ektoravlonitis / satellite-based-rice-crop-yield-prediction

Rice Crop Yield Estimation Using Satellite Data - EY Open Science Data Challenge 2023

Rice Crop Yield Estimation Using Satellite Data

Overview

This project focuses on building a machine learning model to estimate rice crop yield using satellite data in the An Giang province of Vietnam. The primary objective of this study was to leverage the European Copernicus (Sentinel-1) program and NASA's Landsat program to track the location and growth of rice crops, and subsequently predict their productivity. By integrating satellite data, weather data, and advanced analytics, we aimed to achieve a deeper understanding of rice crop phenology and provide essential information for agricultural decision-making, resource allocation, and policy formulation.

Folders Explanation

Scripts

The "Scripts" folder contain all the python files used for the data extraction, database creation and the models used.

Data

The "Data" folder contains all the obtained data.

BI

The "BI" folder contains the PowerBI data visualization.

WebApp

The "WebApp" folder contains the ideas used for our website creation.

Documentation

The "Documentation" folder contains the report of the project.