People

Prajwol (Babu) Subedi
CFANR-UAM Alumni: Class of 2025

Graduated: Spring 2025.

Research topic: "Determination and accuracy analysis of automated individual tree crown delineation parameters and tree canopy cover estimation in Arkansas, USA"

Peer-reviewed scientific publications (#7):

Journal Articles (#2), Conference Proceedings (#4), and Book Chapters (#1)

Subedi*, P.B., H.A., Zurqani, M.A., Blazier, M., Yanez, and K. Cunningham. 2026. Estimating tree canopy cover using high-resolution NAIP imagery and LiDAR and comparing it to existing datasets. Geospatial Artificial Intelligence (GeoAI) in Environmental and Natural Resources Management. Earth and Environmental Sciences Library. Switzerland. Springer International Publishing AG (Book Chapter: In Press)
Subedi*, P.B., and H.A., Zurqani. 2025. Multi-Sensor Forest Aboveground Biomass Estimation Using GEDI, Machine Learning, and Deep Learning Techniques. Advances in Space Research (Journal Article: In Review).
Subedi*, P.B., and H.A., Zurqani. 2025. Multi-Sensor Forest Aboveground Biomass Estimation Using GEDI, Machine Learning, and Deep Learning Techniques. Advances in Space Research (Journal Article: In Review).
Subedi*, P.B., H.A., Zurqani, M.A., Blazier, M., Yanez, and K. Cunningham. 2025. Comparison of Supervised Machine Learning Algorithms for Extracting Tree Canopy Cover Using High-Resolution Imagery and Google Earth Engine. In the 12th IEEE Conference on Technologies for Sustainability (SusTech 2025), Los Angeles, CA, USA, 2025, pp. 1-8, doi: 10.1109/SusTech63138.2025.11025678. (Conference Proceeding).
Subedi*, P.B., H.A., Zurqani, M.A., Blazier, M., Yanez, and K. Cunningham. 2025. Automated Individual Tree Crown Detection and Segmentation Using Simple Non-Iterative Clustering (SNIC) Algorithms and High-Resolution LiDAR. In the 12th IEEE Conference on Technologies for Sustainability (SusTech 2025), Los Angeles, CA, USA, 2025, pp. 1-8, doi: 10.1109/SusTech63138.2025.11025563. (Conference Proceeding).
Subedi*, P.B., and H.A., Zurqani. 2025. Estimating Above Ground Forest Biomass Using High-Resolution NAIP Imagery and Deep Learning. In the IEEE 4th International Conference on Computing and Machine Intelligence (ICMI), Michigan, USA, April 05—06, 2025, (Conference Proceeding).
Subedi*, P.B., and H.A., Zurqani. 2025. Estimating Above Ground Forest Biomass Using High-Resolution NAIP Imagery, Machine Learning, and Google Earth Engine. In 2024 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS), Manado, Indonesia, Dec 13–14, 2024, pp. 92-101, doi: 10.1109/AGERS65212.2024.10932891. (Conference Proceeding).

Abstracts and Posters (#2):

Subedi*, P.B., H.A., Zurqani, M.A., Blazier, M., Yanez, and K. Cunningham. 2024. Comparison of Supervised Machine Learning Algorithms for Extracting Tree Canopy Cover Using High-Resolution Imagery and Google Earth Engine. The Society of American Foresters (SAF) National Convention. Loveland, Colorado, September 17–20, 2024.
Subedi*, P.B., H.A., Zurqani, M.A., Blazier, M., Yanez, and K. Cunningham. 2023. Using Machine Learning and Google Earth Engine to Enhance the Forest Canopy Cover Analysis and Individual Tree-Crown Detection. The 14th Southern Forestry and Natural Resource Management GIS conference (SOFOR GIS), Athens, Georgia, December 11–12, 2023.

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