Geospatial and Environmental Modeling Group

Objective

The Geospatial and Environmental Modeling Group is focused on the research in modeling of varied environmental variables and their applications. It aims to employ cutting-edge technologies in various areas of geosciences and conduct research in both the theoretical and application aspects. The research focuses on following areas:

  • Pollutant Forecasting and Monitoring
  • WaterResource/Quality Modeling
  • WindSpeedModeling
  • ModelingofSoil Nutrients Monitoring
  • DeepLearningforSpatial Data Processing

The Geospatial and Environmental Modeling Group at IIIT Sri City actively looks for the sponsored projects funded by the Govt. Bodies and Industries. The group is also dedicated towards producing the highly trained students in the broad areas of geospatial technologies. The research produced by the group will have a significant impact on companies working on geospatial technologies, remote sensing, deep learning and machine learning.

Faculties
No. Name of Faculty Area of Specialization
1.  Dr.Mainak Thakur
mainak.t@iiits.in		 Spatial Statistics / Geostatistics, Spatio-temporal Statistics, Non-stationary and non-gaussianity problems in spatial data, Multivariate Modeling, Modeling Environmental Variables (Pollutants, Wind Speed, Water Quality), Statistical Modeling of Bio-signals
2. Dr.ArunPV
arun.pv@iiits.in		 Deep Learning, Image Processing, Remote Sensing, Explainable AI, Geo Informatics, Precision Agriculture
3. Dr.Anish Chand Turlapaty
anish.turlapaty@iiits.in		 Intersection of signal processing and machine learning algorithms with applications in remote sensing data
analysis.
Sponsored Research Projects
Title PI and Co-PIs Duration Amount Funding Agency
Digital Twin for City-based Air Pollutant Distribution Framework PI: Dr. Mainak Thakur
Co-PI: Dr. Arijit Roy		 2024 - 2026 Rs. 10,40,000/- DST-DAAD
Development of a generic spatial data warehousing framework and illustration for protected area monitoring and landslide susceptibility mapping PI: Dr. Arun PV 2023 - 2026 Rs. 26 Lakhs SERB-CRG
Machine Learning techniques for multimodal data fusion for lunar surface mapping PI: Dr. Arun PV 2023 - 2026 Rs. 20 Lakhs ISRO
Deep learning-based resolution enhancement and multimodal data fusion PI: Dr. Arun PV 2023 - 2026 Rs. 26 Lakhs ISRO
Advanced ML techniques for real-time spatial data analysis PI: Dr. Arun PV 2024 - 2027 - Indian Army
Spatial Decision Support System for Swachhta Abhiyan Co-PI: Dr. Arun PV 36 Lakhs Meity
Computer vision and machine learning techniques for automated monitoring of engineering structures Co-PI: Dr. Arun PV 60 Lakhs DST
Development of a comprehensive spatial database using AI/ML models for forest fire monitoring PI: Dr. Arun PV 1.8 Cr (1.5 Lakhs USD) ESA
Publications
Journals
2024
  • Mandal, S., Boppani, S., Dasari, V., & Thakur, M. (2024). A bivariate simultaneous pollutant forecasting approach by Unified Spectro-Spatial Graph Neural Network (USSGNN) and its application in prediction of O3 and NO2 for New Delhi, India. Sustainable Cities and Society, 105741.
  • Thakur, M., Mandal, S., Manohar, P., & Chatterjee, S. (2024). Spatio-temporal characteristics of particulate matter in Delhi, India due to the combined effects of fireworks and crop burning during pre-COVID festival seasons. Natural Hazards, 1-28.
2023
  • Gorripati, R., Thakur, M., & Kolagani, N. (2023). Promoting Climate Resilient Sustainable Agriculture through Participatory System Dynamics with Crop-Water-Income Dynamics. Water Resources Management, 1-17. [Published, Impact Factor: 4.3]
    DOI : https://doi.org/10.1007/s11269-023-03533-w
  • Mandal, S., & Thakur, M. (2023). A city-based PM2. 5 forecasting framework using Spatially Attentive Cluster-based Graph Neural Network model. Journal of Cleaner Production, 405, 137036. [Published, Impact Factor: 11.1]
    DOI : https://doi.org/10.1016/j.jclepro.2023.137036
  • Dong Zhao, Xuguang Zhu, Zhe Zhang, Pattathal V. Arun, Jialu Cao, Qing Wang, Huixin Zhou, Hao Jiang, Jianling Hu, Kun Qian, Hyperspectral video target tracking based on pixel-wise spectral matching reduction and deep spectral cascading texture features, Signal Processing, Volume 209, 2023, 109033, ISSN 0165-1684, https://doi.org/10.1016/j.sigpro.2023.109033.
  • Sahoo MM, Kalimuthu R, PV A, Porwal A, Mathew SK. Modelling Spectral Unmixing of Geological Mixtures: An Experimental Study Using Rock Samples. Remote Sensing. 2023; 15(13):3300. https://doi.org/10.3390/rs15133300
  • Zhang J, Li H, Zhao D, Arun PV, Tan W, Xiang P, Zhou H, Hu J, Du J. An ISAR and Visible Image Fusion Algorithm Based on Adaptive Guided Multi-Layer Side Window Box Filter Decomposition. Remote Sensing. 2023; 15(11):2784. https://doi.org/10.3390/rs15112784
  • Zhang Z, Hu B, Wang M, Arun PV, Zhao D, Zhu X, Hu J, Li H, Zhou H, Qian K. Hyperspectral Video Tracker Based on Spectral Deviation Reduction and a Double Siamese Network. Remote Sensing. 2023; 15(6):1579. https://doi.org/10.3390/rs15061579
  • Dong Zhao, Liu Tang, Pattathal V. Arun, Yuta Asano, Like Zhang, Youzhi Xiong, Xu Tao, Jianling Hu, City-scale distance estimation via near-infrared trispectral light extinction in bad weather, Infrared Physics & Technology, Volume 128, 2023, 104507 https://doi.org/10.1016/j.infrared.2022.104507
Conferences
2024
  • Mandal, S., Das, K., Thakur, M., Padmanaban, M., & Hazra, J. (2024, July). IMPROVED DISSOLVED ORGANIC CARBON PREDICTION IN DIVERSE INLAND WATER BODIES: UTILIZING MACHINE LEARNING AND REMOTE SENSING. In IEEE International Geoscience and Remote Sensing Symposium.
2023
  • Mandal, S. & Thakur, M. (2023) A Study on the Estimation of Surface Ozone Pollution in the Indian Megacity, Delhi at pre-, during- and post-COVID Years using Statistical and Machine Learning Models. In 9th International Congress on Environmental Geotechnics (9ICEG), Volume 5, June 25th to June 28th 2023 in Chania, Crete, Greece. DOI: https://doi.org/10.53243/ICEG2023-422
  • Bhojanapalli, A., Mandal, S., Thakur, M., & Das, K. (2023, July). A CALIPSO Observation Based 3-Dimensional Tropospheric Aerosol Classification Model Over the Indian City Delhi. In IGARSS 2023-2023 IEEE International Geoscience and Remote Sensing Symposium (pp. 305-308). IEEE. DOI: 10.1109/IGARSS52108.2023.10282609
  • Ejurothu, P. S. S., Mandal, S., & Thakur, M. (2023). A Machine Learning Approach for PM2. 5 Estimation for the Capital City of New Delhi Using Multispectral LANDSAT-8 Satellite Observations. In Computer Vision and Machine Intelligence: Proceedings of CVMI 2022 (pp. 389-400). Singapore: Springer Nature Singapore. DOI: https://doi.org/10.1007/978-981-19-7867-8_31
2022
  • Mandal, S., Thakur, M., Turlapaty, A. C., Shaik, R. U., & Giovanni, L. (2022, July). Application of Prisma Hyperspectral Data for PM 2.5 Estimation: A Case Study on New Delhi, India. In IGARSS 2022-2022 IEEE International Geoscience and Remote Sensing Symposium (pp. 5069-5072). IEEE. DOI: https://doi.org/10.1109/IGARSS46834.2022.9884594
  • Kusuru, D., B. N. Jyothi V, Imandi, R., Turlapaty, A.C., & Thakur, M. (2022, February). A Gaussian Gamma mixture model for Indian ocean surface wind speed. In OCEANS 2022-Chennai (pp. 1-5). IEEE. DOI: https://doi.org/10.1109/OCEANSChennai45887.2022.9775268
  • Kishore, S. N., Thakur, M., & Mandal, S. (2022, February). Forecasting of Wind Speed at Offshore Wind Site-A Case Study. In OCEANS 2022-Chennai (pp. 1-6). IEEE. DOI: https://doi.org/10.1109/OCEANSChennai45887.2022.9775427
Patents (if any) : None
Other Prominent Details

a) PhD Students:

  • Mr. Subhojit Mandal: Published four journal articles and appearing for Synopsis Topic: Atmospheric Pollutant Monitoring framework using Graph Neural Network approach
  • Mr. Nandha Kishore S R: Communicated a journal article Topic: Wind Speed Modeling and Optimal Siting of Offshore Wind Farm

b) Honors student:

  • Mr. Manoj Varma Datla: Communicated a conference article Topic: Multivariate modeling of pollutants