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2010 | 19 | 5 |

Tytuł artykułu

Using the geographical information system and remote sensing techniques for soil erosion assessment

Autorzy

Warianty tytułu

Języki publikacji

EN

Abstrakty

EN
The objective of this study is to establish a geographical information system method for spatial assessment of soil erosion based on the universal soil loss equation (USLE), and to evaluate the utility of GIS with regard to soil erosion mapping. The study area, Goynuk, covers 1,437 square kilometers and is located in the southeastern part of Bolu, Turkey. In this study, USLE factors including rainfall erosivity (R-factor), soil erodibility (K-factor), slope and slope length (LS-factor), vegetative cover (C-factor), and conservation practice (Pfactor) were studied and reviewed. Each factor, which consists of a set of logically related geographic features and attributes, was used as an input for analysis. A land use map of the study area was generated from (Landsat TM 2000) satellite imagery. A digital elevation model (DEM) interpolated from elevation contours was used to generate the slope and LS-factor. Spatial vegetative cover, extracted from Landsat TM imagery, was used to determine the spatial C-factor and P-factor, values of which are based on experimental results from the literature. USLE model calculation applied to the resultant polygonal layer gave values of soil loss in tons/ha/year. These are then ranked into three classes as low, moderate, and high. The study indicated that highly eroded areas are bare lands and steep conditions, whereas less eroded areas are low slope classes. As a conclusion the study confirms that the use of GIS and remotely sensed data can greatly enhance spatial modeling for soil erosion.

Wydawca

-

Rocznik

Tom

19

Numer

5

Opis fizyczny

p.881-886,fig.,ref.

Twórcy

autor
  • Landscape Architecture Ankara, Ankara, Turkey

Bibliografia

  • 1. MCLEOD C., QUESNEL S. Quantifying soil erosion and sedimentation under conventional and conservation scenarios in the Swan Creek Subwatershed of the Grand River Watershed. GEOG 4480 Applied GIS Home Page, 2003.
  • 2. GARG V., SETH R. Remote sensing & GIS in identifying areas vulnerable to soil erosion WAPCOS: 9, Community Centre, Saket, New Delhi, 2002.
  • 3. KOKH-SHRESTHA M. Soil erosion modeling using remote sensing and GIS: A case study of Jhikhu Khola Watershed, Nepal, 2002.
  • 4. ANONYMOUS. About RUSLE. http://www.Iwr.Msu.Edu/Rusle/, 2003.
  • 5. WISCHMEIER W. H., SMITH D. D. Predicting rainfall erosion losses from cropland east of the Rocky Mountains: Guide for selection of practices for soil and water conservation, US Department Agricultural Handbook: 282, 1965.
  • 6. WISCHMEIER W. H., SMITH D. D. Predicting rainfall erosion losses: Guide to conservation planning, US Department Agricultural Handbook: 537, 1978.
  • 7. RENARD K., FOSTER G. R., WEESIES G. A., PORTER J. P. RUSLE. Revised universal soil loss equation. J. Soil and Water Cons., 46, 30, 1991.
  • 8. ANONYMOUS. http://web.pdx.edu/~emch/rs/EX12rs.html. Imagine Exercise 12: Supervised Classification in Erdas, Portland State University, 2000.
  • 9. DOGAN O. Rainfall Index Map of Turkey. General Directorate of Rural Affairs of Turkey, 1999.
  • 10. MOORE I. D., BURCH G. J. Modeling erosion and deposition: Topographic effects transactions ASAE: 29, 1624, 1986.
  • 11. MITASOVA H., MITAS L. Modeling soil detachment with RUSLE 3D using GIS. University of Illinois at Urbana- Champaign, 1999.
  • 12. WIJESEKERA S., SAMARAKOON L. Extraction of parameters and modeling soil erosion using GIS in a grid environment: 22nd Conference on Remote Sensing, Singapore, 2001.
  • 13. LUFAFA A. Prediction of soil erosion in a Lake Victoria Basin Catchment using a GIS based USLE. Agricultural Systems: 76, 883, 2003.

Typ dokumentu

Bibliografia

Identyfikatory

Identyfikator YADDA

bwmeta1.element.agro-89f4a69a-b0f4-48e9-8d06-70568a4602cb
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