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Wetlands

, Volume 34, Issue 3, pp 513–525 | Cite as

Comparison of Flow Direction Algorithms in the Application of the CTI for Mapping Wetlands in Minnesota

  • Lian P. Rampi
  • Joseph F. Knight
  • Christian F. Lenhart
Article

Abstract

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 81–92 %, 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.

Keywords

Wetland mapping Lidar Flow direction algorithm Compound topographic index 

Notes

Acknowledgments

This research was funded by the Minnesota Environment and Natural Resources Trust (ENRTF), the Minnesota Department of Natural Resources (MNDNR), and the United States Fish and Wildlife Services (USFWS: Award 30181AJ194).

References

  1. Anteau MJ, Afton AD (2009) Wetland use and feeding by lesser scaup during spring migration across the upper Midwest, USA. Wetlands 29:704–712CrossRefGoogle Scholar
  2. Antonarakis AS, Richards KS, Brasington J (2008) Object-based land cover classification using airborne Lidar. Remote Sensing of Environment 112:2988–2998CrossRefGoogle Scholar
  3. Beven KJ, Kirkby MJ (1979) A physically based, variable contributing area model of basin hydrology. Hydrological Sciences Journal 24:43–69CrossRefGoogle Scholar
  4. Bridgham SD, Pastor J, Dewey B, Weltzin JF, Updegraff K (2008) Rapid carbon response of peatlands to climate change. Ecology 89:3041–3048CrossRefGoogle Scholar
  5. Burrough PA, McDonell RA (1998) Principles of geographical information systems. Oxford University Press, New York, 190 ppGoogle Scholar
  6. Chaplot V, Walter C (2003) Subsurface topography to enhance the prediction of the spatial distribution of soil wetness. Hydrological Processes 17:2567–2580CrossRefGoogle Scholar
  7. Charman DJ (2009) Peat and peatlands. Elsevier Inc, 541–548Google Scholar
  8. City of Chanhassen Surface Water Management Plan (2006) In: The second generation surface water management plan - Chanhassen, Minnesota: 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 RatonGoogle Scholar
  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):564–582CrossRefGoogle Scholar
  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 30:1681–1692CrossRefGoogle Scholar
  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.Google Scholar
  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 112Google Scholar
  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 28Google Scholar
  15. Erskine RH, Green TR, Ramirez JA, MacDonald LH (2006) Comparison of grid-based algorithms for computing upslope contributing area. Water Resources Research 42, W09416CrossRefGoogle Scholar
  16. Fairfield J, Leymarie P (1991) Drainage networks from grid digital elevation models. Water Resources Research 27:709–717CrossRefGoogle Scholar
  17. Freeman GT (1991) Calculating catchment area with divergent flow based on a regular grid. Computers and Geosciences 17:413–422Google Scholar
  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 373:15–23CrossRefGoogle Scholar
  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 171–194Google Scholar
  20. Guntner A, Seibert J, Uhlenbrook S (2004) Modeling spatial patterns of saturated areas: an evaluation of different terrain indices. Water Resources Research 40, W05114CrossRefGoogle Scholar
  21. Jenkins RB, Frazier PS (2010) High-resolution remote sensing of upland swamp boundaries and vegetation for baseline mapping and monitoring. Wetlands 30:531–540CrossRefGoogle Scholar
  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 79:613–623CrossRefGoogle Scholar
  23. LaBaugh JW, Winter TC, Rosenberry DO (1998) Hydrologic functions of prairie wetlands. Great Plains Research: A Journal of Natural and Social Sciences 8:17–37Google Scholar
  24. Land Management Information Center (LMIC) (2007) Metadata for the National Wetlands Inventory, MinnesotaGoogle Scholar
  25. Lang MW, McCarty GW (2009) Lidar intensity for improved detection of inundation below the forest canopy. Wetlands 29:1166–1178CrossRefGoogle Scholar
  26. Lang MW, McCarty GW, Oesterling R, Yeo I (2013) Topographic metrics for improved mapping of forested wetlands. Wetlands 33:141–155CrossRefGoogle Scholar
  27. Minnesota Department of Administration (AdminMN) Office of geographic and demographic analysis state demographic center, 2010 census: Minnesota city profiles. 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 57:443–452CrossRefGoogle Scholar
  29. O’Callaghan JF, Mark DM (1984) The extraction of drainage networks from digital elevation data. Computer Vision, Graphic and Image Processing 28:328–344Google Scholar
  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 40:1–11Google Scholar
  31. Prince H (2008) Wetlands of the American Midwest: a historical geography of changing attitudes. Chicago: University of Chicago PressGoogle Scholar
  32. Rodhe A, Seibert J (1999) Wetland occurrence in relation to topography - a test of topographic indices as moisture indicators. Agricultural and Forest Meteorology 98–99:325–340CrossRefGoogle Scholar
  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 43:1–8Google Scholar
  34. Shoutis L, Dunca TP, McGlyn B (2010) Terrain-based predictive modeling of Riparian vegetation in Northern Rocky Mountain watershed. Wetlands 30:621–633CrossRefGoogle Scholar
  35. Sørensen R, Seibert J (2007) Effects of DEM resolution on the calculation of topographical indices: TWI and its components. Journal of Hydrology 347:79–89CrossRefGoogle Scholar
  36. Sørensen 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 10:101–112CrossRefGoogle Scholar
  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 pagesGoogle Scholar
  38. Tarboton DG (1997) A new method for the determination of flow directions and upslope areas in grid digital elevation models. Water Resources Research 33:309–319CrossRefGoogle Scholar
  39. Wilson JP, Gallant JC (2000) Secondary topographic attributes. In: Wilson JP, Gallant JC (eds) Terrain analysis: principles and applications. Wiley, New York, pp 87–131Google Scholar
  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 213–236CrossRefGoogle Scholar
  41. Winter TC, Rosenberry DO (1995) The interaction of ground water with prairie pothole wetlands in the Cottonwood Lake Area, eastcentral North Dakota, 1979–1990. Wetlands 15:193–211CrossRefGoogle Scholar
  42. Zhou Q, Liu X (2002) Error assessment of grid-based flow routing algorithms used in hydrological models. International Journal of Geographical Information Science 16:819–842CrossRefGoogle Scholar

Copyright information

© Society of Wetland Scientists 2014

Authors and Affiliations

  • Lian P. Rampi
    • 1
    • 2
  • Joseph F. Knight
    • 1
  • Christian F. Lenhart
    • 1
  1. 1.University of MinnesotaSaint PaulUSA
  2. 2.Department of Forest ResourcesSaint PaulUSA

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