SEARCH

SEARCH BY CITATION

Literature Cited

  • Arrigoni, A.S., M.C. Greenwood, and J.N. Moore, 2010. Relative Impact of Anthropogenic Modifications Versus Climate Change on the Natural Flow Regimes of Rivers in the Northern Rocky Mountains, United States. Water Resources Research46:W12542, doi: 10.1029/2010WR009162.
  • Band, L.E., 1993. Extraction of Channel Networks and Topographic Parameters from Digital Elevation Data. In : Channel Network Hydrology, K. Beven and M.J. Kirkby (Editors). Wiley, New York, pp. 13-42.
  • Barari, A., D.L. Iles, and T.C. Cowman, 1989. Assessment of Water Resources and Conceptual Evaluation of a Regional Water Supply for Southeastern South Dakota. State of South Dakota Department of Water and Natural Resources, Division of Geological Survey, Open File Report 60-UR, 18 pp.
  • Brown, L.R. and M.L. Bauer, 2009. Effects of Hydrologic Infrastructure on Flow Regimes of California’s Central Valley Rivers: Implications for Fish Populations. River Research and Applications26(6):751-765, doi: 10.1002/rra.1293.
  • Brügelmann, R. and A. Bollweg, 2004. Laser Altimetry for River Management. In : International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences. 20th ISPRS Congress. Proceedings and Results, Volume XXXV, Part A, M.O. Altan (Editor). International Congress for Photogrammetry and Remote Sensing, Lemmer, The Netherlands, pp. 234-239, http://www.isprs.org/proceedings/XXXV/congress/comm2/papers/129.pdf .
  • Carlisle, D.M., J. Falcone, D.M. Wolock, M.R. Meador, and R.H. Norris, 2010. Predicting the Natural Flow Regime: Models for Assessing Hydrological Alteration in Streams. River Research and Applications26(2):118-136, doi: 10.1002/rra.1247.
  • Carlisle, D.M., D.M. Wolock, and M.R. Meador, 2011. Alteration of Stream Flow Magnitudes and Potential Ecological Consequences: A Multiregional Assessment. Frontiers in Ecology and the Environment9(5):264-270, doi: 10.1890/100053.
  • Carrivick, J.L., V. Manville, A. Graettinger, and S.J. Cronin, 2010. Coupled Fluid Dynamics-Sediment Transport Modelling of a Crater Lake Break-Out Lahar: Mt. Ruapehu, New Zealand. Journal of Hydrology388(3-4):399-413, doi: 10.1016/j.jhydrol.2010.05.023.
  • Casas, A., G. Benito, V.R. Thorndycraft, and M. Rico, 2006. The Topographic Data Source of Digital Terrain Models as a Key Element in the Accuracy of Hydraulic Flood Modeling. Earth Surface Processes and Landforms31(4):444-456, doi: 10.1002/esp.1278.
  • Colson, T.P., J.D. Gregory, H. Mitasova, and S.A.C. Nelson, 2006. Comparison of Stream Extraction Models Using LIDAR DEMs, In : Geographic Information Systems and Water Resources IV. AWRA’s 2006 Spring Specialty Conference, Sandra Fox (Editor). American Water Resources Association, Middleburg, Virginia, 7 pp.
  • Ducey, C., D. Wickwire, and J. Stevens, 2012. A Proposed Workflow for Delineating Stream Networks From Lidar-Derived Digital Elevation Models to Update the National Hydrography Dataset (NHD) in the Pacific Northwest. In : Geographic Information Systems (GIS) and Water Resources VII. AWRA’s 2012 Spring Specialty Conference, S. Fox (Editor). American Water Resources Association, Middleburg, Virginia, 7 pp.
  • Farr, T.G., P.A. Rosen, E. Caro, R. Crippen, R. Duren, S. Hensley, M. Kobrick, M. Paller, E. Rodriguez, L. Roth, D. Seal, S. Shaffer, J. Shimada, J. Umland, M. Werner, M. Oskin, D. Burbank, and D. Alsdorf, 2007. The Shuttle Radar Topography Mission. Reviews of Geophysics45:RG2004, doi: 10.1029/2005RG000183.
  • Foster, B.D., 2003. Landslides in the Interstate 5 Corridor Between Valencia and Gorman, Los Angeles County, California. Prepared for California Department of Transportation, New Technology and Research Program, Office of Infrastructure Research. Department of Conservation, California Geological Survey, Special Report 188, 25 pp. http://www.conservation.ca.gov/cgs/rghm/landslides/SR_188/Documents/CT005laREPORT.pdf.
  • Franken, S.K., 2004. USGS EROS Data Center Produces Seamless Hydrologic Derivatives With GIS. ArcNews Online, Fall, pp. 8, 13-14. http://www.esri.com/news/arcnews/fall04articles/usgs-eros.html.
  • French, J.R., 2003. Airborne LiDAR in Support of Geomorphological and Hydraulic Modelling. Earth Surface Processes and Landforms28(3):321-335, doi: 10.1002/esp.484.
  • Garbrecht, J. and L.W. Martz, 1997. An Automated Digital Landscape Analysis Tool for Topographic Evaluation, Drainage Identification, Watershed Segmentation and Subcatchment Parameterization: TOPAZ User Manual. U.S. Department of Agriculture, Agricultural Resource Service, Grazinglands Research Laboratory, El Reno, Oklahoma, ARS Publ. GRL 97-4, 125 pp.
  • Gesch, D.B., 2006. An Inventory and Assessment of Significant Topographic Changes in the United States. Ph.D. Dissertation, South Dakota State University, Brookings, South Dakota.
  • Gesch, D.B., 2007. The National Elevation Dataset. In : Digital Elevation Model Technologies and Applications—The DEM Users Manual (Second Edition), D.F. Maune (Editor). American Society for Photogrammetry and Remote Sensing, Bethesda, Maryland, pp. 99-118.
  • Gesch, D.B., M. Oimoen, S.K. Greenlee, C. Nelson, M. Steuck, and D. Tyler, 2002. The National Elevation Dataset. Photogrammetric Engineering and Remote Sensing68(1):5-11. http://asprs.org/PE-RS-Past-Issues.html .
  • Guptill, S.C., 1979. The Development and Use of Digital Cartographic Data Bases. In : Data Base Techniques for Pictorial Applications, A. Blaser (Editor). Springer-Verlag, Berlin, Germany, pp. 65-77.
  • Guptill, S.C., 1983. The Role of Digital Cartographic Data in the Geosciences. Computers & Geosciences9(1):23-26, doi: 10.1016/0098-3004(83)90032-8.
  • Heine, R.A., C.L. Lant, and R.R. Sengupta, 2004. Development and Comparison of Approaches for Automated Mapping of Stream Channel Networks. Annals of the Association of American Geographers94(3):477-490, doi: 10.1111/j.1467-8306.2004.00409.x.
  • Hjerdt, K.N., J.J. McDonnell, J. Seibert, and A. Rodhe, 2004. A New Topographic Index to Quantify Downslope Controls on Local Drainage. Water Resources Research40:W05602, doi: 10.1029/2004WR003130.
  • Höfle, B., M. Vetter, N. Pfeifer, G. Mandlburger, and J. Stötter, 2009. Water Surface Mapping From Airborne Laser Scanning Using Signal Intensity and Elevation Data. Earth Surface Processes and Landforms34(12):1635-1649, doi: 10.1002/esp.1853.
  • Hollaus, M., W. Wagner, and K. Kraus, 2005. Airborne Laser Scanning and Usefulness for Hydrological Models. Advances in Geosciences5:57-63, doi: 10.5194/adgeo-5-57-2005.
  • Homer, C., C. Huang, L. Yang, B. Wylie, and M. Coan, 2004. Development of a 2001 National Land-Cover Database for the United States. Photogrammetric Engineering and Remote Sensing70(7):829-840. http://asprs.org/PE-RS-Past-Issues.html .
  • Jenkins, R.B. and P.S. Frazier, 2010. High-Resolution Remote Sensing of Upland Swamp Boundaries and Vegetation for Baseline Mapping and Monitoring. Wetlands30(3):531-540, doi: 10.1007/s13157-010-0059-1.
  • Jenson, S.K., 1991. Applications of Hydrologic Information Automatically Extracted From Digital Elevation Models. Hydrological Processes5(1):31-44, doi: 10.1002/hyp.3360050104.
  • Jenson, S.K. and J.O. Domingue, 1988. Extracting Topographic Structure From Digital Elevation Data for Geographic Information System Analysis. Photogrammetric Engineering and Remote Sensing54(11):1593-1600. http://asprs.org/PE-RS-Past-Issues.html .
  • Jones, A.F., P.A. Brewer, E. Johnstone, and M.G. Macklin, 2007. High Resolution Interpretative Geomorphological Mapping of River Valley Environments Using Airborne LiDAR Data. Earth Surface Processes and Landforms32(10):1574-1592, doi: 10.1002/esp.1505.
  • Jones, J.L., 2006. Side Channel Mapping and Fish Habitat Suitability Analysis Using Lidar Topography and Orthophotography. Photogrammetric Engineering and Remote Sensing72(11):1202-1206. http://asprs.org/PE-RS-Past-Issues.html .
  • Jones, K.L., G.C. Poole, S.J. O’Daniel, L.A.K. Mertes, and J.A. Stanford, 2008. Surface Hydrology of Low-Relief Landscapes: Assessing Surface Water Flow Impedance Using LIDAR-Derived Digital Elevation Models. Remote Sensing of Environment112(11):4148-4158, doi: 10.1016/j.rse.2008.01.024.
  • Kaiser, B., C. Ducey, and D. Wickwire, 2010. The Oregon Lidar Hydrography Pilot Project: Evaluation of Existing GIS Hydrological Toolsets for Modeling Stream Networks With LiDAR and Updating the National Hydrography Dataset (NHD). Pacific Northwest Hydrography Framework, 27 pp. http://www.pnwhf.org/docs/LiDAR_Hydrography_PilotPhase_I_Final.pdf.
  • Kelmelis, J.A., 2003. To The National Map and Beyond. Cartography and Geographic Information Science30(2):185-198, doi: 10.1559/152304003100011018.
  • Kelmelis, J.A., M.L. DeMulder, C.E. Ogrosky, N.J. Van Driel, and B.J. Ryan, 2003. The National Map—From Geography to Mapping and Back Again. Photogrammetric Engineering and Remote Sensing69(10):1109-1118. http://asprs.org/PE-RS-Past-Issues.html .
  • King, J.G. and L.C. Tennyson, 1984. Alteration of Streamflow Characteristics Following Road Construction in North Central Idaho. Water Resources Research20(8):1159-1163, doi: 10.1029/WR020i008p01159.
  • Kloiber, S.M. and J. Hinz, 2008. Updating the National Hydrography Data for the Twin Cities Metropolitan Area with Local Subsurface Drainage Information. Metropolitan Council, St. Paul, Minnesota, 24 pp. http://www.metrocouncil.org/environment/ESReports/NHDupdateTCMA.pdf.
  • Kost, J. and G. Kelly, 2001. Watershed Delineation Using the National Elevation Dataset and Semiautomated Techniques. In : Proceedings of the 21st ESRI User’s Conference. Environmental Systems Research Institute, Redlands, California, unpaged CD-ROM.
  • Li, J. and D.W.S. Wong, 2010. Effects of DEM Sources on Hydrologic Applications. Computers, Environment, and Urban Systems34(3):251-261, doi: 10.1016/j.compenvurbsys.2009.11.002.
  • Liu, X., J. Peterson, and Z. Zhang, 2005. High-Resolution DEM Generated From LiDAR Data for Water Resource Management. In : Proceedings of International Congress on Modelling and Simulation ‘MODSIM05’, A. Zerger and R.M. Argent (Editors). Modelling and Simulation Society of Australia and New Zealand, Canberra, Australia, pp. 1402-1408.
  • López-Torrijos, R., C. Rose, and K. Kwasnowski, 2012. Lessons From the Development of New York City’s Water Supply Watershed Hydrography Model. In : Geographic Information Systems (GIS) and Water Resources VII. AWRA’s 2012 Spring Specialty Conference, S. Fox (Editor). American Water Resources Association, Middleburg, Virginia, 6 pp.
  • Maidment, D., 1996. GIS and Hydrological Modelling: An Assessment of Progress. In : Third International Conference/Workshop on Integrating GIS and Environmental Modeling, K. Preas (Editor). National Center for Geographic Information and Analysis, Santa Barbara, California, unpaged CD-ROM. http://www.ncgia.ucsb.edu/conf/SANTA_FE_CD-ROM/program.html.
  • Maidment, D. (Editor), 2002. Arc Hydro: GIS for Water Resources. ESRI, Redlands, California, ISBN-13: 9781589480346.
  • Mandlburger, G. and H., Brockmann, 2001. Modelling a Watercourse DTM Based on Airborne Laser-Scanner Data – Using the Example of the River Oder Along the German/Polish Border. In : OEEPE Workshop on Airborne Laserscanning and Interferometric SAR for Detailed Digital Terrain Models, Official Publication No. 40, K. Torlegård and J. Nelson (Editors). European Organization for Experimental Photogrammetric Research, Frankfurt, Germany, pp. 1-10. http://bono.hostireland.com/~eurosdr/publications/40.pdf .
  • Mark, D.M., 1983. Automated Detection of Drainage Networks for Digital Elevation Models. In : Proceedings of the Sixth International Symposium on Automated Cartography, AutoCarto 6, Volume 2, B.S. Wellar (Editor). The Steering Committee, Ottawa, Canada, pp. 288-298.
  • Marks, D.M., J. Dozier, and J. Frew, 1984. Automated Basin Delineation From Digital Elevation Data. Geo-processing2(3):299-311.
  • Martz, L.W. and J. Garbrecht, 1992. Numerical Definition of Drainage Network and Subcatchment Areas From Digital Elevation Models. Computers and Geosciences18(6):747-761, doi: 10.1016/0098-3004(92)90007-E.
  • Maune, D.F., S.M. Kopp, C.A. Crawford, and C.E. Zervas, 2007a. Introduction. In : Digital Elevation Model Technologies and Applications—The DEM Users Manual (Second Edition), D.F. Maune (Editor). American Society for Photogrammetry and Remote Sensing, Bethesda, Maryland, pp. 1-35.
  • Maune, D.F., J.B. Maitra, and E.J. McKay, 2007b. Accuracy Standards and Guidelines. In : Digital Elevation Model Technologies and Applications—The DEM Users Manual (Second Edition), D.F. Maune (Editor). American Society for Photogrammetry and Remote Sensing, Bethesda, Maryland, pp. 65-97.
  • Moore, I.D., R.B. Grayson, and A.R. Ladson, 1991. Digital Terrain Modelling: A Review of Hydrological, Geomorphological and Biological Applications. Hydrological Processes5(1):3-30, doi: 10.1002/hyp.3360050103.
  • Murphy, P.N.C., J. Ogilvie, F.-R. Meng, and P. Arp, 2008. Stream Network Modelling Using LiDAR and Photogrammetric DEMs: A Comparison and Field Verification. Hydrological Processes22(12):1747-1754, doi: 10.1002/hyp.6770.
  • Nardi, F., S. Grimaldi, M. Santini, A. Petroselli, and L. Ubertini, 2008. Hydrogeomorphic Properties of Simulated Drainage Patterns Using DEMs: The Flat Area Issue. Hydrological Science Journal53(6):1176-1193, doi: 10.1623/hysj.53.6.1176.
  • National Digital Elevation Program, 2004. Guidelines for Digital Elevation Data, Version 1.0, 93 pp. http://www.ndep.gov/NDEP_Elevation_Guidelines_Ver1_10May2004.pdf.
  • National Research Council (U.S.), 2009. Mapping the Zone: Improving Flood Map Accuracy. The National Academies Press, Washington, D.C., ISBN-13: 9780309130578.
  • O’Callaghan, J.F. and D.M. Mark, 1984. The Extraction of Drainage Networks from Digital Elevation Data. Computer Vision and Graphics Image Processing28(3):323-344, doi: 10.1016/S0734-189X(84)80011-0.
  • Pan, F., M. Stieglitz, and R. McKane, 2012. An Algorithm for Treating Flat Areas and Depressions in Digital Elevation Models Using Linear Interpolation. Water Resources Research48:W00L10, doi: 10.1029/2011WR010735.
  • Passalacqua, P., T. Do Trung, E. Foufoula-Georgiou, G. Sapiro, and W.E. Dietrich, 2010. A Geometric Framework for Channel Network Extraction From Lidar: Nonlinear Diffusion and Geodesic Paths. Journal of Geophysical Research-Earth Surface115: F01002, doi: 10.1029/2009JF001254.
  • Perroy, R., L.B. Bookhagen, G.P. Asner, and O.A. Chadwick, 2010. Comparison of Gully Erosion Estimates Using Airborne and Ground-Based LIDAR on Santa Cruz Island, California. Geomorphology118(3-4): 288-300, doi: 10.1016/j.geomorph.2010.01.009.
  • Petroselli, A., 2012. LIDAR Data and Hydrological Applications at the Basin Scale. GIScience & Remote Sensing49(1):139-162, doi: 10.2747/1548-1603.49.1.139.
  • Poppenga, S., B. Worstell, J. Stoker, and S. Greenlee, 2012. Using Selective Drainage Methods to Hydrologically-Condition and Hydrologically-Enforce Lidar-Derived Surface Flow. In : Remote Sensing and Hydrology 2010, IAHS Publication 352, C. Neale (Editor). International Association of Hydrological Sciences (IAHS), Wallingford, United Kingdom, pp. 329-332.
  • Poppenga, S.K., B.B. Worstell, J.M. Stoker, and S.K. Greenlee, 2010. Using Selective Drainage Methods to Extract Continuous Surface Flow From 1-Meter Lidar-Derived Digital Elevation Data. U.S. Geological Survey Scientific Investigations Report 2010-5059, 12 pp. http://pubs.er.usgs.gov/publication/ofr20105059 .
  • Quinn, B.B. and R. López-Torrijos, 2012. Because the Surface Is Not Continuous, But Flow Lines Are: A Community Approach for Hydrologic Enforcement of Topography Data. In : Geographic Information Systems (GIS) and Water Resources VII. AWRA’s 2012 Spring Specialty Conference, S. Fox (Editor). American Water Resources Association, Middleburg, Virginia, 5 pp.
  • Scott, H.I., 2003. Ridge Route: The Road That United California. H.I. Scott, Torrance, California, ISBN-13: 9780615120003.
  • Seibert, J. and B.L. McGlynn, 2007. A New Triangular Multiple Flow Direction Algorithm For Computing Upslope Areas From Gridded Digital Elevation Models. Water Resources Research43:W04501, doi: 10.1029/2006WR005128.
  • Sheng, J., J.P. Wilson, N. Chen, J.S. Devinny, and J.M. Sayre, 2007. Evaluating the Quality of the National Hydrography Dataset for Watershed Assessments in Metropolitan Regions. GIScience & Remote Sensing44(3):1-22, doi: 10.2747/1548-1603.44.3.283.
  • Simley, J., 2006. The National Hydrography Dataset: Introduction. Water Resources Impact8(2):4. http://eh2o.saic.com/Documentation/ICWater_AWRA_Impact_Journal.pdf .
  • Stephens, M.J., M.A. Domaratz, and W.B. Schmidt, 1980. The Development of a National Small-Scale Digital Cartographic Data Base. In : AutoCarto 4. International Symposium on Cartography and Computing Applications in Health and Environment, Proceedings, R.T. Aangeenbrug (Editor). American Congress on Surveying and Mapping and American Society of Photogrammetry, Falls Church, Virginia, pp. 345-352.
  • Stoker, J., D. Harding, and J. Parrish, 2008. The Need for a National Lidar Dataset. Photogrammetric Engineering & Remote Sensing74(9):1066-1068. http://asprs.org/PE-RS-Past-Issues.html .
  • Tarboton, D.G., 1997. A New Method for the Determination of Flow Directions and Upslope Areas in Grid Digital Elevation Models. Water Resources Research33(2):309-319, doi: 10.1029/96WR03137.
  • Tarboton, D.G., R.L. Bras, and I. Rodriguez-Iturbe, 1988. The Fractal Nature of River Networks. Water Resources Research24(8):l3l7-l322, doi: 10.1029/WR024i008p01317.
  • Tarboton, D.G., R.L. Bras, and I. Rodríguez-Iturbe, 1991. On the Extraction of Channel Networks from Digital Elevation Data. Hydrological Processes5(1):81-100, doi: 10.1002/hyp.3360050107.
  • Thoma, D.P., S.C. Gupta, M.E. Bauer, and C.E. Kirchoff, 2005. Airborne Laser Scanning for Riverbank Erosion Assessment. Remote Sensing of Environment95(4):493-501, doi: 10.1016/j.rse.2005.01.012.
  • Usery, E.L., 2012. The Digital Transition in Cartography: USGS Data Innovations, 1970s. In : History of Cartography: International Symposium of the ICA Commission, 2010, E. Liebenberg and I.J. Demhardt (Editors). Springer-Verlag, Berlin, Germany, pp. 115-128.
  • USGS, 1999. Map Accuracy Standards. U.S. Geological Survey Fact Sheet FS-171-99, 2 pp. http://egsc.usgs.gov/isb/pubs/factsheets/fs17199.html.
  • Zandbergen, P., 2010. Accuracy Considerations in the Analysis of Depressions in Medium-Resolution LIDAR DEMs. GIScience & Remote Sensing47(2):187-207, doi: 10.2747/1548-1603.47.2.187.