Presentation on theme: "Graphic Data Clean-Up Issues. Graphic Data Clean-up Very Important if you plan to use existing CAD or GIS data from another agency, department, or private."— Presentation transcript:
Graphic Data Clean-Up Issues
Graphic Data Clean-up Very Important if you plan to use existing CAD or GIS data from another agency, department, or private vendor as a base map. Error Correction before you begin is key. –Spatial errors (ie projection/coordinate systems) –Topological (duplicate lines, gaps, dangles, etc.)
Graphic Data Clean-up (cont.) Existing Attribute linkages on the graphics can also cause “headaches”. Particularly if you plan to use graphics that were attached to databases. Those “old” linkages can cling to the graphic elements and cause troubles later. Potential errors are dependent upon which GIS or 911 software is being implemented.
Line Weeding Line Weeding reduces the size and complexity of linear data based on a user defined tolerance Line Weeding performs distance checks on linear data Benefits of weeding linework: –Significant improvement in screen update times, plot-stroking performance, and spatial analysis processing time –Reduced disk space requirements
Cleaning CAD Linework The line cleaning tools correct errors in 2-D and 3- D linework. The line cleaning tools can: –correct undershoots or overshoots –break intersections –remove short segments –merge duplicate line segments The line cleaning tools can process: –lines, line strings, arcs, curves, shapes, ellipses, complex strings, and complex shapes
Common Line work checks Intersection Processing -- either break or flag intersections. Duplicate Line Processing -- merges duplicate line work in 2-D and 3-D design files. Short Segment Processing -- removes zero- length lines and short segments that have at least one free endpoint in 2-D and 3-D line work. Endpoint Processing -- corrects or flags free endpoints, the free endpoints can be either overshoots or undershoots.
Graphic Attributes also need to be checked TIGER Address Ranges, for example, are often incorrect (or blank) in Rural areas. Can be corrected and updated, but its tedious work! Allow me to demonstrate, using a very simple set of data and GIS software package.
Attribute Edits Selected a street segment with a “NULL” value for the address column.
Attribute Edits Edit the Attribute Table to reflect the address ranges on the left and right side of the street. Geocode a sample address.
Attribute Edits Confirm that the street segment is properly oriented for placing the “odd” address on the correct side of the street. 105 Gadberry Dr.
Attribute Edits Re-edit the Attribute table. Reverse the increase in value in the left and right address columns.
Attribute Edits Geocode the same address as before. Resulting geocode location will be the opposite end of street segment.
Attribute Edits This is overly simplified for the purpose of this demonstration, but this is basically how you could go about updating the TIGER data for a county.