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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

Technology: general issues --- 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

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

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

Technology: general issues --- 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 --- 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