I work for a company that has a list of 35,000+ jobs over 30+ years that they would like to reference easily in a GIS database. They are sorted by the New York State SWIS Codes that can be found here: http://gis.ny.gov/coordinationprogram/workgroups/wg_1/related/spcodes/swis.htm
So for example, I would have: Job A, SWIS Index #, XXXXXX, XXXXXX in an excel file, import to ArcGIS, (IE: Job A, 3720, XXXXXX, XXXXXX = Job A is located in Putnam County, in the town of Carmel, with XXXXXX, XXXXXX GPS coordinates), and have all the jobs plotted on a map by SWIS code using the GPS coordinate assigned to it.
That part is easy. The issue I'm having though, is that I would say between 15-20% of our jobs are referenced wrong. So for instance, Job A might have the Carmel/Putnam County SWIS code (3720) but the GPS coordinates might put it somewhere in New York City (easy to locate, since I would have only Putnam County/Carmel viewable and the dot is way off the map) or vice versa, where a job has a New York City SWIS code but plotting in Carmel (very difficult to locate, since it would be a essentially a needle in a hay-stack with thousands of other jobs in Carmel).
Finding the ones that are outside of my selected city/town/village are easy. Finding the harder ones is tough. I can go through manually and do jobs by town/city using the SWIS index but considering I have a dozen+ counties to go through and well over 100+ cities/towns/villages, my boss doesn't find that very economical and doesn't want me to do that, and I agree. I'm not that expierenced enough yet with ArcGIS where I can import the coodinates and be able to search "3720" and have all the "error jobs" pop up, which is why I'm asking for help.
To sum up, I need to find these two errors:
1) Right SWIS code, wrong GPS coordinate
2) Wrong SWIS code, right GPS cooridinate
Easily, but just searching the SWIS code. However if that's not possible I am open to all other suggestions. My end solution is to find the two errors listed about easily
I am also using ArcGIS 9.2 Build 1234, with not many licenses/features to play with. So any help would be much appreciated.
Thank you
Do you have a polygon layer with your SWIS boundaries? If so you can Spatial Join the points to the SWIS boundaries. Make sure the option to keep all target features is checked. The output would have the original point SWIS code and the actual SWIS code location the point fell within. You can then easily select where the two SWIS code fields do not match. Determining whether the SWIS code is wrong or the coordinate is wrong would have to be determined by some other field data, but assuming there is another field that could indicate whether a given SWIS code was correct or not, you could check the two SWIS codes against that field.
If I'm reading you/doing it right, this only gives me the jobs outside the SWIS code. I still need the jobs that fall within a SWIS code that shouldn't be there
I still must be doing it wrong, because all I'm getting are the points within the SWIS code boundary and not the points outside the SWIS code area with the SWIS code (wrong GPS coordinates). I get what you're saying now, but I'm sure there's a attribute error with my shapefiles that's messing it up. Regardless, this way is still time consuming because I would have to go through each city/town/village to get it completed. My boss really just wants it simple: Plug in a code, and it spits out all the errors. Only way I could do that is if I had GIS programming knowledge which I don't...
Another issue I'm having is that my points are NAD27 and the shapefiles are NAD83 but yet they're projecting together which makes no sense, but that's for another time haha
Actually, thinking about your problem I wonder whether the SWIS boundaries changed during that 30+ years. If they did that could account for the errors. Are you observing errors only on older job data? If so, then perhaps researching the previous boundaries might make it clear that the points are correctly located and just need to be updated to the current SWIS codes.
If the errors are spread out over all years, then the problem is likely to be either data entry input errors (transposing digits or misreading hand written numbers that can appear similar like 5/6 or 8/9 or 2/7 for example), or perhaps some other pattern. Discovering the patterns to the errors is key to selecting and fixing them quickly, and probably does not require examining each individual subarea to sort them out.