Hello, I am building a data pipeline that ingests a table of latitude/longitude coordinates and plots them on a map. All data points are located in Santa Monica, CA.
Here are some sample coordinates from the input table.
If I treat these values as decimal degrees, then the first row would be 34.01244, -118.29456. This plots the value far away from Santa Monica.
If I treat these values as degrees, minutes, seconds (DMS) data, then the first row would be 34° 01' 24.4", -118° 29' 45.6". Converting that value from DMS to DD gives me 34.02011, -118.496. This plots in Santa Monica BUT results in a strange clustered pattern on the map. Notice how all of the points are clustered in 'L' shapes near the intersections.
Does anyone have any idea what might be going on and how I can best convert the values into usable data? I have attached a zipped gdb of the input table for testing.
If these were collected by time, I would expect more while waiting at stop lights/signs and then turning. Less points mid-block when the vehicle was going faster.
Edit: If you label by ID or Sample ID, are the points progressing towards a corner, then turning?