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Forest ecosystems are often disturbed by agents such as harvesting, fire, wind, insects and diseases, and acid deposition, with differing intensities and frequencies. Such disturbances can markedly affect the amount, form, and stability of soil organic carbon in, and the emission of greenhouse gases, including CO2, CH4, and N2O from, forest ecosystems. It is vitally important that we improve our understanding of the impact of different disturbance regimes on forest soil carbon dynamics and greenhouse gas emissions to guide our future research, forest management practices, and policy development. This Special Issue provides an important update on the disturbance effects on soil carbon and greenhouse gas emissions in forest ecosystems in different climate regions.

greenhouse gas emission --- heterotrophic respiration --- Camellia oleifera --- Larix principis-rupprechtii Mayr --- soil microbial residue --- assisted natural regeneration --- soil organic carbon --- soil carbon sequestration --- soil CO2 --- surface soil layer --- landform --- anthropogenic effect --- South Korea --- CO2 effluxes --- storm damage --- microbial properties --- calcareous soil --- land use pattern --- soil total nitrogen --- generation --- tree mortality --- land use types --- forest conversion --- DCD --- carbon source–sink --- stoichiometric ratios --- autotrophic respiration --- N2O --- CO2 emission --- organic carbon mineralization --- CH4 emissions --- clear-cutting --- CO2 production and diffusion --- soil quality --- nitrification inhibitor --- organic carbon accumulation --- climate change mitigation --- global change --- greenhouse gas inventory --- warming --- soil properties --- bacterial community --- sensitivity --- soil characteristics --- forest --- insect outbreak --- biochar --- nitrous oxide --- CO2 --- soil respiration --- land-use change --- decomposition --- soil --- natural forest --- calcareous soils --- greenhouse gas --- forest soils --- karst graben basin --- plantation --- rocky desertification --- fitting parameters --- temperature --- forest disturbance --- microbe --- subtropical forest --- N addition --- carbon stock changes --- IPCC --- next-generation sequencing --- nitrogen --- N2O emissions --- red soils --- CH4 --- coastal wetlands --- CO2 emissions --- stand age --- successive planting --- plum plantation ages

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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