Has anybody else had issues with the screening widget report returning bizarrely high area sums? I'm currently in the configuration stage of a web app and am doing some testing with various zipped shapefile areas of interest (AOI). One ~300 hectare AOI polygon is returning an overlap of 17 million hectares for one of my feature layer categories (4 classes, the other 3 classes return expected results). It's not isolated to a single feature layer either - other feature layers from different source data are also returning oddball results (58K ha overlap on a 120ha polygon, 6K ha overlap on a 250 ha polygon, all different input feature layers). These weird results also happen when I draw an AOI instead of uploading a shapefile. In most cases (but not all), the high area sum is much higher than the total area of all features in the feature layer (i.e. one feature layer totals ~3.5 million ha, but I'm getting 17 million ha returned for a single class within the data). I have been over the source data with a fine-tooth comb and it's as clean as it can be, so I suspect that I'm either configuring something incorrectly or there is either something up with the screening widget itself. I've tried the following with no luck: Reprojected the source data to web Mercator prior to publishing the feature layer Reprojected the AOI shapefiles to web mercator prior to using in the screening widget Run topology on all my source data to ensure no overlaps Re-indexed the spatial index of the source data & republished the feature layer Dissolved the data on the class field to have less features in the feature layer Deleted published feature layer and published a fresh feature layer Split out data with a definition query on the source and published a single-class feature layer – feature layer still gives incorrect area sum Exported the features for a single class into a new feature class and published this as a feature layer Simplified the data (collapsed vertices within 10m) Removed all other feature layers from the screening widget Diced the data with a max 1000 vertices Diced the data with a max 500 vertices Uploaded the fgdb to AGO and made feature layer Uploaded a subset of the data to AGO and made a feature layer The screening widget looks like it has fantastic potential, but if I can't rely on the results I'll have to look at other ways to get a similar output. If anyone has any thoughts on other things I could try to make the screening widget results more reliable for my data, I'm all ears. I've attached a sample PDF output showing the anomalies.
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