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Marble Surface

Publications

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Peer-reviewed

  1. Majumdar, S., Smith, R., Hasan, M.F., Wilson, J. L., White, V.E., Bristow, E.L., Rigby, J.R., Kress, W., and Painter, J.A. (2024). Improving Crop-Specific Groundwater Use Estimation in the Mississippi Alluvial Plain: Implications for Integrated Remote Sensing and Machine Learning Approaches in Data-Scarce Regions. Journal of Hydrology: Regional Studies, 52, 101674.

  2. Hasan, M. F., Smith, R., Vajedian, S., Pommerenke, R., & Majumdar, S. (2023). Global land subsidence mapping reveals widespread loss of aquifer storage capacity. Nature communications, 14(1), 6180.

Conference talk

  1. Hasan, M. F., Smith, R., Vajedian, S., Pommerenke, R., & Majumdar, S. (2022). Linking subsidence and groundwater storage loss: Investigating drivers and trends using big data. In AGU Fall Meeting (Chicago, IL).

  2. Smith, R., Majumdar, S., Oyler, L., Pommerenke, R., Li, J., Hasan, M. F., Butler, J. J., Lakshmi, V., Conway, B. D., Rigby, J. R., Knight, R., & Goebel, M. (2021). Modeling hydrogeologic fluxes and their impact on natural and human systems. In AGU Fall Meeting (New Orleans, LA)

Conference abstract

  1. Hasan, M. F., & Smith, R. (2023). A Data-driven Approach for Estimating Irrigation Groundwater Use for the Western United States. In AGU Fall Meeting (San Francisco, CA).

  2. Majumdar, S., Smith, R., Hasan, M. F., White, V. E., Bristow, E., Kress, W., & Rigby, J. R. (2022). High-resolution groundwater use estimation at annual and monthly scales in the Mississippi Alluvial Plain using remote sensing and machine learning. In AGU Fall Meeting (Chicago, IL).

  3. Hasan, M. F., Smith, R., Pommerenke, R., & Majumdar, S. (2021). Mapping global land subsidence using remote sensing and machine learning. In AGU Fall Meeting (New Orleans, LA).

  4. Majumdar, S., Smith, R., Hasan, M. F., Wilson, J. L., Bristow, E., Oyler, L., & Rigby, J. R. (2021). Using remote sensing and machine learning to estimate groundwater use in the Mississippi Alluvial Plain. In AGU Fall Meeting (New Orleans, LA).

  5. Smith, R., Majumdar, S., Hasan, M. F., Butler, J. J., Lakshmi, V., Conway, B. D., & Rigby, J. R. (2021). Mapping groundwater use with satellite sensor fusion and machine learning. In GSA Connects (Portland, OR).

Conference papers

  1. Hasan, M. F., Rashid, M. A. and Mostofa, N. (2020), Land Use Change Prediction of Cumilla City Using GIS and Remote Sensing Technique with Cellular Automata Markov Analysis. International Conference on Civil Engineering for Sustainable Development (ICCESD 2020)     

  2.  Hasan, M. F., Mow, N. (2019). Trend Analysis of Shoreline Changes of the Ganges in the North West Region of Bangladesh.        International Conference on Water and Environmental Engineering (iCWEE-2019)       

  3. Hasan, M. F., Mow, N., Alam, M. R., Hasan, S. M. A. and Mamtaz, R. (2018). Recycling Potential of Textile Solid Waste. WIT Transactions on Ecology and the Environment, Vol 231, p: 125-136

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