TY - BOOK ID - 44826 TI - Remote Sensing Technology Applications in Forestry and REDD+ AU - Calders, Kim AU - Jonckheere, Inge AU - Vastaranta, Mikko AU - Nightingale, Joanne PY - 2020 SN - 9783039284702 9783039284719 DB - DOAB KW - sentinel imagery KW - above-ground biomass KW - predictive mapping KW - machine learning KW - geographically weighted regression KW - canopy cover (CC) KW - spectral KW - texture KW - digital hemispherical photograph (DHP) KW - random forest (RF) KW - gray level co-occurrence matrix (GLCM) KW - forest inventory KW - LiDAR KW - tall trees KW - overstory trees KW - tree mapping KW - crown delineation KW - aboveground biomass KW - Landsat KW - random forest KW - topography KW - human activity KW - aboveground biomass estimation KW - remote sensing KW - crown density KW - low-accuracy estimation KW - model comparison KW - old-growth forest KW - multispectral satellite imagery KW - random forest KW - forest classification KW - remote sensing KW - forestry KW - phenology KW - silviculture KW - forest growing stock volume (GSV) KW - full polarimetric SAR KW - subtropical forest KW - topographic effects KW - environment effects KW - geographic information system KW - support vector machine KW - random forest KW - ensemble model KW - hazard mapping KW - 3D tree modelling KW - aboveground biomass estimation KW - destructive sampling KW - Guyana KW - LiDAR KW - local tree allometry KW - model evaluation KW - quantitative structural model KW - Pinus massoniana KW - specific leaf area KW - leaf area KW - terrestrial laser scanning KW - voxelization KW - forest canopy KW - REDD+ KW - Cameroon KW - reference level KW - deforestation KW - agriculture KW - forest baseline KW - airborne laser scanning KW - terrestrial laser scanning KW - remote sensing KW - REDD+ KW - forestry UR - https://www.doabooks.org/doab?func=search&query=rid:44826 AB - 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. ER -