Automated Centerline Delineation to Enrich the National Hydrography Dataset

  • Chris Anderson-Tarver
  • Mike Gleason
  • Barbara Buttenfield
  • Larry Stanislawski
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7478)


A common problem in the automated generalization of basemaps is extraction of important features for cartographic visualization purposes. The delineation of a stream network centerline poses unique challenges especially when variables such as stream order, channel depth, or flow rate are not available. This paper presents an algorithm for automated delineation of a continuous cartographic centerline through a flowline network encompassing a single subbasin. Six datasets testing the algorithm are drawn from the U.S. National Hydrography Dataset (NHD) to compare among delineations in landscapes with varying terrain and precipitation regimes. Centerline delineation provides a database enrichment, which adds functionality and enables cartographic generalization. A user-defined cutoff value permits progressively inclusive centerline delineations which may be targeted to multiple map scales and purposes.


Stream centerline cartographic generalization database enrichment 


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  1. 1.
    Anderson-Tarver, C., Buttenfield, B.P., Stanislawski, L.V., Koontz, J.M.: Automated Delineation of Stream Centerlines for the USGS National Hydrography Dataset. In: Ruas, A. (ed.) Advances in Cartography and GIScience, Paris. Lecture Notes in Geoinformation and Cartography, vol. 1, pp. 409–423. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  2. 2.
    Balboa, J.L.G., López, F.J.A.: Generalization-Oriented Road Line Classification by Means of an Artificial Neural Network. Geoinformatica 12, 289–312 (2008)CrossRefGoogle Scholar
  3. 3.
    Benke, A.C., Cushing, C.E. (eds.): Rivers of North America. Elsevier Academic Press, Burlington (2005)Google Scholar
  4. 4.
    Bobzien, M., Burghardt, D., Neun, M., Weibel, R.: Multi-Representation Databases With Explicitly Modeled Horizontal,Vertical and Update Relations. In: Proceedings AutoCarto, Vancouver (2006)Google Scholar
  5. 5.
    Brassel, K.E., Weibel, R.: A Review and Conceptual Framework of Automated Map Generalization. Int’l Journal of Geographical Information Systems 2(3), 229–244 (1988)CrossRefGoogle Scholar
  6. 6.
    Buttenfield, B.P., Mark, D.: Expert Systems in Cartographic Design. In: Geographic Information Systems: the Microcomputer and Modern Cartography, pp. 129–150. Pergamon Press, Oxford (1991)Google Scholar
  7. 7.
    Buttenfield, B.P., Stanislawski, L.V., Brewer, C.A.: Multiscale Representations of Water: Tailoring Generalization Sequences to Specific Physiographic Regimes. GIScience Short Paper Proceedings (2010)Google Scholar
  8. 8.
    Buttenfield, B.P., Stanislawski, L.V., Brewer, C.A.: Adapting Generalization Tools to Physiographic Diversity for the United States National Hydrography Dataset. Cartography and Geographic Information Science 38(3), 289–301 (2011)CrossRefGoogle Scholar
  9. 9.
    Chaudhry, O.Z., Mackaness, W.A.: Automatic Identification of Urban Settlement Boundaries for Multiple Representation Databases. Computers Environment and Urban Systems 32(2), 95–109 (2008)CrossRefGoogle Scholar
  10. 10.
    Crowder, D.W., Diplas, P.: Using Two-Dimensional Hydrodynamic Models at the Scales of Ecological Importance. Journal of Hydrology 230(3-4), 172–191 (2000)CrossRefGoogle Scholar
  11. 11.
    Horton, R.E.: Erosional Development of Streams and Their Drainage Basins: Hydrophysical Approach to Quantitative Morphology. Geological Society of America Bulletin 56(3), 275–370 (1945)CrossRefGoogle Scholar
  12. 12.
    Merwade, V.M., Maidment, D.R., Hodges, B.R.: Geospatial Representation of River Channels. Journal of Hydrologic Engineering 10(3), 243–251 (2005)CrossRefGoogle Scholar
  13. 13.
    Neun, M., Burghardt, D., Weibel, R.: Web Service Approaches for Providing Enriched Data Structures to Generalisation Operators. International Journal of Geographical Information Science 22(2), 133–165 (2008)CrossRefGoogle Scholar
  14. 14.
    Neun, M., Weibel, R., Burghardt, D.: Data Enrichment for Adaptive Generalisation. In: Proceedings of the ICA Workshop on Generalization and Multiple Representations, Leicester, U.K., 6 p. (2004),
  15. 15.
    Pierson, S.M., Rosenbaum, B.J., McKay, L.D., Dewald, T.G.: Strahler Stream Order and Strahler Calculator Values in NHDPlus. Unites States Geological Survey (2008),
  16. 16.
    Stanislawski, L.V., Buttenfield, B.P., Finn, M.: Integrating Hydrographic Generalization over Multiple Physiographic Regimes. In: Proceedings of the Symposium on Generalization and Data Integration (GDI 2010) Boulder (forthcoming, 2010)Google Scholar
  17. 17.
    Stanislawski, L.V., Buttenfield, B.P., Samaranayake, V.A.: Automated Metric Assessment of Hydrographic Feature Generalization Through Bootstrapping. In: Proceedings of the 13th Workshop of ICA Commission on Generalisation and Multiple Representations (2010),
  18. 18.
    Stanislawski, L.V., Finn, M., Starbuck, M., Usery, E.L., Turley, P.: Estimation of Accumulated Upstream Drainage Values in Braided Streams Using Augmented Directed Graphs. In: Proceedings AutoCarto, Vancouver (2006)Google Scholar
  19. 19.
    Stanislawski, L.V., Finn, M., Usery, E.L., Barnes, M.: Assessment of a Rapid Approach for Estimating Catchment Areas for Surface Drainage Lines. In: Proceedings ACSM-IPLSA-MSPS, St. Louis (2007)Google Scholar
  20. 20.
    Steiniger, S., Weibel, R.: Relations Among Map Objects in Cartographic Generalization. Cartography and Geographic Information Science 34(3), 175–197 (2007)CrossRefGoogle Scholar
  21. 21.
    Strahler, A.N.: Quantitative Analysis of Watershed Geomorphology. Transactions of the American Geophysical Union 8(6), 913–920 (1957)Google Scholar
  22. 22.
    Touya, G.: First Thoughts for the Orchestration of Generalisation Methods on Heterogeneous Landscapes. In: Proceedings of the ICA Workshop on Generalizations, Montpellier (2008)Google Scholar
  23. 23.
    USGS: The National Hydrography Dataset: Concepts and Contents, United States Geological Survey (2000),
  24. 24.
    USGS: The National Flood Frequency Program, version 3: A Computer Program for Estimating Magnitude of Flood for Ungaged Sites, Unites States Geological Survey (2002),
  25. 25.
    Zhang, X., Stoter, J., Ai, T., Kraak, M.J.: Formalization and Data Enrichment for Automated Evaluation of Building Pattern Preservation. In: Proceedings of the Spatial Data Handling 2010, vol. 38(2), pp. 267–273 (2010)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Chris Anderson-Tarver
    • 1
  • Mike Gleason
    • 1
  • Barbara Buttenfield
    • 1
  • Larry Stanislawski
    • 2
  1. 1.Dept. of GeographyUniversity of Colorado-BoulderColoradoUSA
  2. 2.Center of Excellence for Geospatial Information Science (CEGIS)United States Geological Survey (USGS)RollaUSA

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