Welcome to Geospaital Analytics in KNIME 101!

Geospatial Analytics is an increasingly essential field, as it allows us to extract valuable insights from location-based data, enabling better decision-making and problem-solving across a wide range of industries. With the Geospatial Analytics Extension for KNIME, you can leverage the full potential of both KNIME’s data analytics capabilities and the rich spatial analysis tools to unlock hidden patterns and relationships within your datasets.

  1. For laptops or PCs with Windows OS, the system typically has a “C drive” as the main hard drive partition:

    • after installation of KNIME, right click on knime.exe > Properties > Compatibility, check Run this program as an admistratror.
    • GAEK nodes may encounter failures caused by an unwritable issue in the System drive of the Python environment.
    • Then install Geospaital Analytics Extension for KNIME.

  2. The configuration of a GAEK node might become empty:

    • When the column number is excessively large and the GAEK node pre-reads the columns, leading to a time-consuming process of building the list.
    • This behavior has been observed with Lat/Lon to Geometry node.

  3. Some community extension can not be found:

    • If can not find the extension in the File > install KNIME extension....
    • Go to Help > Install New Software... > in the Dialog of Availabe Softeare, click Manage.. > check all site under Availabe Software Sites.

  4. Install KNIME Keras Integration:

    • create a new Python environment for CPU version with a name knimedlcpu > conda create -n knimedlcpu python=3.6 h5py=2.8 tensorflow-mkl=1.12 keras=2.2.4 pandas=0.25.3 -c conda-forge
    • create a new Python environment for GPU version with a name knimedlgpu > conda create -n knimedlgpu python=3.6 h5py=2.8 tensorflow=1.12 keras-gpu=2.2.4 pandas=0.25.3 -c conda-forge
    • Go to File > Preference > KNIME > Conda, use Browse to set Conda installation derectory ; under Python Deep Learning, check Keras, check Conda, choose knimedlcpu for Keras Conda environment.

  5. Install KNIME Geospatial Env:

    • create a new Python environment named geospatial_env with all pacakgesgeospatial pextension with a GitHub .yml file
    • In Anaconda Prompt, run as administrator, and input:
    • conda env remove -n geospatial_env
    • for local file: conda env create -f C:\DEV\GIT\EXTERNAL\knime-geospatial-extension\knime_extension\geospatial_env.yml
    • for online file: conda env create -f https://raw.githubusercontent.com/spatial-data-lab/knime-geospatial-extension/main/knime_extension/geospatial_env.yml

  6. Install KNIME Geospatial Env:

    • create a new Python environment named geospatial_env with all pacakgesgeospatial pextension with a GitHub .yml file
    • In Anaconda Prompt, run as administrator, and input:
    • conda env remove -n geospatial_env
    • for local file: conda env create -f C:\DEV\GIT\EXTERNAL\knime-geospatial-extension\knime_extension\geospatial_env.yml
    • for online file: conda env create -f https://raw.githubusercontent.com/spatial-data-lab/knime-geospatial-extension/main/knime_extension/geospatial_env.yml
  7. SSL: CERTIFICATE_VERIFY_FAILED in Installing Python Package in Anaconda:
    • if you encounter “connection error: [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed while installing python packages
    • In Anaconda Prompt, run conda config --set ssl_verify false
  8. Handle Long File Path issue for failure in installing KNIME extension
    • if you encounter error while installing some specific extension,it might be related to the Long File Path issue in Windows OS
    • Go to the website Source
    • copy the code, then input the code in the PowerShell console