Aboveground biomass estimation using multi-sensor data synergy and machine learning algorithms in a dense tropical forest

@article{Ghosh2018AbovegroundBE,
  title={Aboveground biomass estimation using multi-sensor data synergy and machine learning algorithms in a dense tropical forest},
  author={Sujit Ghosh and Mukunda Dev Behera},
  journal={Applied Geography},
  year={2018},
  volume={96},
  pages={29-40}
}
Abstract Forest aboveground biomass (AGB) is an important factor for tracking global carbon cycle to tackle the impact of climate change. Among all available remote sensing data and methods, Synthetic Aperture Radar (SAR) data in combination with decision tree based machine learning algorithms has produced favourable results in estimating higher biomass values. Suitability of this method for dense tropical forests has not been properly checked with an adequate number of studies. In this study… Expand
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