Welcome to my professional portfolio of GIS models and real-world project workflows. This repository contains automation models built in QGIS and problem-driven GIS project solutions focusing on habitat mapping, tree health management, and cloud polygon image processing.
I specialize in:
- 🚀 QGIS Model Builder Automation: Custom-built models to eliminate repetitive tasks and reduce human error.
- 🛰️ Remote Sensing-Based Image Processing: Automating downloads, buffering, and filtering of satellite images.
- 🌿 Ecological Mapping & Habitat Classification: Generating AI-ready datasets with consistent attribution logic using SOP + code tables.
- 🌳 Tree Health & Hazard Analysis: Detecting vegetation threats using multi-angle satellite images with QC/QA insights.
- 🗂️ PostGIS-Backed Workflows: Efficient spatial database management for large-scale, multi-layer GIS operations.
models/: Custom QGIS models for automated image downloading and cloud maskingprojects/: GIS project documentation with problems tackled, workflows used, and results- Each folder includes a
model_description.mdorreport.mdwith all technical details
Automates the classification of habitats using models based on SOP and code tables.
Interpretation of tree health using satellite imagery and QC insights.
QGIS model to auto-download and process cloud-covered imagery areas.
Buffered span-level QGIS model to automate high-resolution image extraction.
| Domain | Stack / Tools |
|---|---|
| GIS Automation | QGIS Model Builder, Python (PyQGIS), Batch Scripting |
| Spatial DB | PostGIS, PostgreSQL |
| Image Analysis | Maxar, UP42, Sentinel, GSAT, Raster Processing |
| Data Science | GeoPandas, Shapely, Field-Verified Pipelines |
| AI Integration | Code4Habitat, Segment Anything (SAM), Labeling |
This project is licensed under the MIT License.
“Precision is not just a metric, it’s the mindset that shapes every spatial decision.”
📫 Let’s collaborate or connect! Reach me at: rsanthosh.geo@gmail.com
🌐 LinkedIn | GitHub