Pale Blue Dot: Climate Visualization Challenge
Published:
Overview
Honorable Mention from NASA, UNVIE, and UNOOSA for creating a compelling visualization using Earth observation data to advance UN Sustainable Development Goal 13: Climate Action.
Project Description
Annual climate trends visualization in Los Glaciares National Park, Argentina (2013-2024) revealing:
- Rising temperatures: Positive slope in surface temperature trends
- Diminishing snow cover: Decreasing percentage indicating climate change impact
- Comprehensive analysis: Using Landsat Collection-2 Level-2 data from Landsat 8/9 OLI/TIRS satellites
The visualization demonstrates the tangible effects of climate change on glacial ecosystems through multi-year satellite imagery analysis.
Key Features
- Automated satellite image processing pipeline with CLI tools
- Multi-spectral analysis: temperature, true color, NDSI, and binary snow cover
- Cloud detection and filtering (0-50% cloud cover threshold)
- ROI-based analysis using GIS shapefiles
- Temporal trend analysis across 11 years of data
Technologies Used
- Python 3.10+
- Poetry (dependency management)
- GDAL 3.4.1 (geospatial data processing)
- Matplotlib (visualization)
- Jupyter Notebook (interactive analysis)
- Landsat 8/9 Collection-2 Level-2 (USGS EarthExplorer)
Impact
Contributes to understanding climate change effects on glacial ecosystems and supports UN SDG 13: Climate Action by providing visual evidence of environmental transformation over time.
Recognition
Honorable Mention - NASA, UNVIE, and UNOOSA for advancing UN Sustainable Development Goals through Earth observation data visualization.
Links
- GitHub Repository: https://github.com/cristianrubioa/pale-blue-dot-challenge
- Challenge: DrivenData Competition
- License: MIT