Resampling and Composite Processing for Himawari Satellite Data

Overview

This project processes Himawari satellite imagery using SatPy for tasks like resampling, cropping, aggregating, and generating composite images. It enables efficient analysis of meteorological satellite data by unifying resolutions, extracting key features, and visualizing RGB composites.

Features

• Resampling: Standardizes image resolution across multiple channels.
• Cropping: Extracts specific regions for targeted analysis.
• Aggregation: Merges data over time or space for improved clarity.
• RGB Composite Generation: Enhances visualization of meteorological data.
• Automated Image Saving: Saves processed images as PNG files for further use.

Requirements

• Python
• SatPy
• Cartopy
• Rasterio
• Dask

Usage

1. Mount Google Drive and install dependencies.
2. Load Himawari satellite data using SatPy.
3. Perform resampling, cropping, and aggregation.
4. Generate RGB composite images.
5. Save processed images for further analysis.

Data Source

Himawari Satellite Data (Google Drive)

This project provides a streamlined approach for analyzing meteorological satellite images efficiently.