Remote Sensing Technology Applications in Forestry and REDD+
Vastaranta, Mikko
Remote Sensing Technology Applications in Forestry and REDD+ - MDPI - Multidisciplinary Digital Publishing Institute 2020 - 1 electronic resource (244 p.)
Open Access
Advances in close-range and remote sensing technologies are driving innovations in forest resource assessments and monitoring on varying scales. Data acquired with airborne and spaceborne platforms provide high(er) spatial resolution, more frequent coverage, and more spectral information. Recent developments in ground-based sensors have advanced 3D measurements, low-cost permanent systems, and community-based monitoring of forests. The UNFCCC REDD+ mechanism has advanced the remote sensing community and the development of forest geospatial products that can be used by countries for the international reporting and national forest monitoring. However, an urgent need remains to better understand the options and limitations of remote and close-range sensing techniques in the field of forest degradation and forest change. Therefore, we invite scientists working on remote sensing technologies, close-range sensing, and field data to contribute to this Special Issue. Topics of interest include: (1) novel remote sensing applications that can meet the needs of forest resource information and REDD+ MRV, (2) case studies of applying remote sensing data for REDD+ MRV, (3) timeseries algorithms and methodologies for forest resource assessment on different spatial scales varying from the tree to the national level, and (4) novel close-range sensing applications that can support sustainable forestry and REDD+ MRV. We particularly welcome submissions on data fusion.
Creative Commons
English
books978-3-03928-471-9 9783039284702 9783039284719
10.3390/books978-3-03928-471-9 doi
spectral Cameroon quantitative structural model digital hemispherical photograph (DHP) environment effects human activity reference level terrestrial laser scanning topographic effects Guyana predictive mapping aboveground biomass estimation geographic information system Pinus massoniana 3D tree modelling ensemble model destructive sampling model comparison topography remote sensing forest growing stock volume (GSV) local tree allometry tree mapping gray level co-occurrence matrix (GLCM) deforestation REDD+ sentinel imagery geographically weighted regression aboveground biomass random forest random forest (RF) silviculture agriculture crown density hazard mapping model evaluation old-growth forest full polarimetric SAR subtropical forest forest canopy forest classification low-accuracy estimation texture LiDAR Landsat phenology airborne laser scanning tall trees machine learning forest baseline overstory trees support vector machine above-ground biomass multispectral satellite imagery crown delineation specific leaf area forest inventory canopy cover (CC) voxelization forestry leaf area
Remote Sensing Technology Applications in Forestry and REDD+ - MDPI - Multidisciplinary Digital Publishing Institute 2020 - 1 electronic resource (244 p.)
Open Access
Advances in close-range and remote sensing technologies are driving innovations in forest resource assessments and monitoring on varying scales. Data acquired with airborne and spaceborne platforms provide high(er) spatial resolution, more frequent coverage, and more spectral information. Recent developments in ground-based sensors have advanced 3D measurements, low-cost permanent systems, and community-based monitoring of forests. The UNFCCC REDD+ mechanism has advanced the remote sensing community and the development of forest geospatial products that can be used by countries for the international reporting and national forest monitoring. However, an urgent need remains to better understand the options and limitations of remote and close-range sensing techniques in the field of forest degradation and forest change. Therefore, we invite scientists working on remote sensing technologies, close-range sensing, and field data to contribute to this Special Issue. Topics of interest include: (1) novel remote sensing applications that can meet the needs of forest resource information and REDD+ MRV, (2) case studies of applying remote sensing data for REDD+ MRV, (3) timeseries algorithms and methodologies for forest resource assessment on different spatial scales varying from the tree to the national level, and (4) novel close-range sensing applications that can support sustainable forestry and REDD+ MRV. We particularly welcome submissions on data fusion.
Creative Commons
English
books978-3-03928-471-9 9783039284702 9783039284719
10.3390/books978-3-03928-471-9 doi
spectral Cameroon quantitative structural model digital hemispherical photograph (DHP) environment effects human activity reference level terrestrial laser scanning topographic effects Guyana predictive mapping aboveground biomass estimation geographic information system Pinus massoniana 3D tree modelling ensemble model destructive sampling model comparison topography remote sensing forest growing stock volume (GSV) local tree allometry tree mapping gray level co-occurrence matrix (GLCM) deforestation REDD+ sentinel imagery geographically weighted regression aboveground biomass random forest random forest (RF) silviculture agriculture crown density hazard mapping model evaluation old-growth forest full polarimetric SAR subtropical forest forest canopy forest classification low-accuracy estimation texture LiDAR Landsat phenology airborne laser scanning tall trees machine learning forest baseline overstory trees support vector machine above-ground biomass multispectral satellite imagery crown delineation specific leaf area forest inventory canopy cover (CC) voxelization forestry leaf area