The Planning Data Services Bureau of the Georgia Department of Transportation has a twofold GIS mission. They need to maintain and update their road characteristics database (RCFILE) and produce publication quality maps for each county in the state. Using the basemap's route features, which have been calibrated to the intersection level, a number of cartographic products can be produced in a semiautomated fashion. The RCFILE uses a linear referencing system; therefore, dynamic segmentation can be used to map the road surface types and bridge locations. Annotation subclasses for route numbers and road names are generated from the route feature attributes rather than individual arc attributes, thereby reducing the amount of editing. A unique set of problems arise, however, from the integration of dynamic segmentation into the cartographic production process. In addition to an overview of the cartographic production techniques used in ArcInfo, the solutions and work-arounds necessary to mitigate these problems are discussed.
Originally, RF3 and DLG-E were based on a common set of linework. However, due to modifications to RF3 linework and to changes in rules defining how hydrologic features are delineated, the two no longer share identical coordinates. As part of EPA's project to enhance and update RF3, the entire RF3 dataset will be conflated to DLG-E linework. To maximize the automated portion of the conflation process, AML macros have been developed to successfully conflate over 90% of the 3.2 million RF3 reaches to DLG-E. This paper presents some innovative techniques that will be used to automate the successful conflation of two very large databases.
The Bureau of the Census (BOC) is building a Master Address File for the 2000 census. When the Master Address File is complete, it will contain an address for every household in the United States for which an address exists. To add the millions of addresses that are currently missing and link them to the BOC's internal TIGER data base for collection and tabulation purposes, the BOC is automating the incorporation of non-census agency information to the extent possible. The BOC is accepting digital information (geographic or tabular) to accomplish it mission. This paper will discuss specific programs for which digital information is being sought, the information being requested, data format requirements, and how the information is utilized by the BOC when it is received.
The Roads Centreline coverage of the State of Qatar was created a few years ago in response to the needs of the growing GIS user community. Over the years with the absence of formal maintenance procedures, it had become increasingly difficult to maintain this dataset using traditional methods which were resource intensive, time consuming and expensive. Last year this problem was thoroughly investigated by CED Roads Division, GIS Unit as the availability of a highly accurate, updated roads centreline coverage was becoming imperative. As resource restrictions did not allow a complete site survey of the extensive road network, an economical yet effective solution was required. The availability of a high quality urban dataset from The Centre for GIS representing man-made structures formed the basis of the project. The challenge was to be able to identify polygons representing roads and then derive road centrelines from these polygons that precisely traversed the centre of the road throughout the network. This paper talks about the outcome of this project, namely: