Spatial Aggregation
Explore the concept of spatial aggregation using GeoPandas to group and summarize geographic data by attributes. Learn how to create coarser-scale spatial units like regions from finer data such as states, and apply aggregation functions to analyze variables like population. This lesson helps you simplify complex spatial datasets and identify broader patterns through effective geoprocessing.
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Spatial aggregation is the process of grouping or combining spatial features based on a common attribute and aggregating the values of other attributes within each group. In many cases, spatial data may be more granular than what is needed for the analysis at hand. So, spatial aggregation involves combining finer geographic areas into larger units based on some criterion and then summarizing the data for each unit.
For example, if we have data on census tracts, but we’re actually interested in studying patterns at the level of zip codes or counties, we may need to aggregate the data to a coarser scale to make it more meaningful. By aggregating the data to a coarser scale, such as neighborhoods or counties, we ...