Achieving Location Accuracy in GIS. John Adams, GISP Orleans Parish Communication District 2015 Louisiana Remote Sensing & GIS Workshop

Transcription

1 Achieving Location Accuracy in GIS John Adams, GISP Orleans Parish Communication District 2015 Louisiana Remote Sensing & GIS Workshop

2 given any reasonable input into the Computer Aided Dispatch (CAD) system.

3 How does geographic information get processed in the center? Chronology of events: 1. The call comes in with Automatic Location Information (ALI), which makes the map move. Landline: generally accurate Phase I wireless: wildly inaccurate Phase II wireless: accurate to inaccurate 2. The citizen describes their location to the call-taker Under duress Unfamiliar with the area they re in (esp. tourists) Limited visibility (night, etc)

4 Chronology of events continued: 3. Call taker interprets and makes entry into the CAD system. Accuracy of what they are hearing Their level of training and geographic knowledge Typos are not unheard of 4. The CAD system tries to work out the location based on the quality of the inputs and the limits of the GIS. 5. Dispatchers assist 1 st responders in getting to location as they don t yet have maps in vehicles. So, many inputs, and links in the chain, each with a significant possibility of error

5 Wide variety of inputs continued: The role of alias tables We have to be able to account for whatever the citizen sees and says 1. The street centerline file has to have an extensive set of aliases due in part to inconsistent or incorrect street naming as present on street signs and also to street names being spelled ambiguously relative to their pronunciation. Is it John Lee, Jon Lee or Jonlee Drive? 1. Common Places can be known by more than one name at once or through time (what I call institutional knowledge, which applies to street name changes as well) Exit 231A West is also Metairie Rd Exit and City Park Ave Exit

6 Multiple models to import GIS into CAD

7 In the past, our CAD system only used street centerlines Now, address points and building footprints are also in the mix.

8 We use every available source of information to achieve location accuracy, including but not limited to: City IT Department Assessor s Office City Planning Commission Regional Planning Commission/LADOTD Google Maps & Street View, Bing Maps, MapQuest, etc. Internet research Telephone interviews Field checks

9 To make our data sufficiently accurate, we use a wide variety of means, but often an ArcGIS address management tool commonly known as the fishbones.the fishbone analysis tool is used in several ways

10 Here we see at least three types of pattern, each of which provides a different piece of information.

11 One way is to compare our centerlines to our address points: 1. Out of numerical order 2. On the wrong side of the street 3. On the wrong block 4. With incorrect attributes such as street name/spelling, suffix type, prefix/suffix directional etc. This can be accomplished by visual inspection or. Out of numerical order

12 by querying the data in certain ways, for example show me every fishbone that intersects a street centerline Wrong side of the street

13 On the wrong block. Significant because CAD generates high/low cross streets and this could affect the routing of first responders.

14 The fishbones also allow us to catch other errors such as a one-digit typo in a segment s range

15 or a centerline that needs to be flipped odd/even.

16 The other primary use is point-to-point analysis to compare our addresses to the city s, which have a different schema, numerous undocumented changes and CAD-critical errors. With this analysis we can find, city points that: 1. Have different\incorrect attributes (will not connect to our points) 2. Are new to us (same as above) 3. Are at a different location than ours ( Give me every fishbone that crosses a parcel boundary ) BTW, you can also use this tool to compare parcels that have address attributes to both centerlines and points

17 Errors in the city file. Each red line is a possible problem, the longer the line the more serious: i.e. valid address points miles from where they should be.

18 Typically refer to six sets of imagery in a given edit session, including the most recent: Two years of oblique Three years of ortho Street level

19 I look at every visual clue as to how many addresses might be at a given location and where to place the points: Visible house number(s), sometimes on the curb or garbage can What appears to be a front door Electric/gas meters Hot water closets Maiboxes Driveways, etc. Sometimes looking at older imagery, especially in StreetView, gives us a way around foliage or other visual obstructions as well as to track changes over time.

20 Sometimes ya gotta go with the flow (chart)