TY  - GEN
AU  - Vastaranta,Mikko
AU  - Calders,Kim
AU  - Jonckheere,Inge
AU  - Nightingale,Joanne
TI  - Remote Sensing Technology Applications in Forestry and REDD+
SN  - books978-3-03928-471-9
PY  - 2020///
PB  - MDPI - Multidisciplinary Digital Publishing Institute
KW  - spectral
KW  - Cameroon
KW  - quantitative structural model
KW  - digital hemispherical photograph (DHP)
KW  - environment effects
KW  - human activity
KW  - reference level
KW  - terrestrial laser scanning
KW  - topographic effects
KW  - Guyana
KW  - predictive mapping
KW  - aboveground biomass estimation
KW  - geographic information system
KW  - Pinus massoniana
KW  - 3D tree modelling
KW  - ensemble model
KW  - destructive sampling
KW  - model comparison
KW  - topography
KW  - remote sensing
KW  - forest growing stock volume (GSV)
KW  - local tree allometry
KW  - tree mapping
KW  - gray level co-occurrence matrix (GLCM)
KW  - deforestation
KW  - REDD+
KW  - sentinel imagery
KW  - geographically weighted regression
KW  - aboveground biomass
KW  - random forest
KW  - random forest (RF)
KW  - silviculture
KW  - agriculture
KW  - crown density
KW  - hazard mapping
KW  - model evaluation
KW  - old-growth forest
KW  - full polarimetric SAR
KW  - subtropical forest
KW  - forest canopy
KW  - forest classification
KW  - low-accuracy estimation
KW  - texture
KW  - LiDAR
KW  - Landsat
KW  - phenology
KW  - airborne laser scanning
KW  - tall trees
KW  - machine learning
KW  - forest baseline
KW  - overstory trees
KW  - support vector machine
KW  - above-ground biomass
KW  - multispectral satellite imagery
KW  - crown delineation
KW  - specific leaf area
KW  - forest inventory
KW  - canopy cover (CC)
KW  - voxelization
KW  - forestry
KW  - leaf area
N1  - Open Access
N2  - 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
UR  - https://mdpi.com/books/pdfview/book/2103
UR  - https://directory.doabooks.org/handle/20.500.12854/58179
ER  -