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This Special Issue (SI), entitled "Applications of Remote Sensing Data in Mapping of Forest Growing Stock and Biomass”, resulted from 13 peer-reviewed papers dedicated to Forestry and Biomass mapping, characterization and accounting. The papers' authors presented improvements in Remote Sensing processing techniques on satellite images, drone-acquired images and LiDAR images, both aerial and terrestrial. Regarding the images’ classification models, all authors presented supervised methods, such as Random Forest, complemented by GIS routines and biophysical variables measured on the field, which were properly georeferenced. The achieved results enable the statement that remote imagery could be successfully used as a data source for regression analysis and formulation and, in this way, used in forestry actions such as canopy structure analysis and mapping, or to estimate biomass. This collection of papers, presented in the form of a book, brings together 13 articles covering various forest issues and issues in forest biomass calculation, constituting an important work manual for those who use mixed GIS and RS techniques.
AGB estimation and mapping --- mangroves --- UAV LiDAR --- WorldView-2 --- terrestrial laser scanning --- above-ground biomass --- nondestructive method --- DBH --- bark roughness --- Landsat dataset --- forest AGC estimation --- random forest --- spatiotemporal evolution --- aboveground biomass --- variable selection --- forest type --- machine learning --- subtropical forests --- Landsat 8 OLI --- seasonal images --- stepwise regression --- map quality --- subtropical forest --- urban vegetation --- biomass estimation --- Sentinel-2A --- Xuzhou --- forest biomass estimation --- forest inventory data --- multisource remote sensing --- biomass density --- ecosystem services --- trade-off --- synergy --- multiple ES interactions --- valley basin --- norway spruce --- LiDAR --- allometric equation --- individual tree detection --- tree height --- diameter at breast height --- GEOMON --- ALOS-2 L band SAR --- Sentinel-1 C band SAR --- Sentinel-2 MSI --- ALOS DSM --- stand volume --- support vector machine for regression --- ordinary kriging --- forest succession --- leaf area index --- plant area index --- machine learning algorithms --- forest growing stock volume --- SPOT6 imagery --- Pinus massoniana plantations --- sentinel 2 --- landsat --- remote sensing --- GIS --- shrubs biomass --- bioenergy --- vegetation indices
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Around 10% of the global population lives in the world’s coastal zones, mostly concentrated in the world’s largest megacities. In many regions, the population is exposed to a variety of natural hazards and space-based observations. This Special Issue will focus on the usage of remote sensing alone or in synergy with in situ measurments and modeling tools to provide precise and systematic information about processes acting in the world’s coastal zones.
ACOLITE --- coastal waters --- atmospheric correction --- time-series --- management --- Sentinel-2 --- radon transform --- remote sensing --- bathymetry inversion --- multi-scale monitoring --- image augmentation --- phytoplankton remote sensing --- coastal ocean --- red tides --- black pixel assumption --- satellite --- sediment transport --- coastal geomorphology --- ocean color --- GOCI --- VIIRS --- turbid waters --- satellite-derived bathymetry --- Copernicus programme --- multi-temporal approach --- lidar --- turbidity --- coastal upwelling --- wind forcing --- river plume --- MODIS --- Arctic Ocean --- hurricanes --- water quality --- Puerto Rico --- harmful algal blooms --- Chattonella spp. --- Skeletonema spp. --- backscattering --- Ariake Sea --- chlorophyll-a variability --- spring–neap tides --- MODIS-Aqua --- total suspended sediment --- river discharge --- band registration --- morphological registration --- multispectral camera --- Micasense Rededge-M --- Pearl River estuary --- diffuse attenuation coefficient --- S-EOF --- land subsidence --- multi-temporal SAR interferometry --- sea-surface height --- relative sea level change --- satellite altimetry data --- GNSS --- coastal urban centers --- natural protected areas --- climate change impact --- physics-based inversion method --- ocean surface circulation --- high frequency radar --- self-organizing map --- empirical orthogonal function --- neural networks --- synoptic characteristics --- wave radar --- sea waves --- model data --- Mediterranean sea --- small river plume --- aerial drone --- coastal processes --- frontal zones --- internal waves --- along-track interferometric synthetic aperture radar (ATI-SAR) --- current line-of-sight (LOS) velocity --- azimuth ambiguity --- baseline-to-platform speed ratio estimation --- storm surge --- coastal flooding --- marine storms --- natural hazards --- steric-effect --- satellite altimetry --- ADG/CDOM colored dissolved organic matter --- Sentinel 3 --- southwestern Puerto Rico --- ocean tidal backwater --- stage–discharge relation --- ocean tide model --- Mekong Delta --- suspended particulate matter --- ocean color data --- satellite remote sensing --- in situ measurements --- C2RCC --- Landsat-8 OLI --- Sentinel-2 MSI --- Mzymta River --- Black Sea --- MUR SST --- SST fronts --- Inner Sea of Chiloé --- northern Patagonia --- suspended sediment --- Typhoon Soudelor --- spatial–temporal distribution --- HF marine radars --- wave energy
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