Added basic README.md.

README.md

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+# Satellite Data Fusion Pipeline
+
+A Python pipeline for downloading, processing, and fusing Sentinel-2 and Sentinel-3 satellite imagery to generate high-resolution NDVI time series.
+
+## Features
+
+- **Data Download**: Downloads Sentinel-2 L2A (via AWS Earth Search) and Sentinel-3 OLCI (via OpenEO/Copernicus)
+- **Cloud Detection**: Identifies cloud-covered images using NDVI analysis
+- **EFAST Fusion**: Combines S2 and S3 data using the EFAST algorithm for enhanced temporal resolution
+- **NDVI Calculation**: Generates Normalized Difference Vegetation Index from raw and fused data
+- **Web Visualization**: Interactive web viewer for exploring NDVI time series and imagery
+
+## Installation
+
+```bash
+pip install -r requirements.txt
+pip install git+https://github.com/DHI-GRAS/efast.git
+```
+
+## Configuration
+
+Set environment variables for Copernicus Data Space authentication:
+- `CDSE_USER`: Copernicus Data Space username
+- `CDSE_PASSWORD`: Copernicus Data Space password
+
+## Usage
+
+```python
+from run import run_pipeline
+
+run_pipeline(season=2024, site_position=(47.116171, 11.320308), site_name="innsbruck")
+```
+
+The pipeline processes data in stages:
+1. Download S2/S3 imagery
+2. Generate NDVI from raw data
+3. Detect clouds
+4. Prepare data for fusion
+5. Run EFAST fusion
+6. Generate NDVI from fused outputs
+
+## Data Structure
+
+```
+data/
+  {site_name}/
+    {season}/
+      raw/
+        s2/          # Sentinel-2 GeoTIFFs
+        s3/          # Sentinel-3 GeoTIFFs
+        ndvi/        # NDVI from raw data
+      prepared/
+        s2/          # Prepared S2 data
+        s3/          # Prepared S3 data
+        fusion/      # EFAST fusion outputs
+        ndvi/        # NDVI from prepared/fused data
+      clouds.json    # Cloud detection results
+```
+
+## Web Viewer
+
+Run a local HTTP server to view the web interface:
+
+```bash
+cd webapp
+python3 -m http.server 8000
+```
+
+Then open `http://localhost:8000/webapp` in your browser to visualize NDVI time series and compare S2, S3, and fusion outputs.
+