Edge matching is simply the procedure to adjust the position of features that extend across typical map sheet boundaries. Theoretically data from adjacent map sheets should meet precisely at map edges. However, in practice this rarely occurs.
Edge Matching is an important part of the creation of a digital map or GIS database. One digital map may encompass many paper maps. But when the paper maps are laid edge-to-edge, features running across the boundaries of the map sheets are not always properly aligned.
When side-by-side map layers are retrieved and displayed, they might not line up well with each other (see Figure 3.11 below). Edge matching adjusts the location of features that extend across one map's boundaries into another.
Edge matching is a procedure to adjust the position of features extending across map sheet boundaries. This function ensures that all features that cross adjacent map sheets have the same edge locations. Links are used when matching features in adjacent coverages.
Editing Functions ...
Edge matching: DEM datasets within a project area (consisting of a number of adjacent files) are edge matched to assure terrain surface continuity between files. Edge matching is the process of correcting adjacent elevation values along common edges.
Map cleanup function that allows for distortion between adjacent maps to produce a true match of features at the edges of maps. The result is a continuous map by ensuring that all features that cross theboundary between two adjacent maps appear to be or are a single feature.
Edge matching - The process of matching corresponding features across map boundaries. This is a prerequisite for using multiple digital maps in geographic data processing and analysis.
Editing - The process of modifying and updating graphics and attribute data ...
Route-system features and event-handling commands provide the dynamic segmentation capability within ARC/INFO.
edge matchingAn editing procedure to ensure that all features that cross adjacent map sheets have the same edge locations.
[LINK] Each scale reduction required edge matching, or paneling, of the larger scale maps to produce the next small scale map. In addition, through the process known as generalization, the amount of information was reduced to make the smaller scale map readable.
Transformation of projections and coordinate systems, edge matching
Spatial retrieval, windowing, selection
Distance, proximity, networking, buffering
Overlays and merging
Modeling, scenario building
Generating maps and reports ...
Aronoff (1989) described seven maintenance and analysis functions for spatial data: format transformation, geometric transformation, transformation between map projections, conflation, edge matching, editing of graphic elements, and line coordinate thinning.
More LSQR interpolations would probably have helped in this case. However, the edge matching problem highlights a key weakness of the interpolative approach taken up until now, which prompted me to add a different patching strategy to BLACKART.