GitHub - ITU-GeoAI-Challenge/GEO-AI-Challenge-for-Cropland-Mapping-Challenge: This repository contains all the deriverables for username JuliusFx ranked position 12 at the close of the competition

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This repository contains all the deriverables for username JuliusFx ranked position 12 at the close of the competition

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Name		Name	Last commit message	Last commit date
Latest commit History 5 Commits
1. bRequirements.txt		1. bRequirements.txt
1.a) Data Extraction Prep -Split Into Countries.ipynb		1.a) Data Extraction Prep -Split Into Countries.ipynb
1.b) Data Extraction - Final Step_(NOT COLAB).ipynb		1.b) Data Extraction - Final Step_(NOT COLAB).ipynb
1.c) VISUALIZATION.ipynb		1.c) VISUALIZATION.ipynb
2.e) GRIDSEARCHED - 0.913.ipynb		2.e) GRIDSEARCHED - 0.913.ipynb
ACCESSING GOOGLE EARTH.txt		ACCESSING GOOGLE EARTH.txt
GEO-AI Challenge for Cropland Mapping by ITU.pptx		GEO-AI Challenge for Cropland Mapping by ITU.pptx
README.txt		README.txt
Test.csv		Test.csv
Train.csv		Train.csv
technical report.pdf		technical report.pdf

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Order of Executing the .ipynb Files:

1.Ensure you are working in the Anaconda environment on your PC. All files provided for this work should be in same location


2.Begin by running the "1.a) Data Extraction Prep -Split Into Countries.ipynb" file first.


-This step is necessary to generate the each country's train and test csv files, which are used in the subsequent "1.b) Data Extraction - Final Step_(NOT COLAB).ipynb" file.

3. Proceed to run the "1.b) Data Extraction - Final Step_(NOT COLAB).ipynb" file.

-This step is necessary to pull sentinel bands for each country for both train and test files 


4. Proceed to run the "2.e) GRIDSEARCHED - 0.913.ipynb" file.


5. For the final submission on Zindi, use the output from the last step, specifically the "1.lgbm.csv".