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...

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Bibliographic Details
Other Authors: Giri, Chandra (Editor)
Format: Book Chapter
Published: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
Subjects:
Online Access:Get Fullteks
DOAB: description of the publication
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100 1 |a Giri, Chandra  |4 edt 
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245 1 0 |a Remote Sensing in Mangroves 
260 |a Basel, Switzerland  |b MDPI - Multidisciplinary Digital Publishing Institute  |c 2021 
300 |a 1 electronic resource (292 p.) 
506 0 |a Open Access  |2 star  |f Unrestricted online access 
520 |a 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 
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546 |a English 
650 7 |a Technology: general issues  |2 bicssc 
653 |a Landsat 
653 |a estuary 
653 |a protected area 
653 |a land use 
653 |a land cover 
653 |a change detection 
653 |a time series 
653 |a Great Barrier Reef 
653 |a Sentinel-2 
653 |a ALOS-2 PALSAR-2 
653 |a mangrove 
653 |a above-ground biomass 
653 |a extreme gradient boosting 
653 |a Can Gio biosphere reserve 
653 |a Vietnam 
653 |a LiDAR 
653 |a random forest 
653 |a GLAS 
653 |a aboveground biomass 
653 |a mangrove plantation 
653 |a aboveground biomass estimation 
653 |a optical images 
653 |a SAR 
653 |a DSM 
653 |a vegetation index 
653 |a color 
653 |a RGB 
653 |a accuracy assessment 
653 |a transgression 
653 |a mangrove development 
653 |a machine learning 
653 |a mangrove condition 
653 |a classification 
653 |a remote sensing 
653 |a ecosystem 
653 |a upscaling 
653 |a Worldview-2 
653 |a Niger Delta Region 
653 |a mangroves 
653 |a land cover dynamics 
653 |a intensity analysis 
653 |a fragmentation 
653 |a spectral-temporal metrics 
653 |a land degradation 
653 |a ALOS PALSAR-2 
653 |a JERS-1 
653 |a GLCM 
653 |a Markov chain 
653 |a cellular automata 
653 |a data fusion 
653 |a forest monitoring 
653 |a Google Earth Engine 
653 |a mangrove forests 
653 |a multi-temporal analysis 
653 |a satellite earth observation 
653 |a time series analysis 
653 |a GEEMMM 
653 |a google earth engine 
653 |a Myanmar 
653 |a cloud computing 
653 |a digital earth 
653 |a GAMs 
653 |a Generalized Additive Models 
653 |a EVI 
653 |a phenology 
653 |a n/a 
856 4 0 |a www.oapen.org  |u https://mdpi.com/books/pdfview/book/3988  |7 0  |z Get Fullteks 
856 4 0 |a www.oapen.org  |u https://directory.doabooks.org/handle/20.500.12854/76542  |7 0  |z DOAB: description of the publication