Hello there! I am Sohan Nag, a Geologist specializing in Remote Sensing, GIS, and Geospatial Analysis with a focus on Water Quality Monitoring and Environmental Applications. I utilize Machine Learning and advanced satellite data processing for Hydrological Systems, Fluvial Geomorphology, and Environmental Sustainability. Passionate about leveraging Google Earth Engine, SAR, and multi-source satellite data, I aim to contribute to climate-resilient water resource management and cutting-edge environmental research.

• Geospatial Data Analysis: Python (Pandas, NumPy, Scikit-learn), Google Earth Engine (JavaScript & Python API)
• Water Quality Analysis: Satellite-based parameter estimation (Turbidity, TDS, Salinity), seasonal variation analysis
• Remote Sensing: Optical & Radar Data Processing (Sentinel-2, SAR), multi-source satellite data integration
• Python Libraries: Geemap, GeoPandas, Rasterio, Matplotlib, Seaborn
• GIS Software: ArcGIS, QGIS
• Data Visualization: Geomorphological Mapping (ArcGIS, QGIS, Python), Seismic & GPS Data (GMT)
• Seismic Data Processing: ObsPy, SAC, TauP, FOCMEC
• Machine Learning: K-means clustering, feature extraction, environmental modeling

• Water Quality Monitoring & Hydrological Systems: Satellite-based water quality assessment, anthropogenic impacts on water resources, climate impacts on drinking water systems
• Machine Learning for Environmental Applications: Automating detection and analysis of environmental features, predictive modeling for water resources management
• Fluvial Morphodynamics & River Systems: River morphology, sediment dynamics, human impact on fluvial systems, intersection of geomorphology with water quality
• Remote Sensing for Environmental Sustainability: Multi-source Earth observation data integration for environmental monitoring, climate resilience applications
• Seismicity and Ground Deformation: Tectonic stress analysis using GPS and seismic data
• All-Weather Monitoring: Using SAR and InSAR for year-round surface monitoring

Repository: Water-Quality-Index-Analysis

• Objective: Monitor water quality parameters using satellite imagery across multiple river systems in North India
• Study Sites:
  • Mahananda River near Fulbari Barrage, Siliguri
  • Ganga River at three locations (Varanasi, Kanpur, Srerampur)
• Findings:
  • Demonstrated feasibility of satellite-based water quality monitoring
  • Identified significant seasonal variations in turbidity, TDS, and salinity between pre-monsoon and post-monsoon periods
  • Established reproducible workflows for operational water quality assessment
• Tools: Google Earth Engine (Python API), Geemap, Sentinel-2 imagery, Python (GeoPandas, Matplotlib)
• Techniques: NDWI/MNDWI for water body extraction, empirical algorithms for turbidity and TDS estimation, seasonal analysis

Repository: Sand Mining Impact Analysis

• Objective: Analyze sand mining effects on river morphology using satellite data and machine learning
• Findings:
  • Spatial-temporal degradation in sand bars and increased channel braiding
  • Identified water quality deterioration as critical consequence of sand mining
  • Achieved 90% accuracy in geomorphic feature classification using K-means clustering
• Tools: Google Earth Engine, ArcGIS, Python, Multi-source satellite data (PlanetScope, Sentinel-2)

• Objective: Analyze urban heat variations between Old Delhi, Athens, and Washington D.C.
• Findings: Land Surface Temperature (LST) differences due to urban morphology and aerosol interaction
• Tools: WRF Model, Python, GIS

• Objective: Investigate seismic activity and ground deformation using GPS and seismic data
• Tools: ObsPy, GMT, Python, IRIS Data

• Remote Sensing and GIS:

  • Introduction to SAR and Applications: NASA ARSET (2025)
  • InSAR Processing and Theory: EarthScope Consortium (2024)
  • Introduction to Hyperspectral Remote Sensing: EO College (2024)
  • Going Places with Spatial Analysis: ArcGIS (2024)
  • GIS for Climate Action: ArcGIS (2023)

• Machine Learning & Data Science:

  • Introduction to Machine Learning for Earth Observation: EO College (2024)
  • Python-Based Machine Learning: Theory to Practice: IIT Kanpur (2023)

• Seismology:

  • Seismology Skill Building Workshop: EarthScope Consortium - IRIS (2024)

• Satellite-Based Water Quality Monitoring for Climate Resilience:
  Develop operational frameworks for monitoring drinking water sources using multi-source satellite data (optical and SAR), integrating machine learning for real-time water quality assessment to support climate-resilient water treatment practices and decision support systems.

• Advanced Machine Learning for Water Quality Prediction:
  Implement deep learning models (CNN, LSTM, RNN) for multi-step forecasting of water quality parameters, enabling proactive management of drinking water treatment under extreme weather events and climate variability.

• Integration of Hydrological Models with Remote Sensing:
  Couple satellite-derived water quality data with hydrological models (SWAT, InVEST) to assess climate change impacts on water resources and develop comprehensive watershed-scale water management strategies.

• Multi-Source Data Fusion for Enhanced Monitoring:
  Integrate optical (Sentinel-2, Landsat) and radar (Sentinel-1) imagery with emerging missions (SWOT, GRACE-FO) for comprehensive water resource monitoring, overcoming limitations of single-sensor approaches.

• Integrating LiDAR and SAR for River Morphology:
  Utilize high-resolution LiDAR for volumetric quantification of river sediments and combine with SAR for tracking seasonal changes in river channels, providing accurate insights into anthropogenic impacts on fluvial systems.

• All-Weather Surface Monitoring with SAR:
  Develop methodologies incorporating Synthetic Aperture Radar (SAR) for year-round monitoring of river morphology and land deformation, overcoming limitations posed by cloud cover and seasonal variations.

• Seismic and Tectonic Stress Correlation:
  Explore relationships between seismic activity and tectonic stress release in the Himalayan region by integrating GPS, seismic data, and InSAR, providing insights into crustal deformation patterns and seismic hazards.

• Classical Music: A source of relaxation and focus
• Photography: Capturing moments, much like observing Earth through satellite data
• Cooking: Precision and creativity in the kitchen
• Science Quizzing: Former district quiz champion, staying sharp with scientific and critical thinking

Feel free to explore my projects and research. Let's connect!