Issue link: https://read.dmtmag.com/i/59336
Infrastructure Data a customized loader was developed. The customized loader populates in/out feature counts and provides logging to ensure that the staging geodatabase fea- tures successfully load into the seamless, provincial- wide Cadastral Fabric. The process workflow design and development is based on repeatability to enable quick and effortless update cycles. Data Integration: Fitting the Puzzle Pieces In total, 850-plus datasets from the four source pro- viders were ultimately integrated into the Cadastral Fabric. In some cases, the data providers supplied known spatial-accuracy statements, datums and projections. In other situations, the spatial accuracy and georeferencing details became another puzzle to solve. MNC's team of highly trained geomatics technicians, specializing in surface land mapping, integrated more than 400,000 plans of survey for the province of Alberta during the last 13 years. This expertise was particularly valuable in creating adjustment and trans- formation vectors required to conflate and edge-match disparate-source datasets. As an example, the spatial alignment of a particular site in northeast Manitoba conflicted with the sur- rounding parcel data; 1:60,000-scale orthoimagery was used to validate that this parcel dataset required a shift and rotation. To capture the required movement, a feature class called TransformV was designed and populated with shift vectors. The custom Transformer FME workspace uses this feature class to move and rotate the source data in an automated and repeatable transformation process. lFigure 2. A staging area was created for unique parcel-puzzle pieces. A custom Adjustor FME workspace was built to address situations where adjustment algorithms are used to spatially conflate data and edge-match with surrounding datasets. The bottom of Figure 4 illus- trates the adjustment vectors stored as a simple feature class, identifying the "from" and "to" nodes (adjustment coefficients). The source data required dramatic adjustment (more than 800 meters) to better fit surrounding, spatially accurate data. The difference between the Transform and Adjustor workspaces is that the Transform work- space provides a solution for a uniform data shift, and the Adjustor provides a solution for a non-uniform adjustment, whereby each adjustment vector defines a unique displacement and rotation. After the data are conflated, subsequent Snapping lFigure 3. A process was created to efficiently repeat parcel-puzzle assembly. 24 GEO W ORLD / MARCH 2O12 FME workspaces are invoked to ensure that the vertices are coincident among adjacent datasets to satisfy topological requirements. CAD data from Manitoba Hydro's internal archives presented a unique challenge. Through the course of many years, these site-specific survey drawings had been drafted using custom AutoCAD software, and it was presumed that the content structure was uniform. However, a comprehensive data review revealed that various layer structures and standards were used that would require extensive effort to normalize. The extent of coverage also required validation, because a number of the AutoCAD files covered similar or partially similar areas. In some cases, better alternate-source data superseded the available CAD data. Initially, more than 500 AutoCAD drawings were reviewed, and, after correlating the coverage to other source datasets, only 310 files were deemed relevant.