SDM Climate Mapping

About the project

This was a passion project of mine that aimed to combine science and conventional machine learning tools to create a visual representation of how a pest species distribution can spread due to the effects of climate change.


The target species for this project was Spodoptera frugiperda - the fall armyworm.


The fall armyworm is a Lepidopteran pest that feeds on many food crop species. This species have been responsible for losses totalling more than $9 billion per year in Africa alone.


The project was divided into four large parts: data collection, modelling, analysis and visualization. Leaflet maps were created for predictions in 2040, 2070 and 2100 for SSP126, SSP370 and SSP585 climate scenarios.

Tech stack for this project

To complete this project, I made use of the following software, programs and libaries:

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Python

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HTML

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CSS

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JavaScript

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Bootstrap

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D3

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Leaflet

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Git & GitHub

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R

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SciKit Learn

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QGIS

Demo

You can check out the site created for this project here.


The site is hosted on GitHub pages, as such, it may load slowly. While you are waiting, you can check out the code for this project, or head back to my projects and check out the summary for another one.