Spatial Temporal Adaptive Reflectance Fusion Model (STARFM)

This is a short implementation of STARFM algorithm in Python language

Getting Started

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.

Prerequisites

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

Installing

Do this to install them

pip install numpy tqdm

Running the tests

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

Built With

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

Authors

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

License

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