ArcGIS Pro

Transform Dynamically Aggregated Time Series Results into Polygons in ArcGIS

This is a continuation of another blog post where I described how to compute aggregated results such as totals and averages from a time series table and show them at the point locations where those values were measured. These results are helpful in many analyses. But there are cases where it is required to visualize them using polygon features. For example, if you are an emergency management professional, you may want to know which counties have the most rainfall; whereas if you’re a scientist, you may want to see the same result but aggregated into watershed boundaries/catchment areas instead.

Weighted total rainfall computed for each county from rainfall stations
Weighted total rainfall computed for each county from rainfall stations

When it comes to transforming results from points to polygons, naturally we think of a simple spatial operation—such as a Contains or a Within operation—to (a) find all points that fall within a polygon feature and (b) use those features to compute the result. This simple approach works well with discrete data, such as computing total sales from all point locations at the state or county level. But this does not work for analyses with sampled data such as rainfall measurements. If you were to do that, you’d get a map, like the one below, where counties with no rainfall stations are not even drawn on the map — basically the map says there were no rain in those counties! That is not true, right?

Simple spatial operation produces incorrect map with missing counties
Simple spatial operation produces incorrect map with missing counties

To avoid that problem and produce an accurate map, we will use Thiessen polygons to compute the rainfall distribution in our area of interest. Such result can be achievable by executing some geoprocessing tools, but that produces result only for one time slice. Every time you want to see result for a different time slice, you need to rerun those tool. This blog post provides step-by-step instructions that overcomes geoprocessing tools limitations – makes the result map reactive to time slider’s current time and still computes aggregated results, such as total rainfall dynamically from a time series table.

Prepare the Data

Let’s get started:

Visualize Weighted Total Rainfall at the County Level

Next, we’ll add a query layer:

Edit Query Layer dialog with a range parameter
Edit Query Layer dialog with a range parameter
Definition a range parameter
Defining a range parameter
Map on the left showing total rainfall at point locations. Map on the right shows same result transformed to county boundaries
Map on the left showing total rainfall at point locations. Map on the right shows same result transformed to county boundaries

Visualize Weighted Total Rainfall for Watersheds

If you want to visualize the weighted total rainfall for watersheds instead of county boundaries, all you need to do is to repeat steps from the previous section but with a watershed layer. Let’s create another query layer with the following SQL query:

SELECT w.objectid, w.huc8, w.Shape, rh.rainfall_w AS Weighted_Total_Rainfall
FROM USGS_HUC8_WATERSHEDS_IL w
INNER JOIN
(
SELECT huc8, (sum(r.rainfall_inch * c.areasqkm) / sum(c.areasqkm)) as rainfall_w
FROM USGS_HUC8_thsn_intsct_il c
INNER JOIN
(
SELECT site_no, Sum(rainfall_inch) AS rainfall_inch
FROM USGS_RAINFALL_TIMESERIES_IL
WHERE ::r:dateRange
GROUP BY site_no
) AS r
ON r.site_no = c.site_no
GROUP BY c.huc8
) AS rh
ON w.huc8 = rh.huc8

Map on the left showing total rainfall at point locations. Map on the right shows same result transformed to watershed boundaries
Map on the left showing total rainfall at point locations. Map on the right shows same result transformed to watershed boundaries

Share and Consume Data in Web Maps

You can share the map as a map image layer (or map service).

About the author

Tanu is a product engineer on Esri Mapping Team focusing on map service, print service, and ArcGIS Pro. He also works on spatio-temporal analysis, spatial aggregation and real-time data. Tanu’s background includes a masters in Urban Planning from University of Akron, Ohio, USA and a bachelor degree from Khulna University, Bangladesh, and worked as GIS Coordinator in City of West Springfield, and GIS Specialist in a hydrology modeling center in Bangladesh before joining Esri in 2007.

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