Multiple factor regression analysis of vegetation changes and land degradation in drylands BASEF 2022

Multiple factor regression analysis of vegetation changes and land degradation in drylands

Presented at the Bay Area and International Science and Engineering Fairs in 2022.

The purpose of the study is to quantify the effect of various factors, including drought, precipitation, CO2 emissions, forest area, and electrical energy consumption, on the vegetation cover of various regions using multiple factor regression and identify measures that humans can take to increase the vegetation cover.

This project was really interesting to work on! At a certain point, I took my project notebook with me everywhere I went, including the grocery store, just in case a stroke of inspiration or an interesting idea would hit me. It was the kind of obsession that I really want to experience again. Every day, I encountered and worked through different challenges associated with finding appropriate data, data clean-up, choosing which algorithm to use, algorithm implementation, and data training. Working on the project was an incredibly motivating experience! Through it, I first discovered what the engineering design process and, particularly, its iterative nature looks and feels like.

If you would like a copy of the report, please don't hesitate to reach out!

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