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How to perform spatial join

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Spatial joins are a fundamental GIS operation that combines spatial data from two datasets based on their geographic relationship. This process is essential for tasks like analyzing proximity, aggregating attributes, or combining different layers of geographic information. With Atlas, performing a spatial join is intuitive and requires no advanced technical knowledge.

This guide will walk you through the steps to perform and customize spatial joins using Atlas.

What is a Spatial Join?

A spatial join is a process of merging attributes from one layer to another based on their spatial relationship. For example, you might join data about population demographics to geographic areas like districts or identify points that fall within specific boundaries. Spatial joins are especially useful for spatial analysis in urban planning, environmental studies, and market research.

Step 1: Log In to Atlas

Log in to your Atlas account and open an existing map or create a new project by selecting Create Project. This will take you to the map editor, where you can start preparing your datasets for the spatial join.

Step 2: Prepare and Upload Your Data

To perform a spatial join, you’ll need two datasets:

  • Target Layer: The layer where attributes will be added (e.g., points or polygons).
  • Join Layer: The layer containing the attributes to be joined (e.g., boundaries or zones).
  1. Upload your data: Click Add Data in the map editor to upload your files. Atlas supports formats like CSV, GeoJSON, Shapefiles, and Geopackage.
  2. Verify your data: Check that both layers are displayed correctly on the map and that their geometries (points, lines, or polygons) align as needed for the spatial join.

Step 3: Initiate the Spatial Join

  1. Select the Target Layer: Click on the layer where you want the joined attributes to appear in the Layers Panel.
  2. Choose Spatial Join: From the layer options or tools menu, select Spatial Join.
  3. Define the Join Relationship: Specify how the spatial relationship will be determined, such as:
  • Intersect: Joins attributes if geometries overlap.
  • Within: Joins attributes if one geometry is entirely within another.
  • Touches: Joins attributes if one geometry shares a boundary or point with another.
  • Crosses: Joins attributes if one geometry crosses through another.
  • Equals: Joins attributes if two geometries are identical in shape and location.
  • Overlaps: Joins attributes if two geometries partially cover each other.

Atlas will process the join and add the attributes from the join layer to the target layer.

Step 4: Visualize and Analyze the Results

Once the spatial join is complete, the combined data will appear in your target layer. Use the map editor’s tools to visualize and analyze the results:

  • Style the joined data to highlight patterns or trends.
  • Use thematic mapping to categorize features based on their newly joined attributes.
  • Analyze relationships, such as the density of points within polygons or the average value of attributes within zones.

Step 5: Share Your Spatial Join Results

After analyzing your spatial join results, share them with collaborators by generating a link, exporting the map as an image or PDF, or embedding it on a website.

Practical Applications of Spatial Joins

Spatial joins have diverse applications across industries:

  • Urban Planning: Analyze population density within city zones or identify areas lacking public services.
  • Retail: Link customer data to store locations for targeted marketing.
  • Environmental Studies: Associate pollution readings with watershed boundaries or land use zones.
  • Transportation: Match accident data to specific road segments or intersections.
  • Real Estate: Combine property data with neighborhood characteristics for market analysis.

Tips for Effective Spatial Joins

  • Ensure both datasets use the same coordinate reference system (CRS) to avoid misalignment.
  • Simplify your data by removing unnecessary attributes before performing the join.
  • Double-check the spatial relationship criteria to ensure accurate results.

By following this guide, you’ll be able to perform spatial joins in Atlas to uncover insights and make data-driven decisions across various fields.