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An efficient method for identifying and filling surface depressions in digital elevation models for hydrologic analysis and modelling
Abstract
Identification and removal of surface depressions is a critical step for automated modelling of surface rainfall runoff based on Digital Elevation Models (DEMs). At present, nearly all GIS and hydrologic software packages employ Jenson and Domingue's method for preparing depressionless DEMs for hydrologic analysis. This conventional method is computationally intensive and time‐consuming. With the growing availability of high‐resolution DEMs produced by airborne LIDAR and InSAR techniques, GIS‐based hydrologic applications often need to handle larger geographic areas at finer resolutions. In the face of high‐resolution DEMs, the conventional method becomes inadequate and deficient. In this paper, we present a new method for efficiently identifying and filling surface depressions in DEMs. This method can simultaneously determine flow paths and spatial partition of watersheds with one pass of processing. A novel concept of spill elevation and the least‐cost search for optimal flow paths are the two cornerstones of our method. The time complexity of our method is in O(Nlog N). It has been implemented using C++ programming language and successfully applied to USGS DEMs and LIDAR DEMs of various sizes. Experiments show that our method outperforms the conventional method by a factor of over 30, in terms of running time.
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The DEMs were corrected for unrealistic geomorphology introduced by adding the random error field using a sink fill algorithm that removes surface depressions.
“The DEMs were then corrected for unrealistic geomorphology that might have been introduced when adding the random error field (Temme et al., 2009, p. 131).This was achieved through the use of a sink fill algorithm, which removes surface depressions in DEMs (Choi, 2018;Wang & Liu, 2006).”
From Probabilistic modelling for incorporating uncertainty in least cost path results: a postdictive roman road case study (2021) · cites this paper as Wang & Liu, 2006
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A Formal Basis for the Heuristic Determination of Minimum Cost Paths
Hart, P., Nilsson, N., & Raphael, B. (1968) · IEEE Transactions on Systems Science and Cybernetics · doi:10.1109/tssc.1968.300136 · Cited by 12,738
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Research works printed but not linked: 32
- 10.1029/WR022i001p00015 · DOI
- Band L. E., 1999, Geographical Information Systems Volume 1: Principles and Technical Issues, 527
- 10.1029/2002WR001754 · DOI
- Cormen T. H., 1996, Introduction to Algorithms
- Dechter R., 1988, Search in Artificial Intelligence, 166, 10.1007/978-1-4613-8788-6_5 · DOI
- 1994, Cell‐Based Modeling with GRID
- 1999, Technical Documentation of ArcInfo, version 8.0.1
- 10.1016/S0022-1694(96)03138-1 · DOI
- Garbrecht J., 2000, Hydrologic and Hydraulic Modeling Support with Geographic Information Systems, 1
- 10.1111/j.1467-8306.1987.tb00158.x · DOI
- 2002, Off the Charts: Tropical Storm Allison Public Report, Tropical Storm Allison Recovery Project
- 10.1016/S0034-4257(02)00114-1 · DOI
- Hutchinson M. F., 1988, Proceedings of the Third International Symposium on Spatial Data Handling, 117
- 10.1016/0022-1694(89)90073-5 · DOI
- Jenson S. K., 1988, Photogrammetric Engineering and Remote Sensing, 54, 1593
- 10.1080/13658810050024278 · DOI
- 10.1029/98WR00094 · DOI
- Mark D. M., 1983, Cartographica, 21, 168, 10.3138/10LM-4435-6310-251R · DOI
- Marks D., 1984, Geo‐Processing, 2, 299
- 10.1002/(SICI)1099-1085(199805)12:6<843::AID-HYP658>3.0.CO;2-R · DOI
- 10.1002/hyp.3360050103 · DOI
- Moore I. D., 1993, Environmental Modeling with GIS, 196
- 10.1016/S0734-189X(84)80011-0 · DOI
- Oliver F., 2000, Hydrologic and Hydraulic Modeling Support with Geographic Information Systems, 85
- Peckham, S. 1995. “Self‐similarity in the geometry and dynamics of large river basins.”. PhD thesis, University of Colorado
- 10.1016/S0341-8162(01)00164-3 · DOI
- Sedgewick R., 2002, Algorithms in C++: Part 5 Graph Algorithms
- Srinivasan R., 1991, Applied Engineering in Agriculture, 7, 779, 10.13031/2013.26302 · DOI
- 10.1029/96WR03137 · DOI · Paper page
- 10.1002/hyp.3360050107 · DOI
- 10.1016/0022-1694(92)90206-B · DOI
- 2002, Geospatial Hydrologic Modeling Extension HEC‐GeoHMS User's Manual Version 1.0
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Lewis, J. (2021) · Journal of Archaeological Method and Theory · doi:10.1007/s10816-021-09522-w · Cited by 53
Metadata
- Authors
- Wang, L., & Liu, H.
- Venue
- International Journal of Geographical Information Science
- Publisher
- Informa UK Limited
- Published
- 2006-02
- Volume
- 20
- Issue
- 2
- Pages
- 193-213
- ISSN
- 1365-8816
- 1362-3087
- Cited by
- 506
- References
- 1
- Language
- en
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