diff --git a/.history/README_20250329005823.md b/.history/README_20250329005823.md new file mode 100644 index 0000000000000000000000000000000000000000..51dc2e942d9df8aeff69a9b2deb074305d545b5e --- /dev/null +++ b/.history/README_20250329005823.md @@ -0,0 +1,51 @@ +## TOAR-classifier v2: A data-driven classification tool for global air quality stations +This study develops a machine learning approach to classify 23,974 air quality monitoring stations in the TOAR database as urban, suburban, or rural using K-means clustering and an ensemble of supervised classifiers. The proposed method outperforms existing classifications, improving suburban accuracy and providing a more reliable foundation for air quality assessments. +<img src="./figures/toar_classifier_v2.png" alt="My image" with="200"> + +### Files +- `data` is the folder containing all the data used in this work, including the predictions of station categories from the Machine Learning (ML) model. +- `figures` contains all the figures. +- `TOAR-classifier_v2.ipynb` is the notebook containing the code. +- `requirements.txt` contains all the necessary packages. + +### Run the Code + +**Note:** This has been tested on Ubuntu 24.04. + +1. Install Python 3 if not already installed (most Linux systems have Python pre-installed). +2. Install Jupyter Notebook: + - `pip install notebook` (for Jupyter Notebook) or + - `pip install jupyterlab` (for JupyterLab). + +3. clone the project by running the following + - `git clone https://gitlab.jsc.fz-juelich.de/esde/toar-public/ml_toar_station_classification.git` + +4. Change directory to ml_toar_station_classification +- `cd ml_toar_station_classification` + +5. Creat virtual environment + - `python -m venv TOAR-classifier_v2` # feel free to change the virtual environment as convenient + +6. Activate the created venv + - `python -m ipykernel install --user --name=TOAR-classifier_v2 --display-name "Python (TOAR-classifier_v2)"` + +#### Install required package +1. open jupyter notebook, `jupyter-notebook` and select kernel `TOAR-classifier_v2` + +2. Install all the required packages for the project by uncommenting the first cell in the notebook and running the cell + +Run the code cell by cell. + + +### Citation + +If you use this please cite + +@article{Mache2025TOARClassifier, + author = {Ramiyou Karim Mache and Sabine Schröder and Michael Langguth and Ankit Patnala and Martin G. Schultz}, + title = {TOAR-classifier v2: A data-driven classification tool for global air quality stations}, + year = {2025}, + note = {Correspondence: Ramiyou Karim Mache (k.mache@fz-juelich.de)}, + url = {} +} + diff --git a/.history/README_20250329005842.md b/.history/README_20250329005842.md new file mode 100644 index 0000000000000000000000000000000000000000..2b227c1d0988338f25b1b528a6b2cb456e84b1cb --- /dev/null +++ b/.history/README_20250329005842.md @@ -0,0 +1,51 @@ +## TOAR-classifier v2: A data-driven classification tool for global air quality stations +This study develops a machine learning approach to classify 23,974 air quality monitoring stations in the TOAR database as urban, suburban, or rural using K-means clustering and an ensemble of supervised classifiers. The proposed method outperforms existing classifications, improving suburban accuracy and providing a more reliable foundation for air quality assessments. +<img src="./figures/toar_classifier_v2.png" alt="My image" with="200"> + +### Files +- `data` is the folder containing all the data used in this work, including the predictions of station categories from the Machine Learning (ML) model. +- `figures` contains all the figures. +- `TOAR-classifier_v2.ipynb` is the notebook containing the code. +- `requirements.txt` contains all the necessary packages. + +### Run the Code + +**Note:** This has been tested on Ubuntu 24.04. + +1. Install Python 3 if not already installed (most Linux systems have Python pre-installed). +2. Install Jupyter Notebook: + - `pip install notebook` (for Jupyter Notebook) or + - `pip install jupyterlab` (for JupyterLab). + +3. clone the project by running the following + - `git clone https://gitlab.jsc.fz-juelich.de/esde/toar-public/ml_toar_station_classification.git` + +4. Change directory to ml_toar_station_classification + - `cd ml_toar_station_classification` + +5. Creat virtual environment + - `python -m venv TOAR-classifier_v2` # feel free to change the virtual environment as convenient + +6. Activate the created venv + - `python -m ipykernel install --user --name=TOAR-classifier_v2 --display-name "Python (TOAR-classifier_v2)"` + +#### Install required package +1. open jupyter notebook, `jupyter-notebook` and select kernel `TOAR-classifier_v2` + +2. Install all the required packages for the project by uncommenting the first cell in the notebook and running the cell + +Run the code cell by cell. + + +### Citation + +If you use this please cite + +@article{Mache2025TOARClassifier, + author = {Ramiyou Karim Mache and Sabine Schröder and Michael Langguth and Ankit Patnala and Martin G. Schultz}, + title = {TOAR-classifier v2: A data-driven classification tool for global air quality stations}, + year = {2025}, + note = {Correspondence: Ramiyou Karim Mache (k.mache@fz-juelich.de)}, + url = {} +} + diff --git a/README.md b/README.md index dc2b813f58fe0bcb24960a82966416d6fce45c11..2b227c1d0988338f25b1b528a6b2cb456e84b1cb 100644 --- a/README.md +++ b/README.md @@ -21,13 +21,13 @@ This study develops a machine learning approach to classify 23,974 air quality m - `git clone https://gitlab.jsc.fz-juelich.de/esde/toar-public/ml_toar_station_classification.git` 4. Change directory to ml_toar_station_classification -- `cd ml_toar_station_classification` + - `cd ml_toar_station_classification` 5. Creat virtual environment - `python -m venv TOAR-classifier_v2` # feel free to change the virtual environment as convenient 6. Activate the created venv - -`python -m ipykernel install --user --name=TOAR-classifier_v2 --display-name "Python (TOAR-classifier_v2)"` + - `python -m ipykernel install --user --name=TOAR-classifier_v2 --display-name "Python (TOAR-classifier_v2)"` #### Install required package 1. open jupyter notebook, `jupyter-notebook` and select kernel `TOAR-classifier_v2`