Comparison of Flow Direction Algorithms in the Application of the CTI for Mapping Wetlands in Minnesota
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- 作者：Lian P. Rampi (1) (2)
Joseph F. Knight (1)
Christian F. Lenhart (1) - 关键词：Wetland mapping ; Lidar ; Flow direction algorithm ; Compound topographic index
- 刊名：Wetlands
- 出版年：2014
- 出版时间：June 2014
- 年：2014
- 卷：34
- 期：3
- 页码：513-525
- 全文大小：
- 参考文献：1. Anteau MJ, Afton AD (2009) Wetland use and feeding by lesser scaup during spring migration across the upper Midwest, USA. Wetlands 29:704-12 f="http://dx.doi.org/10.1672/08-157.1" target="_blank" title="It opens in new window">CrossRef
2. Antonarakis AS, Richards KS, Brasington J (2008) Object-based land cover classification using airborne Lidar. Remote Sensing of Environment 112:2988-998 f="http://dx.doi.org/10.1016/j.rse.2008.02.004" target="_blank" title="It opens in new window">CrossRef
3. Beven KJ, Kirkby MJ (1979) A physically based, variable contributing area model of basin hydrology. Hydrological Sciences Journal 24:43-9 f="http://dx.doi.org/10.1080/02626667909491834" target="_blank" title="It opens in new window">CrossRef
4. Bridgham SD, Pastor J, Dewey B, Weltzin JF, Updegraff K (2008) Rapid carbon response of peatlands to climate change. Ecology 89:3041-048 f="http://dx.doi.org/10.1890/08-0279.1" target="_blank" title="It opens in new window">CrossRef
5. Burrough PA, McDonell RA (1998) Principles of geographical information systems. Oxford University Press, New York, 190 pp
6. Chaplot V, Walter C (2003) Subsurface topography to enhance the prediction of the spatial distribution of soil wetness. Hydrological Processes 17:2567-580 f="http://dx.doi.org/10.1002/hyp.1273" target="_blank" title="It opens in new window">CrossRef
7. Charman DJ (2009) Peat and peatlands. Elsevier Inc, 541-48
8. City of Chanhassen Surface Water Management Plan (2006) In: The second generation surface water management plan - Chanhassen, Minnesota: f="http://www.ci.chanhassen.mn.us/serv/cip/swmp/wetlandsmanagement.htm" class="a-plus-plus">http://www.ci.chanhassen.mn.us/serv/cip/swmp/wetlandsmanagement.htm. Accessed 25 May 2013
9. Congalton RG, Green K (2009) Assessing the accuracy of remotely sensed data: principles and practices, 2nd edn. CRC Press/Taylor and Francis, Boca Raton
10. Corcoran JM, Knight JF, Brisco B, Kaya S, Cull A, Murnaghan K (2011) The integration of optical, topographic, and radar data for wetland mapping in northern Minnesota. Canadian Journal of Remote Sensing 37(5):564-82 f="http://dx.doi.org/10.5589/m11-067" target="_blank" title="It opens in new window">CrossRef
11. Costa-Cabral M, Burges SJ (1994) Digital elevation model networks (DEMON): a model of flow over hillslopes for computation of contributing and dispersal areas. Water Resources Research 30:1681-692 f="http://dx.doi.org/10.1029/93WR03512" target="_blank" title="It opens in new window">CrossRef
12. Cowardin, L.M., V. Carter, F.C. Golet, and E.T. LaRoe, 1974. Classification of wetlands and deepwater habitats of the United States, U.S. Department of the Interior, Fish and Wildlife Service, Washington, D.C.
13. Dahl TE (2006) Status and trends of wetlands in the conterminous United States 1998 to 2004. U.S. Department of the Interior; Fish and Wildlife Service, Washington, D.C., p 112
14. Dahl TE, Johnson CE (1991) Status and trends of wetlands in the conterminous United States, mid-1970’s to mid-1980’s. U.S. Fish and Wildlife Service, Washington, DC, p 28
15. Erskine RH, Green TR, Ramirez JA, MacDonald LH (2006) Comparison of grid-based algorithms for computing upslope contributing area. Water Resources Research 42, W09416 f="http://dx.doi.org/10.1029/2005WR004648" target="_blank" title="It opens in new window">CrossRef
16. Fairfield J, Leymarie P (1991) Drainage networks from grid digital elevation models. Water Resources Research 27:709-17 f="http://dx.doi.org/10.1029/90WR02658" target="_blank" title="It opens in new window">CrossRef
17. Freeman GT (1991) Calculating catchment area with divergent flow based on a regular grid. Computers and Geosciences 17:413-22
18. Grabs T, Seibert J, Bishop K, Laudon H (2009) Modeling spatial patterns of saturated areas: a comparison of the topographic wetness index and a dynamic distributed model. Journal of Hydrology 373:15-3 f="http://dx.doi.org/10.1016/j.jhydrol.2009.03.031" target="_blank" title="It opens in new window">CrossRef
19. Gruber S, Peckham S (2008) Land-surface parameters and objects in hydrology. In: Hengl T, Reuter HI (eds) Geomorphometry: concepts, software, applications. Elsevier, Amsterdam, pp 171-94
20. Guntner A, Seibert J, Uhlenbrook S (2004) Modeling spatial patterns of saturated areas: an evaluation of different terrain indices. Water Resources Research 40, W05114 f="http://dx.doi.org/10.1029/2003WR002864" target="_blank" title="It opens in new window">CrossRef
21. Jenkins RB, Frazier PS (2010) High-resolution remote sensing of upland swamp boundaries and vegetation for baseline mapping and monitoring. Wetlands 30:531-40 f="http://dx.doi.org/10.1007/s13157-010-0059-1" target="_blank" title="It opens in new window">CrossRef
22. Knight JF, Tolcser BT, Corcoran JM, Rampi LP (2013) The effects of data selection and thematic detail on the accuracy of high spatial resolution wetland classifications. Photogrammetric Engineering and Remote Sensing 79:613-23 f="http://dx.doi.org/10.14358/PERS.79.7.613" target="_blank" title="It opens in new window">CrossRef
23. LaBaugh JW, Winter TC, Rosenberry DO (1998) Hydrologic functions of prairie wetlands. Great Plains Research: A Journal of Natural and Social Sciences 8:17-7
24. Land Management Information Center (LMIC) (2007) Metadata for the National Wetlands Inventory, Minnesota
25. Lang MW, McCarty GW (2009) Lidar intensity for improved detection of inundation below the forest canopy. Wetlands 29:1166-178 f="http://dx.doi.org/10.1672/08-197.1" target="_blank" title="It opens in new window">CrossRef
26. Lang MW, McCarty GW, Oesterling R, Yeo I (2013) Topographic metrics for improved mapping of forested wetlands. Wetlands 33:141-55 f="http://dx.doi.org/10.1007/s13157-012-0359-8" target="_blank" title="It opens in new window">CrossRef
27. Minnesota Department of Administration (AdminMN) Office of geographic and demographic analysis state demographic center, 2010 census: Minnesota city profiles. f="http://www.demography.state.mn.us/CityProfiles2010/index.html" class="a-plus-plus">http://www.demography.state.mn.us/CityProfiles2010/index.html. Accessed 20 May 2013
28. Moore ID, Gessler PE, Nielsen GA, Peterson GA (1993) Soil attribute prediction using terrain analysis. Soil Science Society of America Journal 57:443-52 f="http://dx.doi.org/10.2136/sssaj1993.03615995005700020026x" target="_blank" title="It opens in new window">CrossRef
29. O’Callaghan JF, Mark DM (1984) The extraction of drainage networks from digital elevation data. Computer Vision, Graphic and Image Processing 28:328-44
30. Pan F, Peters- Lidar CD, Sale MJ, King AW (2004) A comparison of geographical information system-based algorithms for computing the TOPMODEL topographic index. Water Resources Research 40:1-1
31. Prince H (2008) Wetlands of the American Midwest: a historical geography of changing attitudes. Chicago: University of Chicago Press
32. Rodhe A, Seibert J (1999) Wetland occurrence in relation to topography - a test of topographic indices as moisture indicators. Agricultural and Forest Meteorology 98-9:325-40 f="http://dx.doi.org/10.1016/S0168-1923(99)00104-5" target="_blank" title="It opens in new window">CrossRef
33. Seibert J, McGlynn B (2007) A new triangular multiple flow direction algorithm for computing upslope areas from gridded digital elevation models. Water Resources Research 43:1-
34. Shoutis L, Dunca TP, McGlyn B (2010) Terrain-based predictive modeling of Riparian vegetation in Northern Rocky Mountain watershed. Wetlands 30:621-33 f="http://dx.doi.org/10.1007/s13157-010-0047-5" target="_blank" title="It opens in new window">CrossRef
35. S?rensen R, Seibert J (2007) Effects of DEM resolution on the calculation of topographical indices: TWI and its components. Journal of Hydrology 347:79-9 f="http://dx.doi.org/10.1016/j.jhydrol.2007.09.001" target="_blank" title="It opens in new window">CrossRef
36. S?rensen R, Zinko U, Seibert J (2006) On the calculation of the topographic wetness index: evaluation of different methods based on field observations. Hydrology and Earth System Sciences 10:101-12 f="http://dx.doi.org/10.5194/hess-10-101-2006" target="_blank" title="It opens in new window">CrossRef
37. Stedman S, Dahl TE (2008) Status and trends of wetlands in the coastal watersheds of the Eastern United States 1998 o 2004. National Oceanic and Atmospheric Administration, National Marine Fisheries Service and U.S. Department of the Interior, Fish and Wildlife Service, 32 pages
38. Tarboton DG (1997) A new method for the determination of flow directions and upslope areas in grid digital elevation models. Water Resources Research 33:309-19 f="http://dx.doi.org/10.1029/96WR03137" target="_blank" title="It opens in new window">CrossRef
39. Wilson JP, Gallant JC (2000) Secondary topographic attributes. In: Wilson JP, Gallant JC (eds) Terrain analysis: principles and applications. Wiley, New York, pp 87-31
40. Wilson JP, Aggett G, Deng YX, Lam CS (2008) Water in the landscape: a review of contemporary flow routing algorithms. In: Zhou Q, Lees B, Tang G (eds) Advances in digital terrain analysis. Springer, Berlin, pp 213-36 f="http://dx.doi.org/10.1007/978-3-540-77800-4_12" target="_blank" title="It opens in new window">CrossRef
41. Winter TC, Rosenberry DO (1995) The interaction of ground water with prairie pothole wetlands in the Cottonwood Lake Area, eastcentral North Dakota, 1979-990. Wetlands 15:193-11 f="http://dx.doi.org/10.1007/BF03160700" target="_blank" title="It opens in new window">CrossRef
42. Zhou Q, Liu X (2002) Error assessment of grid-based flow routing algorithms used in hydrological models. International Journal of Geographical Information Science 16:819-42 f="http://dx.doi.org/10.1080/13658810210149425" target="_blank" title="It opens in new window">CrossRef - 作者单位：Lian P. Rampi (1) (2)
Joseph F. Knight (1)
Christian F. Lenhart (1)
1. University of Minnesota, Saint Paul, MN, USA
2. Department of Forest Resources, 1530 Cleveland Avenue North, Saint Paul, MN, 55108, USA - ISSN：1943-6246
文摘
Topography has been traditionally used as a surrogate to model spatial patterns of water distribution and variation of hydrological conditions. In this study, we investigated the use of light detection and ranging (lidar) data to derive two Single Flow Direction (SFD) and five Multiple Flow Direction (MFD) algorithms in the application of the compound topographic index (CTI) for mapping wetlands. The CTI is defined here as ln [(α)/(tan (β)], where α represents the local upslope contributing area and β represents the local slope gradient. We evaluated the following flow direction algorithms: D8, Rho8, DEMON, D-?MD-? Mass Flux, and FD8 in three ecoregions in Minnesota. Numerous studies have found that MFD algorithms better represent the spatial distribution of water compared to SFD algorithms. CTI maps were compared to field collected and image interpreted reference data using traditional remote sensing accuracy estimators. Overall accuracy results for the majority of CTI based algorithms were in the range of 81-2?%, with low errors of wetland omission. The results of this study provide evidence that 1) wetlands can be accurately identified using a lidar derived CTI, and 2) MFD algorithms should be preferred over SFD algorithms in most cases for mapping wetlands.