84 lines
2.4 KiB
Markdown
84 lines
2.4 KiB
Markdown
# Satellite Data Fusion Pipeline
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A Python pipeline for downloading, processing, and fusing Sentinel-2 and Sentinel-3 satellite imagery to generate high-resolution NDVI time series.
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## Features
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- **Data Download**: Downloads Sentinel-2 L2A (via AWS Earth Search) and Sentinel-3 OLCI (via OpenEO/Copernicus)
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- **Cloud Detection**: Identifies cloud-covered images using NDVI analysis
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- **EFAST Fusion**: Combines S2 and S3 data using the EFAST algorithm for enhanced temporal resolution
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- **NDVI Calculation**: Generates Normalized Difference Vegetation Index from raw and fused data
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- **Web Visualization**: Interactive web viewer for exploring NDVI time series and imagery
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## Installation
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```bash
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pip install -r requirements.txt
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pip install git+https://github.com/DHI-GRAS/efast.git
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```
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## Configuration
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Set environment variables for Copernicus Data Space authentication:
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- `CDSE_USER`: Copernicus Data Space username
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- `CDSE_PASSWORD`: Copernicus Data Space password
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## Usage
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```python
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from run import run_pipeline
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run_pipeline(season=2024, site_position=(47.116171, 11.320308), site_name="innsbruck")
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```
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The pipeline processes data in stages:
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1. Download S2/S3 imagery
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2. Generate NDVI from raw data
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3. Detect clouds
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4. Prepare data for fusion
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5. Run EFAST fusion
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6. Generate NDVI from fused outputs
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## Data Structure
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```
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data/
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{site_name}/
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{season}/
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raw/
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s2/ # Sentinel-2 GeoTIFFs
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s3/ # Sentinel-3 GeoTIFFs
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ndvi/ # NDVI from raw data
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prepared/
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s2/ # Prepared S2 data
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s3/ # Prepared S3 data
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fusion/ # EFAST fusion outputs
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ndvi/ # NDVI from prepared/fused data
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clouds.json # Cloud detection results
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```
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### File Formats
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**Sentinel-2 (raw/s2/)**: Multi-band GeoTIFF
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- Bands: B02 (blue), B03 (green), B04 (red), B8A (nir)
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- Metadata: `VIEWING_ZENITH_ANGLE` tag (degrees)
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- Filename: `{YYYYMMDD}_{increment}.geotiff`
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**Sentinel-3 (raw/s3/)**: Multi-band GeoTIFF
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- Bands: SDR_Oa04 (blue), SDR_Oa06 (green), SDR_Oa08 (red), SDR_Oa17 (nir)
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- Filename: `{YYYYMMDD}_{increment}.geotiff`
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## Web Viewer
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Run a local HTTP server from the **webapp** directory:
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```bash
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cd webapp
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python3 -m http.server 8000
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```
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Then open `http://localhost:8000/` in your browser. Data is served via the `webapp/data` symlink.
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## License
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This project is licensed under the GNU Affero General Public License v3.0 (AGPL-3.0). See the [LICENSE](LICENSE) file for details.
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