Dr. Subhasis Ghosh

Assistant Professor of Physical Geography
Office: 211 Martin Hall
256-782-5301
ghosh@jsu.edu  

Dr. Subhasis Ghosh is a Geoscientist specialized in quantitative geospatial research, with formal training in Earth System Science (interdisciplinary), Physical Geography, Geoinformatics, and Urban Planning & Development. His work encompasses diverse interests, including (but not limited to) Remote Sensing of the natural and built environment, Weather-Climate research, Geospatial Data Science, GIS, and Drone (UAS) applications.
Leveraging advanced technologies such as remote sensing, machine learning/Artificial Intelligence, and cloud computing, he is committed to interdisciplinary research that uncovers innovative solutions for our evolving world, driving positive change for our future.
He is also actively engaged in various leadership, community service, and outreach activities within and off campus. At present, he serves as the Vice Chair of the Regional Development and Planning Specialty Group of the American Association of Geographers (AAG). He enjoys mentoring students and helping them discover their true potential.

Subhasis Ghosh

Courses Taught

  • GY 250 Physical Geography I: Atmospheric Patterns and Processes
  • GY 252 Physical Geography Lab I
  • GIS 5220/GIS 420 Web-based GIS: Technologies and Applications
  • GY 251 Physical Geography II: Landscape Patterns and Processes

Education

  • Ph.D. in Earth System Science - Auburn University, AL (2025)
  • Graduate Cert. in Geographic Information System Science - Auburn University, AL (2024)
  • M.S. in Geography (Geography and Environmental Studies) - Auburn University, AL (2023)
  • Post Graduate Diploma in Urban Planning and Development - Indira Gandhi National Open University, India (2020)
  • Post Graduate Diploma in Geoinformatics - Maulana Abul Kalam Azad University of Technolog, India (2019)
  • M.A. in Geography - Visva-Bharati University, India (2018)
  • B.A. (Honors) in Geography - Visva-Bharati University, India (2016)

Other Responsibilities

  • Vice Chair - Regional Development and Planning Specialty Group, American Association of Geographers

Publications

Selected Peer-Reviewed Publications
  1. Das, R. D., Bandopadhyay, S., Ghosh, S., Das, M., Chowdhury, M., Cotrina-Sanchez, A., Kumar, C., & Mitra, C. (2023). Have COVID lockdowns really improved global air quality? –Hierarchical observations from the perspective of urban agglomerations using atmospheric reanalysis data. Physics and Chemistry of the Earth, Parts A/B/C, 132, 103452. https://doi.org/10.1016/j.pce.2023.103452
  2. Bandopadhyay, S., Das, B., Sánchez, A. C., Banerjee, S. P., Banerjee, B. P., & Ghosh, S. (2023). Canopy Scale High-Resolution Forest Biophysical Parameter (LAI, fAPAR, and fCover) Retrieval Through Machine Learning and Cloud Computation Approach. In IEEE (Ed.), 2023 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing (MIGARS) (pp. 1-4). Hyderabad, India. doi: https://doi.org/10.1109/MIGARS57353.2023.10064558 
  3. Cotrina Sánchez, A., Rojas Briceño, N. B., Bandopadhyay, S., Ghosh, S., Torres Guzmán, C., Oliva, M., Guzman, B. K., & Salas López, R. (2021). Biogeographic Distribution of Cedrela spp. Genus in Peru Using MaxEnt Modeling: A Conservation and Restoration Approach. Diversity, 13(6), 261. https://doi.org/10.3390/d13060261
  4. Ghosh, S., Bandopadhyay, S., & Sánchez, D. A. Cotrina. (2021). Long-Term Sensitivity Analysis of Palmer Drought Severity Index (PDSI) through Uncertainty and Error Estimation from Plant Productivity and Biophysical Parameters. Environ. Sci. Proc., 3(1), 57. https://doi.org/10.3390/IECF2020-07956
  5. Jha, V. C., & Ghosh, S. (2020). Environmental Risk Assessment: A Geomorphic Investigation over the Bolpur-Santiniketan-Illambazar Lateritic Patch of Birbhum District, West Bengal, India. National Geographical Journal of India, 66(2), 94-110. https://doi.org/10.48008/ngji.1733

Global Urban Footprints Dataset (Open Access)

Description: The NDUI+ dataset is a global, high-resolution (30-meter) remotely sensed urban dataset, covering the period from 1999 to the present. It solves key challenges in remote sensing, including gaps in resolution, coverage, and the continuity of urban data. This comprehensive dataset is valuable for a wide range of applications, such as urban growth analysis, microclimatic variability studies, and assessments of economic impacts, among others. Data Repository Link: DOI: 10.5281/zenodo.10799651