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03 Create Grid with GAUL and Visualize Feature Collection

Spatial Data LabHarvard UniversityGoogle Earth Engine
Center for Geographic Analysis at Harvard University profile image
Draft Latest edits on 
Aug 12, 2024 6:47 PM
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This KNIME workflow processes and visualizes geographic data from the GAUL (Global Administrative Unit Layers) map. The workflow includes steps to filter the map data for the state of Massachusetts (MA) in the USA, visualize the filtered features, create a grid overlay, and visualize the grid.

Workflow Steps
GAUL Map: Reads the GAUL map data.
Function: This node imports the GAUL map, which contains global administrative boundaries.

Feature Filtering: Filters the GAUL map data.
Function: This node filters the GAUL map to extract the features corresponding to Massachusetts (MA), USA. The filtering criteria focus on selecting the specific administrative unit.

GEE Feature Visualization : Visualizes the filtered features.
Function: This node visualizes the filtered feature, allowing users to inspect the map data specifically for Massachusetts. The visualization helps in verifying the filtering process.

Create Grid From Feature: Creates a grid overlay from the filtered features.
Function: This node generates a grid overlay on the filtered Massachusetts feature. The grid can be used for various spatial analyses, such as sampling or spatial statistics.

This workflow demonstrates the process of reading, filtering, and visualizing GAUL map data within KNIME. It highlights how to isolate specific geographic features, such as Massachusetts, and apply a grid overlay for enhanced spatial analysis.

Created By:
Lingbo Liu
lingboliu@fas.harvard.edu
Spatial Data Lab project
Center for Geographic Analysis
Harvard University
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Used extensions & nodes

Created with KNIME Analytics Platform version 5.3.0
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    KNIME Python IntegrationTrusted extension

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