Subhasis Ghosh, MS, MA, PgDip.

Ph.D. Candidate of Earth System Science
Graduate Teaching Assistant
NASA Graduate Research Fellow, 2021-2025
USGS Climate Adaptation Scientists of Tomorrow Fellow, 2023
Department of Geosciences, Auburn University, USA

"Dedicated to excellence, committed to impact"

About image
Subhasis Ghosh is an early career researcher and a published author. He is a Geoscientist specializing in urban-climatology research, with a strong academic foundation in geography, geoinformatics, and urban planning. His work encompasses diverse interests, including urban agglomerations, climate change, weather & climate modeling, human-environment interactions, and process geomorphology. Leveraging advanced techniques 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.
Presently, he is a doctoral candidate (ABD) at the Department of Geosciences, Auburn University, USA. He is looking into the global urbanization footprints and urban rainfall effect climatologies which is being funded through the National Aeronautics and Space Administration (NASA) under the supervision of Dr. Chandana Mitra from the urbanPRism research lab of the department. He also teaches geography and geospatial courses as a Graduate Teaching Assistant in the department.
He holds a Master of Science degree in Geography (urban geoinformatics focused), Master of Arts degree in Geography (Applied Geomorphology focused), a Post-Graduate Diploma in Geoinformatics, and a Post-Graduate Diploma in Urban Planning and development.
Prior joining Auburn, Subhasis had worked closely with the Indian Space Research Organization (ISRO) and contributed in the planning & development process of the country.
He is skilled in performing complex geospatial analyses using advanced Remote Sensing, GIS and Machine Learning techniques; spatial and non-spatial database management systems , cloud computing (GEE), and is well versed in using Python and R programming languages in terms of geospatial analysis and research.
Besides academics, he is actively engaged in various leadership, community service, and outreach activities within and off campus. At present, he serves as the Director of Outreach and Engagement for the Regional Development and Planning Specialty Group of the American Association of Geographers (AAG). In his spare time, he likes to mentor students and help them discover their potential.

View Scholarly Profiles:
Google Scholar , ORCID,  Research Gate

"Discover, Explore, Engage!"

NDUI+: A New AI-powered multidecadal global high-resolution urban dataset is here! check it out!

NDUI+: A New AI-powered multidecadal global high-resolution urban dataset is here! check it out!

10/18/2024

The all-new 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. NDUI+ data can be generated globally using the codes made available at https://github.com/manmeet3591/ndui_plus, and the trained weights available in Zenodo.

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Have covid lockdowns really improved global air quality? –Hierarchical observations from the perspective of urban agglomerations using atmospheric reanalysis data

Have covid lockdowns really improved global air quality? –Hierarchical observations from the perspective of urban agglomerations using atmospheric reanalysis data

8/3/2023

COVID-19 cases surged in late 2019, leading to worldwide lockdowns that closed non-essential places and activities, industries, and businesses to halt the spread of the virus. Many studies suggested improved air quality during lockdowns. However, these findings often focused on core city limits and did not account for heavy pollution sources outside cities (around the fringe areas), such as factories, power plants, and coal mines, which operated continuously for energy needs even during lockdowns. Therefore, this study quantified and re-analyzed the air quality data using a top-down approach.

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Long-term normalized difference urban index (NDUI) data time series for urban studies

Long-term normalized difference urban index (NDUI) data time series for urban studies

6/5/2023

This is a working paper. Keeping continuous, long-term data to examine changes in urban surroundings is crucial as cities expand and develop. The DMSP OLS nighttime lights data and the Landsat NDVI were used to create the Normalized Difference Urbanization Index (NDUI), which has proven to be an invaluable resource for studying urban areas. However, DMSP's reach and usefulness are constrained by the fact that data collecting ended in 2014 while VIIRS has continued to collect the nighttime lights data since 2012...

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Biogeographic Distribution of Cedrela spp. Genus in Peru Using MaxEnt Modeling: A Conservation and Restoration Approach

Biogeographic Distribution of Cedrela spp. Genus in Peru Using MaxEnt Modeling: A Conservation and Restoration Approach

6/10/2021

The increasing demand for tropical timber from natural forests has reduced the population sizes of native species such as Cedrela spp. because of their high economic value. To prevent the decline of population sizes of the species, all Cedrela species have been incorporated into Appendix II of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). The study presents information about the modeled distribution of the genus Cedrela in Peru that aims to...

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Long-Term Sensitivity Analysis of Palmer Drought Severity Index (PDSI) Through Uncertainty and Error Estimation from Plant Productivity and Biophysical Parameters

Long-Term Sensitivity Analysis of Palmer Drought Severity Index (PDSI) Through Uncertainty and Error Estimation from Plant Productivity and Biophysical Parameters

11/12/2020

Palmer Drought Severity Index (PDSI) is the most effective and well-acknowledged drought severity index that particularly determines the long-term drought conditions over the forest and other terrestrial ecosystems. However, the sensitivity of PDSI has not been explored yet based on productivity (i.e., Gross Primary Productivity (GPP)), biophysical parameters (i.e., biomass—Leaf Area Index (LAI) and Enhanced Vegetation Index (EVI) and greenness content—Normalized Difference Vegetation Index (NDVI)), and absorbed solar radiation by plants (i.e., fraction of Absorbed Solar Radiation (fAPAR)) over a humid-subtropical forest ecosystem...

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Environmental Risk Assessment: A Geomorphic Investigation over the Bolpur-Santiniketan-Illambazar Lateritic Patch of Birbhum District, West Bengal, India

Environmental Risk Assessment: A Geomorphic Investigation over the Bolpur-Santiniketan-Illambazar Lateritic Patch of Birbhum District, West Bengal, India

2/24/2022

A proper Geomorphic study of a region can be useful in understanding past and present environmental circumstances and analyzing potential environmental risks. Careful analysis of morphodynamic processes and existing diagnostic land forms reveal several aspects about the origin, characteristics and possible pattern of morpho-climatic interactions on the landscape over temporal scale, which helps significantly in proper terrain evaluation from societal welfare and integrated management point of view, including environmental risk assessment and disaster management. This paper has made a thorough geomorphic investigation...

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Canopy Scale High-Resolution Forest Biophysical Parameter (LAI, fAPAR, and fCover) Retrieval Through Machine Learning and Cloud Computation Approach

Canopy Scale High-Resolution Forest Biophysical Parameter (LAI, fAPAR, and fCover) Retrieval Through Machine Learning and Cloud Computation Approach

3/16/2023

High-resolution Forest biophysical parameter estimation is crucial to understand forest structural and functional variability. Moreover, mapping high-resolution biophysical products is significant to capture accurate forest carbon fluxes and understand seasonal variability. The existing biophysical products are coarse in spatial resolution and unable to capture intra-annual variability. In this study, we proposed a random forest machine learning approach embedded in Google Earth Engine to retrieve three major forest biophysical parameters. The training samples were distributed in a 70:30 ratio for model training and validation. The outcome of the work shows promising results that hold a good agreement with SNAP-derived biophysical variables, whereas the agreement is moderate-to-poor for MODIS and VIIRS biophysical products...

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"Shining Bright in Media's Spotlight!"

Auburn doctoral student challenges perceptions of COVID-lockdowns' impact on air quality with international team of researchers through NASA project

Auburn doctoral student challenges perceptions of COVID-lockdowns' impact on air quality with international team of researchers through NASA project

10/24/2023

Research activity featured by COSAM Today news

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"Where knowledge meets action"

 

Graduate Teaching Assistant

Teaching Assistant at the Department of Geosciences, Auburn University, USA. Courses Teaught: Advanced GIS, Drones and Geospatial Applications, Quantitative Methods and Spatial Analysis, Concepts of Science, Global Geography.

1/11/2024
 

Graduate Research Assistant (USGS funded project)

Working in a USGS-funded project - 'Earth as Art’ Interactive Global Museum. In this project, I am turning the complex remote-sensing images into simple, artistic photographs and working with a multidisciplinary team to transform the processed images into engaging virtual reality (VR) based interactive modules, ensuring alignment with educational objectives and target audience engagement to promote interest in Earth science and STEM disciplines.

Learn More10/1/2023
 

Graduate Research Assistant - NASA IDS

Researching the impacts of global urbanization footprints and urban rainfall effect climatologies funded by National Aeronautics and Space Administration (NASA)At Department of Geosciences, Auburn University Duration: Aug 2021 to Present

Learn More8/16/2021
 

Project Scientist at West Bengal State Council of Science & Technology, Govt. of West Bengal, India

Professionally worked and contributed to the project- “Space Based Information Support for Decentralized Planning (SIS-DP) Update”, sponsored by National Remote Sensing Centre (NRSC), Indian Space Research Organization (ISRO), Govt. of India. Duration: Mar 2021 - Jul 2021

Learn More3/1/2021
 

Trainee GIS Analyst at Prayukti Systems Private Limited, India

Engaged as the Lead GIS Consultant to the office of West Bengal State Rural Development Agency - Purulia Division, Govt. of West Bengal for the project - ’Utility-Facility mapping, geo-database creation, and verification of road construction status sanctioned under Pradhan Mantri Gram Sadak Yojana (PMGSY) scheme' , funded by Government of India.

Learn More9/2/2019

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  • Office: Haley 2194A
  • Department of Geosciences, College of Sciences and Mathematics, Auburn University, Auburn, AL, USA, 36849

info@subhasisghosh.com


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