Monitoring Forest Carbon Sequestration with Remote Sensing

The forest, as the main body of the terrestrial ecosystem, has a huge carbon sink function and plays an important role in coping with global climate change. This reprint on “Monitoring forest carbon sequestration with remote sensing” mainly focuses on new remote sensing theories, methods, and techno...

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Detaylı Bibliyografya
Materyal Türü:	Online
Dil:	İngilizce
Baskı/Yayın Bilgisi:	MDPI - Multidisciplinary Digital Publishing Institute 2023
Konular:	forest height synthetic aperture radar (SAR) interferometry random volume over ground (RVoG) model three-stage inversion method bamboo forest BEPS model gross primary productivity net primary productivity spatiotemporal evolution climate change backscatter coefficients polarization decomposition collinearity ridge regression RF PCA aboveground carbon density LiDAR stratified estimation machine learning algorithm Northeast China canopy closure the GOST model fisheye camera photos transects LAI forest height inversion three-stage algorithm coherence optimization complex coherence amplitude inversion SRTM random forest stochastic gradient boosting random forest Kriging wavelet analysis carbon storage land use/cover change scenario simulation PLUS model InVEST model remote sensing inversion dynamic change driving factors Shaoguan City above-ground biomass (AGB) airborne LiDAR airborne hyperspectral wavelet transform feature fusion Landsat time-series VCT model classifying forest types forest aboveground biomass forest aboveground biomass (AGB) scale effect random forest (RF) scale correction phenology dynamic threshold method northeast China TIMESAT forest carbon stocks simulation LUCC multi-source data feature selection aboveground biomass habitat dataset Landsat 8-OLI images pine forest model comparison 3D green volume UAV-Lidar urban forest random forest model remote sensing MODIS FY-3C VIRR Yunnan Province mangrove forests Hainan Island deep learning influential mechanism Bayesian hierarchical modelling geostatistics Eucalyptus grandis Eucalyptus camaldulensis Pinus patula spatial random effects spatially varying coefficient rubber plantation time series shapelet Landsat Pinus densata terrain niche index dynamic model canopy volume diameter at breast height (DBH) aboveground biomass (AGB) stem volume (V) near-infrared reflectance of vegetation carbon budget L-band PolInSAR RVoG model forest density terrain slope coherence extinction coefficient signal penetration 3-PG model eucalyptus forest age forest structure sensitivity clumping index estimation impact analysis field measurement Sentinel-2 images artificial neural network random forests quantile regression neural network Pinus densata forests thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics
Online Erişim:	ONIX_20230511_9783036572086_52
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Diğer Bilgiler
Özet:	The forest, as the main body of the terrestrial ecosystem, has a huge carbon sink function and plays an important role in coping with global climate change. This reprint on “Monitoring forest carbon sequestration with remote sensing” mainly focuses on new remote sensing theories, methods, and technologies for monitoring carbon sinks in forest ecosystems (including urban forest ecosystems).

Monitoring Forest Carbon Sequestration with Remote Sensing

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