The traditional method of address matching requires that the roads have full address attributes. Even then, the "best match" would be an interpolated point somewhere along the road. This paper discusses my algorithm for "Parcel Matching". This technique uses the annotation attribute (street number) form the parcels coverage and annotation attribute (street name) from the roads coverage to match an address event to its correct parcel. This method is particularly useful for utility companies or appraisal districts that have a GIS system with coverages that originated from CAD systems. These coverages have annotations with no real attributes other then text and coordinates. With "Parcel Matching", we can methodologically attach a foreign key to the parcel annotation. This foreign key then can be used to relate other attributes to the parcel annotation. My algorithm for "Parcel Matching" adds address intelligence to nearly 95% (1.4 million) of all parcel in the Houston Light and Power base map.
A unique approach which combines raster and vector spatial processing techniques was developed for generating vector road center-lines utilizing vector road rights-of-way. This process also explores the ability to automatically build address topology into the street centerline vectors utilizing parcel centroid topology. This data model has been researched and tested using a local government land records database provided by the Dane County, Wisconsin, Land Information Office. This data model uses the Euclidean Distance functions of Grid to produce an integrated vector parcel/street centerline database.
For many years now one of the more beneficial tools in planning applications has been the intelligent street name file. Whether in the form of a GBF DIME file, TIGER file or a proprietary database the street centerline file with street names and address ranges have assisted cities and counties in address matching, census aggregation and pavement management. However, in many cases, agencies are caught with graphics centerline files that have little or no intelligence and are looking tools to improve the quality of their centerline file. In order to accomplish this task Black and Veatch instituted a series of applications that: 1) set the direction of street segments based upon a theoretical address range guide quad, 2) evaluates street segment "chains" on a coordinate basis rather than an address range basis, 3) performs "intelligent pseudo node elimination" that eliminates pseudo nodes while retaining valid street segment name and address data and 4) However, in many cases, agencies are caught with graphics centerline files that have little or no intelligence and are looking tools to improve the quality of their centerline file. In order to accomplish this task Black and Veatch instituted a series of applications that: 1) set the direction of street segments based upon a theoretical address range guide quad, 2) evaluates street segment "chains" on a coordinate basis rather than an address range basis, 3) performs "intelligent pseudo node elimination" that eliminates pseudo nodes while retaining valid street segment name and address data and 4) propagates address ranges from address point data file. This suite of tools allows users to audit and edit their centerline file by taking full advantage of GIS automation capabilities by exploiting graphic and database manipulation procedures.