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Geospatial View

Geospatial Geospatial Analytics Visualization Map Release 4.7
Center for Geographic Analysis at Harvard University profile image

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In this example, we want to visually represent the population distribution by ethnic identification in the city of New York. We get this information from the US2020 Census, where people can place themselves into the following categories: White, African American, Latino, Asian and Native American. The goal here is to generate a Geographic Heatmap to easily visualize the composition of the Manhattan inhabitants by their ethnic identification. We use the Geospatial View node to create this visual map and KNIME nodes to build a dynamic data application where you can select the percentage of people of one ethnic identity over the total, to see how they are geographically distributed. Geospatial Analytics is fully developed in Python, e.g. the Geopandas library, which was heavily used to write the nodes. All the nodes provided with the extension are the perfect toolkit to apply geospatial technologies in a no-code/low-code way, so also beginners can benefit from this kind of analysis.

External resources

  • Request US Census API key (for free)
  • Geoandas Documentation
  • Center for Geographic Analysis

Used extensions & nodes

Created with KNIME Analytics Platform version 4.7.0
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    Geospatial Analytics Extension for KNIME Trusted extension

    SDL, Harvard, Cambridge US

    Version 1.0.0

    Center for Geographic Analysis at Harvard University profile image
    Center for Geographic Analysis at Harvard University
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    KNIME Base nodes Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.7.0

    knime
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    KNIME Math Expression (JEP) Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.7.0

    knime
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    KNIME Quick Forms Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.7.0

    knime
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