 GLCM Markov chain cellular automata data fusion forest monitoring Google Earth Engine mangrove forests multi-temporal analysis satellite earth observation time series analysis GEEMMM google earth engine Myanmar cloud computing digital earth GAMs Generalized Additive Models EVI phenology n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues Remote Sensing in Mangroves |
| title | Remote Sensing in Mangroves |
| title_full | Remote Sensing in Mangroves |
| title_fullStr | Remote Sensing in Mangroves |
| title_full_unstemmed | Remote Sensing in Mangroves |
| title_short | Remote Sensing in Mangroves |
| title_sort | remote sensing in mangroves |
| topic | Landsat estuary protected area land use land cover change detection time series Great Barrier Reef Sentinel-2 ALOS-2 PALSAR-2 mangrove above-ground biomass extreme gradient boosting Can Gio biosphere reserve Vietnam LiDAR random forest GLAS aboveground biomass mangrove plantation aboveground biomass estimation optical images SAR DSM vegetation index color RGB accuracy assessment transgression mangrove development machine learning mangrove condition classification remote sensing ecosystem upscaling Worldview-2 Niger Delta Region mangroves land cover dynamics intensity analysis fragmentation spectral-temporal metrics land degradation ALOS PALSAR-2 JERS-1 GLCM Markov chain cellular automata data fusion forest monitoring Google Earth Engine mangrove forests multi-temporal analysis satellite earth observation time series analysis GEEMMM google earth engine Myanmar cloud computing digital earth GAMs Generalized Additive Models EVI phenology n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues |
| topic_facet | Landsat estuary protected area land use land cover change detection time series Great Barrier Reef Sentinel-2 ALOS-2 PALSAR-2 mangrove above-ground biomass extreme gradient boosting Can Gio biosphere reserve Vietnam LiDAR random forest GLAS aboveground biomass mangrove plantation aboveground biomass estimation optical images SAR DSM vegetation index color RGB accuracy assessment transgression mangrove development machine learning mangrove condition classification remote sensing ecosystem upscaling Worldview-2 Niger Delta Region mangroves land cover dynamics intensity analysis fragmentation spectral-temporal metrics land degradation ALOS PALSAR-2 JERS-1 GLCM Markov chain cellular automata data fusion forest monitoring Google Earth Engine mangrove forests multi-temporal analysis satellite earth observation time series analysis GEEMMM google earth engine Myanmar cloud computing digital earth GAMs Generalized Additive Models EVI phenology n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues |
| url | ONIX_20220111_9783036508504_278 |