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This problem statement focused on building machine learning models that would assist create city-level air pollution susceptibility maps with a 5-meter spatial resolution for milan city in Italy. This city has unique challenges of dealing with pollution levels due to its unique topographic features.

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JuliusFx131/GeoAI-Challenge-for-Air-Pollution-Susceptibility-Mapping

 
 

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GeoAI-Challenge-for-Air-Pollution-Susceptibility-Mapping

Submissions for username JuliusFx for the above ITU problem statement

This repository contains the following files

  1. Technical Report - gives the summary of the model developed

  2. main.ipynb- the jupyter notebook used to generate the predictions

  3. The datasets provided

    a) Train.csv-contain train features (this file is big cannot upload here-- download from data section of page url provided below)

    b) Test.csv-we are supposed to predict the aqi values for the 160 location in the city of milan

    c) air_pollution_Milan_Comune_topo_only.csv-contains topological features for the city of milan

    d) Interpolated seasonal datasets from the city of milan from a regular grid

      i) meteo_autumn_2022
    
      ii) meteo_spring_2022
    
      iii) meteo_summer_2022
    
      iv) meteo_winter_2022
    
  4. requirements.txt- has the module version required to run the notebook successfuly

  5. lgb_sub.csv - contains the predictions for our proposed model

Order of Running the Files

  1. Ensure all files are residing in the same folder. I run them on conda environment in my computer

  2. Install the models in requirements.txt

  3. Run main.ipynb-should be able to generate the lgb_sub.csv file

To view the competition page where you can get more information on the problem statement, please visit: https://zindi.africa/competitions/geoai-challenge-for-air-pollution-susceptibility-mapping

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This problem statement focused on building machine learning models that would assist create city-level air pollution susceptibility maps with a 5-meter spatial resolution for milan city in Italy. This city has unique challenges of dealing with pollution levels due to its unique topographic features.

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  • Jupyter Notebook 100.0%