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Optimize geometry retrieval and rendering while performing search, particularly for scenarios where there are a ton of points.
The 1st challenge is to reduce the amount of data returned by ML. One method is to use a geo heat map and aggregate the number of points per map section/box. Look into point clustering as well.
The 2nd challenge is to properly render the aggregate information as overlay elements in ArcGIS Pro. Investigate whether we can render text so we can show the frequency counts of aggregated areas or point clusters.
Clustering/aggregation should be a seamless experience. Potentially set a geometry count threshold (like 1000) that determines whether the search results will be clustered or be individual points.
Reference: EFS-73
The text was updated successfully, but these errors were encountered:
Optimize geometry retrieval and rendering while performing search, particularly for scenarios where there are a ton of points.
The 1st challenge is to reduce the amount of data returned by ML. One method is to use a geo heat map and aggregate the number of points per map section/box. Look into point clustering as well.
The 2nd challenge is to properly render the aggregate information as overlay elements in ArcGIS Pro. Investigate whether we can render text so we can show the frequency counts of aggregated areas or point clusters.
Clustering/aggregation should be a seamless experience. Potentially set a geometry count threshold (like 1000) that determines whether the search results will be clustered or be individual points.
Reference: EFS-73
The text was updated successfully, but these errors were encountered: