This tool integrates the satellite image download method officially provided by the Himawari satellite. It filters the required latitude and longitude, and downloads the images in batches.

• Integrates with the Himawari satellite image download service.
• Allows filtering by specific latitude and longitude coordinates.
• Downloads Images of Band 03 (0.64 μm) gridded resolution Images 0.005 degree (approx. 500 m) in batches .

• Python 3.6
• ext.01 file (Conversion count value into tbb)
• downloads.txt (The time period you want to download Ex: yyyymmdd(StartTime) yyyymmdd(EndTime))

1. Clone the repository:

   git clone https://github.com/Alanlee0323/Clone_Hiwamari_Images.git
   cd Clone_Hiwamari_Images
   

1. Run the script to start downloading images:

   python HIwamari_get.py

The latitude and longitude adjustments are made within the process_data function in the script. Specifically, you need to modify the following variables:

• start_row: The starting row index in the data grid. This corresponds to latitude.
• end_row: The ending row index in the data grid. This also corresponds to latitude.
• start_column: The starting column index in the data grid. This corresponds to longitude.
• end_column: The ending column index in the data grid. This also corresponds to longitude.

These adjustments allow you to specify the precise geographical area for data extraction. It's essential to understand the relationship between row and column indices and latitude and longitude coordinates in the data grid.

The byte conversion process is integral to the script, particularly in the read_data_range function. Here's a brief explanation of the byte conversion process:

• The satellite data is stored in a binary format, where each data point (e.g., temperature, humidity) is represented by a certain number of bytes.
• The read_data_range function reads the binary data from the satellite files and extracts the relevant data points based on the specified row and column indices.
• The byte conversion process involves reading the bytes corresponding to the selected data points and converting them into a human-readable format (e.g., floating-point numbers representing temperature values).
• By understanding the byte conversion process, you can interpret the extracted data accurately and effectively.

Below are two illustrations to help you understand the latitude and longitude adjustments and the byte conversion process:

Latitude and Longitude Adjustments:

Byte Conversion Process:

See the bands and sampling gradations from Himawari satellite

These illustrations visually demonstrate how to adjust latitude and longitude indices and the byte conversion process, aiding in your understanding of the script's functionality.

Feel free to fork this repository, make changes, and submit pull requests. Contributions are always welcome.

This project is licensed under the MIT License. See the LICENSE file for details.

• Thanks to the Himawari satellite team for providing the satellite images.
• This tool utilizes the download methods provided at Himawari Quick Looks.