Uncertainties associated with digital elevation models for hydrologic applications: A review

Hydrology and Earth System Sciences

Volumn 11, Issue 4, 2007, Pages 1481-1500

  Wechsler, S P ^a  

^a CALIFORNIA STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; AREAL INTERPOLATION; DIGITAL ELEVATION MODEL; DIGITAL TERRAIN MODEL; ERROR ANALYSIS; GIS; HYDROLOGICAL MODELING; HYDROLOGICAL REGIME; TOPOGRAPHY;

EID: 34547767081     PISSN: 10275606     EISSN: 16077938     Source Type: Journal    
DOI: 10.5194/hess-11-1481-2007     Document Type: Review

References (164)

1. Acevedo, W.: First Assessment of U.S. Geological Survey 30-Minute DEMs: A Great Improvement over Existing 1-Degree Data, ASPRS-ACSM Technical Papers, 2, 1-14, 1991.
2. Aerts, J., Goodchild, M., and Heuvelink, G. B. M.: Accounting for spatial uncertainty in optimization with spatial decision support systems, Transactions in GIS, 7, 211-230, 2003.
3. Airborne1: LiDAR Accuracy An Airborne1 Perspective, Briefing Note BN#01, Airborne1 Corporation, El Segundo, CA, 2006.
4. Albani, M., Klinkenberg, B., Andison, D. W., and Kkimmins, J. P.: The choice of window size in approximating topographic surfaces from Digital Elevation Models, Int. J. Geogr. Inf. Sci, 18, 577-593, 2004.
5. Armstrong, R. N. and Martz, L. W.: Topographic Parameterization in continental hydrology: a study in scale, Hydrol. Processes, 17, 3763-3781, 2003.
6. Ascough, J. C., Rector, H. D., Hoag, D. L., McMaster, G. S., Vandenberg, B. C., Shaffer, M. J., Weltz, M. A., and Ahjua, L. R.: Multicriteria Spatial Decision Support Systems: Overview, Applications, and Future Research Directions. Integrated Assessment and Decision Support Proceedings of the 1st Biennial Meeting of the IEMSs, Lugano, Switzerland 3, 175-180, 2002.
7. Bachmann, A. and Allgower, B.: Uncertainty propagation in wildland fire behaviour modelling, Int. J. Geogr. Inf. Sci, 16, 115-127, 2002.
8. Band, L. and Moore, I.: Scale: Landscape Attributes And Geographical Information Systems, Hydrol. Processes, 9, 401-422, 1995.
9. Berry, P. A. M., Hoogerboord, A. M., and Pinnock, R. A.: Identification of Common Error Signatures in Global Digital Elevation Models Based on Satellite Altimeter Reference Data, Phys. Chem. Earth (A), 25, 95-99, 2000.
10. Beven, K.: A manifesto for the equifinality thesis, J. Hydrol., 320, 18-36, 2006.
11. Beven, K.: Towards integrated environmental models of everywhere: uncertainty, data and modelling as a learning process, Hydrol. Earth Syst. Sci., 11, 460-467, 2007, http://www.hydrol-earth-syst-sci.net/11/460/2007/.
12. Beven, K. and Binley, A.: The Future of Distributed Modeling: Model Calibration and Uncertainty Prediction, Hydrol. Processes, 6, 255-264, 1992.
13. Bolstad, P. and Stowe, T.: An Evaluation of DEM Accuracy: Elevation, Slope, and Aspect, Photogramm. Eng. Rem. S., 60, 1327-1332, 1994.
14. Brasington, K. and Richards, K.: Interactions Between Model Predictions, Parameters and DTM Scales for TopModel, Comput. Geosci., 24, 299-314, 1998.
15. Brunsdon, C. and Openshaw, S.: Chapter 7: Simulating the effects of error in GIS, in: Geographical Information Handling - Research and Applications, edited by: Mather, P., John Wiley and Sons, New York, 47-61, 1993.
16. Burrough, P. and McDonnell, R.: Principles of Geographic Information Systems, Oxford University Press, New York, NY, 333 p., 1998.
17. Burrough, P. A.: Principles of Geographical Information Systems for Land Resources Assessment, Oxford University Press, New York, NY, 194 p., 1986.
18. Canters, F., DeGenst, W., and Dufourmont, H.: Assessing effects of input uncertainty in structural landscape classification, Int. J. Geogr. Inf. Sci, 16, 129-149, 2002.
19. Carter, J.: Some Effects of Spatial Resolution in the Calculation of Slope Using the Spatial Derivative, ASPRS-ACSM Annual Convention - Technical Papers, 1, 43-52, 1990.
20. Chang, K.-T and Tsai, B.-W.: The effect of DEM Resolution on Slope and Aspect Mapping, Cartography and GIS, 18, 67-99, 1991.
21. Chaplot, V.: Impact of DEM mesh size and soil map scale on SWAT runoff, sediment, and NO3-N loads predictions, J. Hydrol., 312, 207-222, 2005.
22. Chaubey, I., Cotter, A. S., Costello, T. A., and Soerens, T. S.: Effect of DEM data resolution on SWAT output uncertainty, Hydrol. Processes, 19, 621-628, 2005.
23. Chochrane, T. A. and Flanagan, D. C.: Effect of DEM Resolutions in the runoff and soil loss predictions of the WEPP watershed model, Transactions of the ASAE, 48, 109-120, 2005.
24. Chrisman, N.: Error in Categorical Maps: Testing versus Simulation. Auto-Carto 9: Proceedings of the 9th International Symposium, on Computer-Assisted Cartography, ASPRS/ACSM, Baltimore, Maryland, 521-529, 1989.
25. Claessens, L., Heuvelink, G. B. M., Schoorl, J. M., and Veldkamp, A.: DEM resolution effects on shallow landslide hazard and soil redistribution modelling, Earth Surf. Proc. Land., 30, 461-477, 2005.
26. Costa-Cabral, M. and Burgess, S.: Digital Elevation Model Networks (DEMON): A model of flow over hillslopes for computation of contributing and dispersal areas, Water Resour. Res., 30, 681-1692, 1994.
27. Cowell, P. and Zeng, T.: Integrating uncertainty theories with GIS for modeling coastal hazards of climate change, Mar. Geod., 26, 5-18, 2003.
28. Crosetto, M. and Tarantola, S.: Uncertainty and sensitivity analysis: tools for GIS-based model implementation, Int. J. Geogr. Inf. Sci, 15, 415-437, 2001.
29. Davis, T. J. and Keller, C. P.: Modeling and Visualizing Multiple Spatial Uncertainties, Comput. Geosci., 23, 397-408, 1997.
30. deBruin, S. and deWit, A. J. W.: Stochastic simulation of large grids using free and public domain software, Comput. Geosci., 31, 828-836, 2005.
31. Desmet, P. and Govers, G.: Comparison of routing algorithms for digital elevation models and their implications for predicting ephemeral gullies, Int. J. Geogr. Inf. Syst., 10, 311-331, 1996.
32. Desmet, P. J. J.: Effects of Interpolation Errors on the Analysis of DEMs, Earth. Surf. Proc. Land., 22, 563-580, 1997.
33. Deutsch, C. and Journel, A.: GSLIB Geostatistical Software Library and User's Guide, Oxford University Press, New York, 369 p., 1998.
34. Dubois, G., Malczewski, J., and Cort, M. D.: Spatial Interpolation Comparison 97: Special Issue, Journal of Geographic Information and Decision Analysis, 2, Special Issue, 1998.
35. Dunn, M. and Hickey, R.: The effect of slope algorithms on slope estimates within a GIS, Cartography, 27, 9-15, 1998.
36. Durañona, G. and López, C.: DM4DEM: a GRASS-compatible tool for blunder detection of DEM, 4th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, Amsterdam, The Netherlands, 191-194, 2000.
37. Eastman, R.: Idrisi, Clark University Graduate School of Geography, Worcester, MA, 1992.
38. Ehlschlaeger, C.: The Stochastic Simulation Approach: Tools for Representing Spatial Application Uncertainty, University of California Santa Barbara, Santa Barbara, CA, Ph.D. Dissertation, 1998.
39. Ehlschlaeger, C. and Shortridge, A.: Modeling Elevation Uncertainty in Geographical Analyses, Proceedings of the International Symposium, on Spatial Data Handling, Delft, Netherlands, 9B.15-19B.25, 1996.
40. Ehlschlaeger, C. R.: Representing multiple spatial statistics in generalized elevation uncertainty models: moving beyond the variogram, Int. J. Geogr. Inf. Sci, 16, 259-285, 2002.
41. Ehlschlaeger, C. R., Shortridge, A. M., and Goodchild, M. F.: Visualizing Spatial Data Uncertainty Using Animation, Comput. Geosci., 23, 387-395, 1997.
42. Endreny, T. A. and Wood, E. F.: Representing elevation uncertainty in runoff modelling and flowpath mapping, Hydrol. Processes, 15, 2223-2236, 2001.
43. Englund, E.: Spatial Simulation: Environmental Applications, Chapter 43, in: Environmental Modeling with GIS, edited by: Goodchild, M., Parks, B., and Steyaert, L., Oxford University Press, New York, 432-446, 1993.
44. Erxleben, J., Elder, K., and Davis, R.: Comparison of spatial interpolation methods for estimating snow distribution in the Colorado Rocky Mountains, Hydrol. Processes, 16, 3627-3649, 2002.
45. ESRI: ArcView Spatial Analyst, Environmental Systems Research Institute, Redlands, CA, 1998.
46. Evans, I.: What Do Terrain Statistics Really Mean?, in: Landform Monitoring, Modelling and Analysis, edited by: Lane, S. N., Richards, K. S., and Chandler, J. H., John Wiley and Sons, New York, 300 p., 1998.
47. FGDC: Geospatial Positioning Accuracy Standards Part 3: National Standard for Spatial Data Accuracy, FGDC-STC-007.3-1998, USGS Federal Geographic Data Committee, 25 pp., 1998.
48. Fisher, P.: Algorithm and Implementation Uncertainty in Viewshed Analysis, Int. J. Geogr. Inf. Sci., 7, 331-347, 1993.
49. Fisher, P.: Animation and Sound For the Visualization of Uncertain Spatial Information, Chapter 19, in: Visualization In Geographical Information Systems, edited by: Hearnshaw, H. and Unwin, D., John Wiley and Sons, 181-185, 1994.
50. Fisher, P.: Sorites paradox and vague geographies, Fuzzy Set Syst., 113, 7-18, 2000.
51. Fisher, P. F.: First experiments in viewshed uncertainty: the accuracy of the viewshed area, Photogramm. Eng. Rem. S., 57, 1321-1327, 1991.
52. Fisher, P. F.: Improved Modeling of Elevation Error with Geostatistics, GeoInformatica, 2, 215-233, 1998.
53. Freer, J., Beven, K., and Ambroise, B.: Bayesian estimation of uncertainty in runoff prediction and the value of data: An application of the GLUE approach, Water Resour. Res., 32, 2161-2174 1996.
54. Gao, J.: Resolution and Accuracy of Terrain Representation by Grid DEMs at a micro-scale, Int. J. Geogr. Inf. SCi, 11, 199-212, 1997.
55. Garbrecht, J. and Martz, L.: Grid Size Dependency Of Parameters Extracted From Digital Elevation Models, Comput. Geosci., 20, 85-87, 1994.
56. Goodchild, M.: Algorthm 9: Simulation of autocorrelation for aggregate data, Environ. Plann. A., 12, 1073-1081, 1980.
57. Goodchild, M., Shortridge, A., and Fohl, P.: Encapsulating Simulation Models with Geospatial Data Sets, in: Spatial Accuracy Assessment: Land Information Uncertainty in Natural Resources, edited by: Lowell, K. and Jaton, A., Ann Arbor Press, Ann Arbor, Michigan, 1999.
58. Goodchild, M., Sun, G., and Yang, S.: Development and Test of an Error Model for Categorical Data, Int. J. Geogr. Inf. Syst., 6, 87-104, 1992.
59. Gunther, A.: SLOPEMAP: programs for automated mapping of geometrical and kinematical properties of hard rock hill slopes, Comput. Geosci., 29, 865-875, 2003.
60. Guth, P. L.: Slope and aspect calculations on gridded digital elevation models: Examples form a geomorphic toolbox for personal computers, Z. Geomorph, N. F., Suppl. 101, 31-52, 1995.
61. Hancock, G. R.: The use of digital elevation models in the identification and characterization of catchments over different grid scales, Hydrol. Processes, 19, 1727-1749, 2005.
62. Hengl, T., Gruber, S., and Shrestha, D. P.: Reduction of errors in digital terrain parameters used in soil-landscape modelling, Int. J. Appl. Earth Obs. Geoinfo., 5, 97-112, 2004.
63. Heuvelink, G., Burrough, P., and Stein, A.: Propagation of errors in spatial modeling with GIS, Int. J. Geogr. Inf. Sci., 3, 303-322, 1989.
64. Heuvelink, G., Burrough, P., and Stein, A.: Developments in Analysis of Spatial Data Uncertainty Since 1989, in: Classics from IJGIS: twenty years of the International Journal of Geographical Information Science and Systems, edited by: Fisher, P., Taylor and Francis, Boca Raton, FL, 91-95, 2007.
65. Heuvelink, G. B. M.: Error Propagation in Environmental Modelling with GIS, Taylor & Francis Ltd, London, England, 127 p., 1998.
66. Heuvelink, G. B. M.: Analysing Uncertainty Propagation in GIS: Why is it not that simple?, in: Uncertainty in Remote Sensing and GIS, edited by: Foody, G. M. and Atkinson, P. M., John Wiley & Sons, West Sussex, England, .155-165, 2002.
67. Hickey, R.: Slope Angle and Slope Length Solutions for GIS, Cartography, 29, 1-8, 2001.
68. Holmes, K. W., Chadwick, O. A., and Kyriakidis, P. C.: Error in a USGS 30-meter digital elevation model and its impact on terrain modeling, J. Hydrol., 233, 154-173, 2000.
69. Horn, B.: Hill Shading and the Reflectance Map, Proceedings of the IEEE, 69, 14-47, 1981.
70. Hunter, G. and Goodchild, M.: Dealing with Error in Spatial Databases: A Simple Case Study, Photogramm. Eng. Rem. S., 61, 529-537, 1995.
71. Hunter, G. and Goodchild, M.: Modeling the Uncertainty of Slope and Aspect Estimates Derived From Spatial Databases, Geogr. Anal., 29, 35-49, 1997.
72. Hutchinson, M. F.: A New Procedure for Gridding Elevation and Stream Line Data with Automatic Removal of Spurious Pits, J. Hydrol., 106, 211-232, 1989.
73. Hutchinson, M. F.: ANUDEM Version 5.2, Centre for Resource and Environmental Studies, The Australian National University, 2006.
74. Hwang, D., Karmi, H. A., and Byun, D. W.: Uncertainty Analysis of Environmental Models Within GIS Environments, Comput. Geosci., 24, 119-130, 1998.
75. Jankowski, P., Andrienko, N., and Andrienko, G.: Map-centered exploratory approach to multiple criteria spatial decision making, Int. J. Geogr. Inf. Sci, 15, 101-127, 2001.
76. Jenson, S.: Applications of Hydrologic Information Automatically Extracted from Digital Elevation Models, Hydrol. Processes, 5, 31-44, 1991.
77. Jenson, S. and Domingue, J. O.: Extracting topographic structure from Digital Elevation Data for Geographic Information System Analysis, Photogramm. Eng. Rem. S., 54, 1593-1600, 1988.
78. Johnson, D. L. and Miller, A. C.: A Spatially Distributed Hydrologic Model Utilizing Raster Data Structures, Comput. Geosci., 23, 267-272, 1997.
79. Journel, A.: Modelling uncertainty and spatial dependence: stochastic imaging, Int. J. Geogr. Inf. Syst., 10, 517-22, 1996.
80. Karssenberg, D. and Jong, K. D.: Dynamic environmental modelling in GIS: 2. Modelling error propagation, Int. J. Geogr. Inf. Sci, 19, 623-637, 2005.
81. Kenward, T., Lettenmaier, D. P., Wood, E. F., and Fielding, E.: Effects of Digital Elevation Model Accuracy on Hydrologic Predictions, Remote Sens. Env., 74, 432-444, 2000.
82. Kienzle, S.: The effect of DEM Resolution on First Order, Second Order and Compound Terrain Derivatives, Transactions in GIS, 8, 83-111, 2004.
83. Kuo, W., Steenhuis, T., McCulloch, C., Mohler, C., Weinstein, D., DeGloria, S., and Swaney, D.: Effect of grid size on runoff and soil moisture for a variable-source-area hydrology model, Water Resour. Res., 35, 3419-3428, 1999.
84. Kyriakidis, P. C., Shortridge, A. M., and Goodchild, M. F.: Geostatistics for conflation and accuracy assessment of digital elevation models. Int. J. Geogr. Inf. Sci, 13, 677-707, 1999.
85. Lacroix, M. P., Martz, L. W., Kite, G. W., and Garbrecht, J.: Using digital terrain analysis modeling techniques for the parameterization of a hydrologic model, Environ. Modell. Software, 17, 127-136, 2002.
86. Lagacherie, P., Moussa, R., Cormary, D., and Molenat, J.: Effects of DEM data source and sampling pattern on topographical parameters and on a topography-based hydrological model Application of geographic information systems in hydrology and water resources management, Vienna, Austria, 1996.
87. Lee, J., Snyder, P., and Fisher, P.: Modeling the Effect of Data Errors on Feature Extraction From Digital Elevation Models, Photogramm. Eng. Rem. S., 58, 1461-1467, 1992.
88. Li, Z.: Effects of Check Points on the Reliability of DTM Accuracy Estimates Obtained From Experimental Tests, Photogramm. Eng. Rem. S., 57, 1333-1340, 1991.
89. Li, Z.: Variation of the Accuracy of Digital Terrain Models With Sampling Interval, Photogramm. Rec., 14, 113-128, 1992.
90. Li, Z.: A comparative study of the accuracy of digital terrain models (DTMs) based on various data models, ISPRS Journal of Photogrammetry and Remote Sensing, 49, 2-11, 1994.
91. Lindsay, J. B.: Sensitivity of channel mapping techniques to uncertainty in digital elevation data, Int. J. Geogr. Inf. Sci, 20, 669-692, 2006.
92. Lindsay, J. B. and Creed, I. F.: Removal of artifact depressions from digital elevation models: towards a minimum impact approach, Hydrol. Processes, 19, 3113-3126, 2005a.
93. Lindsay, J. B. and Creed, I. F.: Sensitivity of Digital Landscapes to Artifact Depressions in Remotely-sensed DEMs, Photogramm. Eng. Rem. S., 71, 1029-1036, 2005b.
94. Lindsay, J. B. and Creed, I. F.: Distinguishing actual and artefact depressions in digital elevation data, Comput. Geosci., 32, 1192-1204, 2006.
95. Liu, R. and Herrington, L.: The Effects of Spatial Data Error on Forest Management Decisions. Proceedings of the GIS 1993 Symposium, Vancouver, British Columbia, 1-8, 1993.
96. Lopez, C.: An experiment on the elevation accuracy improvement of photogrammetrically derived DEM, Int. J. Geogr. Inf. Sci, 16, 361-375, 2002.
97. Mark, D.: Network Models In Geomorphology, Modeling in Geomorphological Systems, John Wiley and Sons, New York, 1988.
98. Martz, L. W. and Garbrecht, J.: An outlet breaching algorithm for the treatment of closed depressions in a raster DEM, Comput. Geosci., 25, 835-844, 1999.
99. Maune, D. F.: Digital Elevation Model Technologies and Applications: The DEM Users Manual, The American Society for Photogrammetry and Remote Sensing, Bethesda, Maryland, 2001.
100. Miliaresis, G. C. and Paraschou, C. V. E.: Vertical accuracy of the SRTM DTED level 1 of Crete, Int. J. Appl. Earth Obs. Geoinfo., 7, 49-59, 2005.
101. Monckton, C.: An Investigation into the spatial structure of error in digital elevation data, Chapter 14, in: Innovations in GIS, edited by: Worboys, M., Taylor and Francis, Bristol, PA, 201-210, 1994.
102. Murillo, M. L. and Hunter, G. J.: Assessing uncertainty due to elevation error in a landslide susceptibility model Transactions in GIS, 2, 289-298, 1997.
103. O'Callaghan, J. F. and Mark, D. M.: The extraction of drainage networks from digital elevation data. Computer Visualization Graph, Image Proceedings of GIS/LIS, 28, 323-344, 1984.
104. Oksanen, J.: Digital Elevation Model Error In Terrain Analysis, University of Helsinki, Helsinki, Finland, Ph.D., 51 p., 2006.
105. Oksanen, J. and Sarjakoski, T.: Error Propagation analysis of DEM- based drainage basin delineation, Int. J. Rem. Sens., 26, 3085-3102, 2005a.
106. Oksanen, J. and Sarjakoski, T.: Error propagation of DEM-based surface derivatives, Comput. Geosci., 31, 1015-1027, 2005b.
107. Oksanen, J. and Sarjakoski, T.: Uncovering the statistical and spatial characteristics of fine toposcale DEM error, Int. J. Geogr. Inf. SCi, 20, 345-369, 2006.
108. Openshaw, S., Charlton, M., and Carver, S.: Error Propagation: A Monte Carlo Simulation, in: Handling Geographical Information - Methodology and Potential Applications, edited by: Masser, I. and Blakemore, M., John Wiley and Sons, 1991.
109. Perlitsh, S.: Integration of GIS with the Agricultural Non-Point Source Pollution Model: The Effect of Resolution and Soils Data Sources On Model Input and Output, EPA, 164-174, 1994.
110. Pike, R.: A Bibliography of Terrain Modeling (Geomorphometry), the Quantitative Representation of Topography-Supplement 4.0, USGS, 158 pp., 2002.
111. Quattrochi, D. and Goodchild, M.: Scale in Remote Sensing and GIS, CRC Press, Boca Raton, FL, 406 p., 1997.
112. Quinn, P., Beven, K., Chevallier, P., and Planchon, O.: The Prediction of Hillslope Flow Paths For Distributed Hydrological Modelling Using Digital Terrain Models, Hydrol. Processes, 5, 59-79, 1991.
113. Quinn, P., Beven, K., and Lamb, R.: The ln(a/TanB) index: how to calculate it and how to use it within the TOPMODEL framework, Hydrol. Processes, 9, 161-182, 1995.
114. Refsgaard, J. C., Sluijs, J. P. v. d., Højberg, A. L., and Vanrolleghem, P.: Harmoni-CA Guidance Uncertainty Analysis Guidance 1, A research project supported by the European Commission under the Fifth Framework Programme and contributing to the implementation of the Key Action "Sustainable Management and Quality of Water" within the Energy, Environment and Sustainable Development, Contract no: EVK1-2001-00192, 46, 2004.
115. Reitsma, F. and Albrecht, J.: Implementing a new data model for simulating processes, Int. J. Geogr. Inf. Sci, 19, 1073-1090, 2005.
116. Rieger, W.: A phenomenon-based approach to upslope contributing area and depressions in DEMs, Hydrol. Processes, 12, 857-872, 1998.
117. Rodhe, A. and Seibert, J.: Wetland occurrence in relation to topography: a test of topographic indices as moisture indicators, Agric. For. Meteorol., 98-99, 325-340, 1999.
118. Saghafian, B., Lieshout, A. M. v., and Rajaei, H.: Distributed Catchment Simulation using a raster GIS, JAG, 2, 199-203, 2000.
119. Saulnier, G.-M., Obled, C., and Beven, K.: Analytical Compensation between DTM Grid Resolution and Effective Values of Saturated Hydraulic Conductivity Within the TopModel Framework, Hydrol. Processes, 11, 1331-1346, 1997.
120. Schoorl, J. M., Sonneveld, M. P. W., and Veldkamp, A.: Three-Dimensional landscape process modelling: The Effect of DEM Resolution, Earth Surf. Proc. Land., 25, 1025-1034, 2000.
121. Shan, J., Zaheer, M., and Hussain, E.: Study on Accuracy of 1- Degree DEM Versus Topographic Complexity Using GIS Zonal Analysis, J. Surv. Eng. ASCE, 129, 85-89, 2003.
122. Skidmore, A.: A Comparison of techniques for Calculating Gradient and Aspect From A Gridded Digital Elevation Model, Int. J. Geogr. Inf. Sci, 3, 323-334, 1989.
123. Spear, M., Hall J., and Wadsworth, R.: Communication of Uncertainty in Spatial Data to Policy makers. Spatial Accuracy Assessment in Natural Resources and Environmental Sciences: Second International Symposium, Rocky Mountain Forest and Range Experiment Station, Fort Collins, CO, Report RM-GTR- 277, 199-207, 1996.
124. Srivasta, R.: An Overview of Stochastic Spatial Simulation, Spatial Accuracy Assessment in Natural Resources and Environmental Sciences: Second International Symposium, Rocky Mountain Forest and Range Experiement Station, Fort Collins, CO, 13-29, 1996.
125. Suna, G., Ransonb, K. J., Kharukc, V. I., and Kovacsd, K.: Validation of surface height from shuttle radar topography mission using shuttle laser altimeter, Remote Sens. Env., 88, 401-411, 2003.
126. Tang, G.-A., Hui, Y-H., Strobl, J., and Lui, W-Q.: The impact of resolution accuracy of hydrologic data derived from DEMs, J. Geogr. Sci., 11, 393-401, 2001.
127. Tarboton, D.: A new method for the determination of flow directions and upslope areas in grid digital elevation models, Water Resour. Res., 33, 309-319, 1997.
128. Tarboton, D., Bras, R., and Rodriguez-Iturbe, I.: On the extraction of channel networks from digital elevation data, in: Terrain Analysis and Distributed Modeling In Hydrology, edited by: Beven, K. and Moore, I. D., John Wiley and Sons, New York, 85-104, 1993.
129. Taylor, J.: An Introduction to Error Analysis: The Study of Uncertainties In Physical Measurements, University Science Books, Sausalito, CA, 327 p., 1997.
130. Theobald, D.: Accuracy and Bias Issues in surface representation, Chapter 9, in: The Accuracy of Spatial Databases, edited by: Goodchild, M. F. and Gopal, S., Taylor and Francis, Bristol, PA, 99-106, 1989.
131. Thompson, J. A., Bell, J. C., and Butler, C. A.: Digital elevation model resolution: effects on terrain attribute calculation and quantitative soil-landscape modeling, Geoderma, 100, 67- 89, 2001.
132. Tobler, W. R.: A computer movie simulating urban growth in the Detroit region, Econ. Geogr., 46, 234-240, 1970.
133. Toutin, T.: Impact of terrain slope and aspect on radargrammetric DEM accuracy, ISPRS Journal of Photogrammetry and Remote Sensing, 57, 228-240, 2002.
134. USGS, U.S. Geological Survey: Standards For Digital Elevation Models, Part 1: General, Part 2: Specifications, Part 3: Quality Control., 1997.
135. Usul, N. and Pasaogullari, O.: Effect of Map Scale and Grid Size for Hydrologic Modelling. GIS and Remote Sensing in Hydrology, Water Resources and Environment, Three Gorges Dam, China, 289, 91-100, 2004.
136. Valeo, C. and. Moin, S.: Grid-resolution effects on a model for integrating urban and rural areas, Hydrol. Processes, 14, 2505-2525, 2000.
137. Van Niel, K., Laffan, S., and Lees, B.: Effect of error in the DEM on environmental variables for predictive vegetation modeling, J. Veg. Sci., 15, 747-756, 2004.
138. Veregin, H.: Integration of Simulation Modeling and Error Propagation for the Buffer Operation in GIS, Photogramm. Eng. Rem. S., 60, 427-435, 1994.
139. Veregin, H.: The effects of vertical error in Digital Elevation Models on the determination of flowpath direction, Cartography and GIS, 24, 67-79, 1997.
140. Vieux, B. and Needham, H.: Nonpoint Pollution Model Sensitivity To Grid Cell Size, J. Water Res. Pl. ASCE, 119, 141-157, 1993.
141. Vogt, J. V., Colombo, R., and Bertolo, F.: Deriving drainage networks and catchment boundaries: a new methodology combining digital elevation data and environmental characteristics, Geomorphology, 53, 281-298, 2003.
142. Wang, L.-W. and Trinder, J.: Analysis and evaluation of the DEM derived from TOPSAR Airborne Interferometric SAR System, The Australian Surveyor, 44, 174-182, 1999.
143. Wang, X. and Yin, Z.-Y.: A comparison of drainage networks derived from digital elevation models at two scales, J. Hydrol., 210, 221-241, 1998.
144. Wechsler, S. P.: Effect of DEM Uncertainty on Topographic Parameters, DEM Scale and Terrain Evaluation, State University of New York College of Environmental Science and Forestry, Syracuse, NY, Ph.D. Dissertation, 380 p., 2000.
145. Wechsler, S. P.: Perceptions of Digital Elevation Model Uncertainty by DEM Users, URISA Journal, 15, 57-64, 2003.
146. Wechsler, S. P. and Kroll, C.: Quantifying DEM Uncertainty and its Effect on Topographic Parameters, Photogramm. Eng. Rem. S., 72, 1081-1090, 2006.
147. Widayati, A., Lusiana, B., Suyamto, D., and Verbist, B.: Uncertainty and effects of resolution of digital elevation model and its derived features: case study of Sumberjaya, Sumatera, Indonesia, Int. Arch. of Photogrammetry and Remote Sensing, 35, 1013-1018, 2004.
148. Wilson, J. P. and Gallant, J. C.: Terrain Analysis Principles and Applications, John Wiley & Sons, New York, NY, 479 p., 2000.
149. Wise, S.: The Effect of GIS Interpolation Errors on the Use of Digital Elevation Models in Geomorphology, in: Landform Monitoring, Modelling and Analysis, edited by: Lane, S. N., Richards, K. S., and Chandler, J. H., John Wiley and Sons, 300 p., 1998.
150. Wise, S.: Assessing the quality for hydrological applications of digital elevation models derived from contours, Hydrol. Processes, 14, 1909-1929, 2000.
151. Wise, S., Haining, R., and Ma, J.: Providing spatial statistical data analysis functionality for the GIS user: the SAGE project, Int. J. Geogr. Inf. Sci, 15, 239-254, 2001.
152. Wolock, D. and McCabe, G.: Comparison of single and multiple flow direction algorithms for computing topographic parameters, Water Resour. Res., 31, 1315-1324, 1995.
153. Wolock, D. and Price, C.: Effects of digital elevation model map scale and data resolution on a topography-based watershed model, Water Resour. Res., 30, 3041-3052, 1994.
154. Wood, J.: The Geomorphological Characterization of Digital Elevation Models, University of Leicester, Leicester, UK, 1996.
155. Wood, J. D. and Fisher, P. F.: Assessing Interpolation Accuracy in Elevation Models, IEEE Comput Graph, 13, 48-56, 1993.
156. Worboys, M. F.: Nearness relations in environmental space, Int. J. Geogr. Inf. Sci, 15, 633-651, 2001.
157. Yilmaz, M., Usul, N., and Akyurek, Z.: Modeling the Propagation of DEM Uncertainty in Flood Inundation, ESRI User Conference 2004, San Diego, CA, 2004.
158. Yin, Z.-Y. and Wang, X.: Technical Communication: A Cross-Scale Comparison of Drainage Basin Characteristics Derived from Digital Elevation Models Earth Planet Sc. Lett., 24, 557-567, 1999.
159. Zerger, A.: Examining GIS decision utility for natural hazard risk modelling, Environmental Modeling & Software, 17, 287-294, 2002.
160. Zevenbergen, L. and Thorne, C.: Quantitative Analysis of Land Surface Topography, Earth Surf. Proc. Land., 12, 47-56, 1987.
161. Zhang, J. and Stuart, N.: Fuzzy methods for categorical mapping with image-based land cover data, Int. J. Geogr. Inf. Sci, 15, 175-195, 2001.
162. Zhang, W. and Montgomery, D.: Digital elevation model grid size, landscape representation and hydrologic simulations, Water Resour. Res., 30, 1019-1028, 1994.
163. Zhou, Q. and Liu, X.: Error assessment of grid-based flow routing algorithms used in hydrological models, Int. J. Geogr. Inf. Sci, 16, 819-842, 2002.
164. Zhou, Q. and Liu, X.: Analysis of errors of derived slope and aspect related to DEM data properties, Comput. Geosci., 30, 369-378, 2004.