A cost-effective, real-time Earth observation system using publicly accessible satellite signals and open source technologies.
Earth-Lens presents the design and implementation of a complete system for acquiring and enhancing real-time Earth imagery transmitted by NOAA (National Oceanic and Atmospheric Administration) weather satellites — specifically NOAA 15, NOAA 18, and NOAA 19 — via their Automatic Picture Transmission (APT) signals.
Utilizing publicly available WebSDR platforms and open-source decoding tools, analog APT signals are captured, processed, and converted into visible satellite images.
- Capture: NOAA APT signals are received from WebSDR sources.
- Decoding: Signals are processed through open-source decoding tools to reconstruct visible imagery.
- Noise Reduction: Implemented using Gaussian and Median filtering.
- Line Reconstruction: The Hough Transform is used to detect and repair corrupted line segments in the imagery.
- Contrast Optimization: Enhancement techniques improve overall visual clarity of received images.
- K-Means Clustering: Applied to classify and segment key geographic features such as:
- Land
- Water bodies
- Cloud formations
The Earth-Lens system provides practical exposure to satellite communication and remote sensing, while promoting a cost-effective approach to Earth observation using publicly accessible technologies.
- Supports learning in fields like signal processing, image enhancement, and geospatial analysis.
- Enables weather monitoring, environmental change detection, and geographic visualization for research and analysis.
- Integration with real-time decoding pipelines using SDR hardware or WebSDR APIs.
- Implementation of AI-based segmentation models (e.g., U-Net) for improved accuracy.
- Addition of georeferencing modules to map decoded imagery onto real-world coordinates.
- Expansion toward multi-satellite data fusion for enhanced environmental analytics.
Earth-Lens bridges the gap between satellite signal acquisition, image processing, and geospatial analysis, demonstrating that open-source tools and accessible technologies can be harnessed for meaningful Earth observation and educational innovation.