Land Cover Classification Random Forest

Last update: Jan 21, 2022

Overview

Land_Cover_Classification_Random_Forest

You can perform Land Cover Classification on Satellite Images using Random Forest and visualize the result using Earthpy package. Make sure to install the required packages and such as

pip install gdal pip install earthpy

These packages require C++ build dependencies so be sure to install Visual C++ 14.0 or higher. If you want to avoid all hussle of installing packages then just opt for Google Colab. Be sure to upload images and ground truth file from The Sundarbans Dataset (https://earthdata.nasa.gov/worldview/worldview-image-archive/the-sundarbans). For ease I am also uploading the data with this repository

Owner

Dr. Sander Ali Khowaja

Assistant Professor, Department of Telecommunication, Faculty of Engineering and Technology.

GitHub Repository

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Land Cover Classification Random Forest

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Overview

Land_Cover_Classification_Random_Forest

Owner

Dr. Sander Ali Khowaja

A Lucid Framework for Transparent and Interpretable Machine Learning Models.

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