Prajwol Babu Subedi Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
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Biography and Research Information
OverviewAI-generated summary
Prajwol Babu Subedi's research focuses on the application of remote sensing, Geographic Information Systems (GIS), and machine learning techniques for environmental assessment and resource management. His work includes mapping land use and land cover dynamics, estimating above-ground forest biomass, and assessing deforestation and forest degradation rates. Subedi has investigated the agroforestry potential of specific regions and mapped forest fire risk zones.
His recent publications explore the use of high-resolution imagery, machine learning, and deep learning techniques for biomass estimation, including studies utilizing data from GEDI. He has also examined vegetation structure and carbon stock potential in community-managed forests. Subedi has an h-index of 2 with 11 total publications and has collaborated with Marco A. Yáñez on two shared publications.
Metrics
- h-index: 2
- Publications: 11
- Citations: 21
Selected Publications
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Multi-sensor forest aboveground biomass estimation using GEDI, machine learning, and deep learning techniques (2025)
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Estimating Above Ground Forest Biomass Using High-Resolution NAIP Imagery and Deep Learning (2025)
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Comparison of Supervised Machine Learning Algorithms for Extracting Tree Canopy Cover using High-Resolution Imagery and Google Earth Engine (2025)
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Automated Individual Tree Crown Detection and Segmentation using Simple Non-Iterative Clustering (SNIC) Algorithms and High-Resolution LiDAR (2025)
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Estimating Above Ground Forest Biomass Using High-Resolution NAIP Imagery, Machine Learning, and Google Earth Engine (2024)
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