Hello there! I am Sohan Nag, a Geologist specializing in Remote Sensing, GIS, and Geospatial Analysis. My focus is on Earth Sciences, utilizing Machine Learning and advanced data processing for Fluvial Geomorphology and Seismic Analysis. Passionate about using InSAR and LiDAR technologies, I aim to contribute to cutting-edge research in environmental and geospatial sciences.
- Geospatial Data Analysis: Python (Pandas, NumPy, Scikit-learn), Google Earth Engine
- Remote Sensing: Optical & Radar Data Processing (SAR), DEM creation
- GIS Software: ArcGIS, QGIS
- Data Visualization: Geomorphological Mapping (ArcGIS, QGIS, Python), Seismic & GPS Data (GMT)
- Seismic Data Processing: ObsPy, SAC, TauP, FOCMEC
- Fluvial Geomorphology: River morphology, sediment dynamics, human impact on fluvial systems
- Machine Learning in Geosciences: Automating detection and analysis of geomorphic features
- Seismicity and Ground Deformation: Tectonic stress analysis using GPS and seismic data
- All-Weather Monitoring: Using InSAR for year-round surface and river morphology studies
- Climate Change Impact on Rivers: Linking climate factors to river dynamics and morphology
- Objective: Analyze sand mining effects on river morphology using satellite data
- Findings: Spatial-temporal degradation in sand bars, increased channel braiding, and anthropogenic impacts on river width
- Tools: Google Earth Engine, ArcGIS, Python (K-means for bar detection), SAR Data
- 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
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Remote Sensing and GIS:
- InSAR Processing and Theory: EarthScope Consortium (2024)
- Going Places with Spatial Analysis: ArcGIS (2024)
- GIS for Climate Action: ArcGIS (2023)
- Imagery in Action: ArcGIS (2023)
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Seismology:
- Seismology Skill Building Workshop: EarthScope Consortium - IRIS (2024)
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Machine Learning:
- Python-Based Machine Learning: Theory to Practice: IIT Kanpur (2023)
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Geospatial Data Science:
- Spatial Data Science: The New Frontier: ArcGIS (2023)
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Integrating LiDAR and SAR for River Morphology:
Utilize high-resolution LiDAR for volumetric quantification of river sediments and combine it with SAR for tracking seasonal changes in river channels, giving more accurate insights into anthropogenic impacts. -
All-Weather Surface Monitoring with SAR:
Develop methodologies to incorporate Synthetic Aperture Radar (SAR) for year-round monitoring of river morphology and land deformation, overcoming the limitations posed by cloud cover and seasonal variations. -
Advanced Machine Learning for Geospatial Analysis:
Further develop machine learning techniques (e.g., K-means, Random Forests) for automating the detection of geomorphic features and anomalies in large-scale satellite datasets, improving the efficiency and accuracy of geospatial research. -
Seismic and Tectonic Stress Correlation:
Explore the relationship between seismic activity and tectonic stress release in the Himalayan region by integrating GPS, seismic data, and InSAR, providing better insight into crustal deformation patterns and associated seismic hazards. -
Impact of Climate Change on River Dynamics:
Investigate how climate change is affecting river morphology by integrating hydrological models with remote sensing data to study changes in river flow, sediment transport, and channel behavior in response to varying climatic conditions.
- Classical Music: A source of relaxation and focus.
- Photography: Capturing moments, much like observing Earth through satellite data.
- Cooking: Developed an interest in 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!