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b-yogesh authored Oct 4, 2020
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This project was developed by a diverse team of coders, ML enthusiasts, story-tellers and UI/UX developers as a part of submission for the [NASA's SpaceApp Challenge 2020 Hackathon](https://www.spaceappschallenge.org/)

![L L O C U S T_Logo](https://user-images.githubusercontent.com/22027039/95028169-99ced300-069e-11eb-9f1c-0b7dbad9f120.png)

## Overview
Project L.L.O.C.U.S.T identifies and predicts the probability of locust invasion as well as forecast locust’s movements in vulnerable areas. Using a machine learning model trained on satellite data of wind, humidity, surface temperatures, and vegetation index, -- all of which are factors that promote locust population – we attune L.L.O.C.U.S.T. to create a heat map of areas that are most at risk of locust infestation. Through the use of an interactive, user-friendly website, farmers, city-officials, and businesses alike are able to view our models predictions in the form of an interactive map.

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