Development of Upscaling Model by Integrating Terrestrial LiDAR and Aerial LiDAR for Individual Tree Morphology, Above Ground Biomass, and Species Identification to Estimate Carbon Stock
Implementing Organization
Indian Institute of Technology (IIT), Kanpur
Principal Investigator
Prof. Bharat Lohani
Indian Institute Of Technology (IIT), Kanpur, Uttar Pradesh (208016)
CO-Principal Investigator
Dr. Sandeep Gupta
Kurukshetra University
About
The project aims to improve tree morphology, species identification, AGB, and carbon stock in Indian forests by integrating TLS and ALS technologies. Accurate AGB estimation is crucial for understanding the global carbon cycle, assessing forest hazards, promoting bioenergy, and implementing environmental initiatives. The project will use machine learning ML and deep learning DL techniques for leaf filtering, species identification, and upscaling model development. It will also develop a strata-based upscaling model for AGB estimation, considering factors like forest type, species, age, site quality, and spectral data indices. Species information will be incorporated into the analysis.
Indian Institute of Technology (IIT), Kanpur
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