This is a short implementation of STARFM algorithm in Python language

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Here are some dependencies to make this project work. Numpy for the matrix computation. While, tqdm only to beautify this project processing time :) .

Numpy
tqdm

Do this to install them

pip install numpy tqdm

To start your first prediction, change these three line in compute.py according to your input filenames

Lkpixel = "WV_blue_1812.txt"
Mkpixel = "L8_blue_0701.txt"
M0pixel = "L8_blue_0411.txt"

then, change the pixel dimension variable according to your input pixel here in compute.py and write.py

pixel_dimension = 1125

Then, run this to predict

python compute.py

• Numpy - Scientific computation support
• tqdm - Used to generate progress bar
• ArcGIS - Data source and preparation

• Hari Setiawan - Implementation Detail
• Karisma Rizkika - Original ideas

This project is licensed under the MIT License - see the LICENSE.md file for details