U.S. Department of the Interior U.S. Geological Survey Data Integration of Layers and Features for The National Map March 31, 2003 E. Lynn Usery Michael P. Finn Michael Starbuck

Outline n Motivation, Goals, and Objectives n Approach n Data n Test Sites n Methods n Products n Conclusions

Motivation and Goals n The National Map will consist of integrated datasets, a digital product similar to the comprehensive, integrated lithographic printed map n Current USGS digital products (DLG, DOQ, NED, NHD, NLCD) are single layer and not vertically-integrated n The goal is to develop procedures for automated integration based on metadata

Objectives n Framework for layer integration based on metadata n Framework for feature integration n Example results for Atlanta and St. Louis

Approach n Layer-based Use existing seamless datasets Determine integration feasibility based on resolution and accuracy n Feature-based Implement integration on feature by feature basis Use developed feature library

Data n Orthoimages from 133 Urban Areas n National Hydrography Dataset (NHD) n National Elevation Dataset (NED) n Transportation (DLG) n National Land Cover Dataset (NLCD)

Data Integration Layer Sources

Test Sites n St. Louis, Missouri Initially the Manchester and Kirkwood quadrangles n Atlanta Initial area in Northeast in Gwinnett County

Methods n Layer integration Determine compatible resolutions and accuracies and use metadata to automatically combine appropriate datasets Determine transformations possible that integrate datasets of incompatible resolutions and accuracies Determine limits of integration based on resolution and accuracy

Integration Possibilities

Cartographic Transformations from Keates n Sphere to plane – projection Mathematical, deterministic, correctable n Three-dimensional to two-dimensional Mathematical, deterministic, correctable n Generalization Non-mathematical, scale dependent, humanistic, not correctable

Mathematical Transformations -- Scale and Resolution Matching n If data meet NMAS, then integration can be automated based on the scale ratios If linear ratios of scale denominators are ½, then integration is possible through mathematical transformations For ratios smaller than ½, generalization results in incompatible differences

Generalization Issues n Selection – common features may not appear on data layers to be integrated (Topfer’s Radical Law) n Simplification – lines may contain reduced numbers of points and have different shapes n Symbolization – for map sources, symbolization may result in areas shown as lines or points n Induction – features may have been interpolated and appear differently on different sources

Feature Integration n Metadata exists on a feature basis Accuracy, resolution, source are documented by feature Use Feature Library with an integration application

Products n Integration methodology for layers and features n Test implementations for St. Louis and Atlanta

Conclusions n Data integration of layers for The National Map can only be accomplished with datasets that are compatible in resolution and accuracy n Mathematical transformation can automate integration with limited ranges of scales, but cannot correct generalization differences between datasets

U.S. Department of the Interior U.S. Geological Survey Data Integration of Layers and Features for The National Map March 31, 2003 E. Lynn Usery Michael P. Finn Michael Starbuck