Remote sensing technologies contribute to accurate forest carbon stock estimation and monitoring by providing detailed and continuous data, enabling global coverage, and facilitating the integration of various data sources for a more holistic understanding of forest ecosystems. However, its contribute to accurately estimating and monitoring forest carbon stock at both regional and global scales is lacking.
Accuracy of Forest carbon stock estimation and monitoring using Remote sensing technologies depends upon the accurate forest biomass estimation at regional and global level. Various remote sensing data Optical, Hyperspectral, SAR & Lidar are used for Forest biomass estimation based on their spatial, spectral and temporal resolution. At regional level Hyperspectral imageries are used for vegetation structure identification and various SAR & LiDAR data are used for forest tree height mapping to estimate the regional level forest biomass and respective carbon stock. However for global level a more holistic methodology is adopted for the forest biomass estimation by integrating the various data sources. Also ground measurement is must required activity for forest biomass and carbon stock estimation and monitoring.
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