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⚙️ Environment Setup for Dataset Download

To download and process datasets with Data4WA, you need a Python environment configured with common geospatial libraries such as GDAL, Rasterio, Xarray, and others.

Conda is a cross-platform environment manager that makes it easy to install geospatial libraries like GDAL.

Windows

  1. Download the Miniconda installer:
    👉 Miniconda Windows 64-bit
  2. Run the installer and choose “Add Miniconda to PATH” during setup.
  3. After installation, open Anaconda Prompt or Command Prompt and test:
conda --version

MacOS OS

  1. Download the installer for macOS from:
    👉 Miniconda macOS

  2. Run the installer

  3. Restart terminal and verify:

conda --version

2: Create a Conda Environment

conda create --name data4wa_env python=3.10
conda activate data4wa_env

3: Install GDAL and Geospatial Libraries

Use the conda-forge channel:

conda install -c conda-forge "gdal=3.10.*" libgdal-jp2openjpeg

Verify GDAL installation:

gdalinfo --version

Then install required Python libraries:

pip install pandas tqdm geopandas numpy xarray rioxarray rasterio netCDF4 requests beautifulsoup4  earthengine-api geemap planetary-computer pystac-client

4: Enable Jupyter Notebook Support (Optional)

conda install -c conda-forge notebook ipykernel
python -m ipykernel install --user --name=data4wa_env --display-name "Python (data4wa_env)"

To select the environment kernel in Jupyter: Kernel → Change Kernel → Python (data4wa_env)

Optional Cleanup: If you ever want to remove the kernel, use: 

jupyter kernelspec uninstall data4wa_env