Abstract
The present paper offers an innovative method to monitor the change in soil erosion potential by integrating terrain and vegetation indices derived from remote sensing data. Three terrain indices namely, topographic wetness index (TWI), stream power index (SPI) and slope length factor (LS), were derived from the digital elevation model. Normalized vegetation index (NDVI) was derived for the year 1988 and 2004 using remote sensing images. K-mean clustering was performed on staked indices to categorize the study area into four soil erosion potential classes. The validation of derived erosion potential map using USLE model showed a good agreement. Results indicated that there was a significant change in the erosion potential of the watershed and a gradual shifting of lower erosion potential class to next higher erosion potential class over the study period.
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Bou Kheir R, Abdallah C, Khawlie M (2008) Assessing soil erosion in Mediterranean karst landscapes of Lebanon using remote sensing and GIS [J]. Engineering Geology, 99(3–4): 239–254
Bali Y P, Karale R L (1977) Sediment yield index as a criterion for choosing priority basins [J]. IAHS-AISH Publication, 122: 180–188
Wischmeier W H, Smith D D (1978) Predicting rainfall erosion losses[R]. USDA Agricultural Habdbook, No 537, U.S. Govt. Print Office, Washington, DC
Renard K G, Foster G R, Weesies G A, et al. (1997) Predicting soil erosion by water: a guide to conservation planning with the revised universal soil loss equation (RUSLE)[R]. USDA Agricultural Habdbook, No 703, U.S. Govt. Print Office, Washington DC
Flanagan D C, Ascough II J C, Nearing M A, et al (2001) The water erosion prediction project (WEPP) model[M]. In: Harmon R S, Doe III W W, (eds). Landscape Erosion and Evolution Modeling. New York: Kluwer Acad. Publication
Jianxi H, Feng M, Wenbo X, et al. (2008) Quantitative assessment of regional soil erosion in Chengdu plain of Sichuan Province [C]. Proceedings of 2007 IEEE International Geoscience and Remote Sensing Symposium, Barcelona
Molling C C, Strikwerda J C, Norman J M, et al. (2005) Distributed runoff formulation designed for a precision agricultural-landscape modeling system [J]. J Am Water Resource Assoc., 41: 1289–1313
Tomer M D, James D E (2004) Do soil surveys and terrain analyses identify similar priority sites for conservation? [J]. Soil Science Society of America Journal, 68(6): 1905–1915
Conrad O, Kruger J P, Bock M, et al. (2006) Soil degradation risk assessment integrating terrain analysis and soil spatial prediction methods [C]. Proceedings of International Conference Soil and Desertification — Integrated Research for the Sustainable Management of Soils in Drylands, Hamburg, Germany
Zhou W, Wu B, Lei Z, et al. (2004) Using remote sensing and GIS to estimate the probability of soil erosion rapidly [C]. Proceedings of IEEE International Geoscience and Remote Sensing Symposium, Anchorage, AK
Moore I D, Wilson J P (1992) Length-slope factors for the revised universal soil loss equation: simplified method of estimation [J]. Journal of Soil & Water Conservation, 47(5): 423–428
Wilson J P, Lorang M S (1999) Spatial models of soil erosion and GIS [M]. In: Fotheringham A S, Wegener M, (eds). Spatial Models and GIS: New Potential and New Models. London: Taylor and Francis
Wilson J P, Gallant J C (2000) Digital terrain analysis [M]. In: Wilson J P, Gallant G C, (eds). Terrain Analysis: Principles and Applications. New York: John Wiley & Sons
Rouse J W, Haas R H, Schell J A, et al. (1973) Monitoring vegetation systems in the Great Plains with ERTS [C]. Proceedings of Third ERTS Symposium, NASA, Washington DC
Schmidt F, Persson A (2003) Comparison of DEM data capture and topographic wetness indices [J]. Precision Agriculture, 4(2): 179–192
Foster G R (1990) Process based modelling of soil erosion by water on agricultural land [M]. In: Boardman J (ed). BGRG Symposia Series: Soil Erosion on Agricultural Land. Chichester: Wiley
Gitas I Z, Douros K, Minakou C, et al. (2009). Multi-temporal soil erosion risk assessment in N. Chalkidiki using a modified USLE raster model [J]. EARSeL eProceedings, 8(1): 40–52
Wischmeier W H (1959) A rainfall erosivity index for a Universal Soil Loss Equation [J]. Soil Science Society of America Proceedings, 23: 246–249
Foster G R, Mc Cool D K, Renard K G, et al. (1991) Conversion of the universal soil loss equation to SI metric units [J]. J Soil Water Conservation, 36: 356–359
McCool D K, Foster G R, Mutchler C K, et al. (1987) Revised slope steepness factor for the universal soil loss Equation [J]. Trans of ASAE, 30(5): 1387–1396
Singh G, Babu R, Narayan P, et al. (1992) Soil erosion rates in India [J]. Journal of Soil and Water Conservation, 47: 97–99
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Arabinda Sharma is an Assistant Professor in Civil Engineering Department, MM University, Mullana, India. He is holding post graduate degrees in environmental sciences as well as in remote sensing and is currently pursuing Ph.D. His research interest includes application of geoinformatics in hydrology, landscape ecology and forestry.
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Sharma, A. Integrating terrain and vegetation indices for identifying potential soil erosion risk area. Geo-spat. Inf. Sci. 13, 201–209 (2010). https://doi.org/10.1007/s11806-010-0342-6
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DOI: https://doi.org/10.1007/s11806-010-0342-6