Installing conda environments for spatial and remote-sensing analyses

Conda environments provide an easy way to install relevant packages for a python environment. Here, we present a ‘Spatial Data Analysis’ (SDA) environment that covers most relevant packages for point cloud and spatial-data analysis.

Install Spatial Data Analysis (SDA) relevant environment

conda create -y -n SDA python=3.10 pip scipy pandas numpy matplotlib scikit-image gdal ipython statsmodels jupyter pyproj lastools pdal pykdtree h5py plotly seaborn pytables pdal python-pdal scikit-learn jupyterlab numba jupyter-resource-usage geopandas rasterio xarray dask netCDF4 bottleneck lmfit xlrd -c conda-forge
conda activate SDA
pip install open3d laspy laszip jakteristics structure_tensor

This should install open3d-0.17.x. or newer.

You can additionally install spyder if required.

Make sure to add your conda environment to the Jupyter Notebook environment:

conda activate SDA
python -m ipykernel install --user --name=SDA

Install Mintpy

conda create -n mintpy -c conda-forge
conda activate mintpy
conda install -c conda-forge mintpy