Scale Representation using the VisibilityFilter Attribute
Please note: The VisibilityFeature attribute currently is only available for NHDPlus HR Regions 1 and 6. After a period of testing, it will be included in all NHD and NHDPlus HR data as datasets are produced.
The VisibilityFilter attribute allows for filtering of vector data features at eight approximate scales. A given VisibilityFilter coded-value indicates that the feature is appropriate for use at approximately the defined scale and all larger scales. Two separate methods to display NHD features with the VisbilityFilter attribute for NHDFlowline, NHDWaterbody, NHDArea, and NHDLine feature classes are described below.
Methods for Using the VisibilityFilter Attribute
These instructions are specific to Esri ArcMap as general examples, but can be adapted to perform in other GIS software.
Method 1: Definition Query
To view features at a desired scale in Esri ArcMap:
Alternatively, copy and paste, or type definition queries from the “VisibilityFilter Domains, Codes and Queries” table below directly into the Definition Query field.
Method 2: New Data Layer
To create a data layer with a desired scale in Esri ArcMap:
For example, to create a 1:250,000-scale map, enter “VisibilityFilter >= 250000” to select all features appropriate for use at scales smaller than approximately 1:250,000 and export this data to a new layer.
VisibilityFilter Domains, Codes and Queries
Below is a list of Visibility Filter domains, codes, and queries for reference
The VisibilityFilter attribute currently is in a testing phase. Issues will be listed here as they are discovered. Known issues will be resolved as VisibilityFilter attribute population is updated to an automated process prior to NHDPlus HR creation. The new process will allow the VisibilityFilter attribute to be populated when a geometry change to any of the NHD feature classes with the VisibilityFilter attribute is detected, ensuring NHD and NHDPlus HR data VisibilityFilter attributes are maintained and current.
The methods to determine the VisibilityFilter attribute for NHDFlowline, NHDLine, NHDWaterbody, and NHDFlowline features are detailed in the papers listed below.
Buttenfield, B. P., Stanislawski, L. V., and Brewer, C. A., 2011, Adapting generalization tools to physiographic diversity for the United States National Hydrography Dataset: Cartography and Geographic Information Science, v. 38, no. 3, p. 289-301, http://www.tandfonline.com/doi/abs/10.1559/15230406382289, last accessed 05/09/2017.
Stanislawski, L. V., 2009, Feature pruning by upstream drainage area to support automated generalization of the United States National Hydrography Dataset: Computers, Environment and Urban Systems, v. 33, p. 325-333, http://www.sciencedirect.com/science/article/pii/S0198971509000520, last accessed 05/09/2017.
Stanislawski, L. V. and Buttenfield, B. P., 2011, A raster alternative for partitioning line densities to support automated cartographic generalization: Proceedings of the 25th International Cartographic Conference, Paris, France, http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.468.8004&rep=rep1&type=pdf, last accessed 05/09/2017.
Stanislawski, L.V., Doumbouya, A.T., Miller-Corbett, C.D., Buttenfield, B.P. and Arundel, S.T., 2012, Scaling stream densities for hydrologic generalization: Proceedings, 7th International Conference on Geographic Information Science, September 18-21, 2012, Columbus, Ohio, 6 p.
Stanislawski, L.V., Buttenfield, B.P., and Doumbouya, A., 2015, A rapid approach for automated comparison of independently derived stream networks: Cartography and Geographic Information Science, 42(5): 435-448, DOI: 10.1080/15230406.2015.1060869
Stanislawski, L.V., Falgout, J., Buttenfield, B.P., 2015, Automated extraction of natural drainage density patterns for the conterminous United States through high performance computing: The Cartography Journal 52(2):185-192
Stanislawski, L.V., Survila, K., Wendel, J., Liu, Y., and Buttenfield, B.P., 2017, An open source high-performance solution to extract surface water drainage networks from diverse terrain conditions: Cartography and Geographic Information Science, DOI: 10.1080/15230406.2017.1337524
Stauffer, A.J., Finelli, E., and Stanislawski, L.V., 2016, Moving from generalization to the 'Visibility Filter Attribute': Leveraging database attribution to support efficient generalization decisions: American Water Resources Association 2016 Summer Specialty Conference, GIS & Water Resources IX, July 11-13, 2016, Sacramento, California.
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