OPTIMAL RESOLUTION INVESTIGATION OF DIGITAL ELEVATION MODELS BY GOESTATISTCAL TECHNIQUE TO COMPUTE TOPOGRAPHIC FACTOR (LS) FOR RUSLE EQUATION IN TALESHOLIA DISTRICT, GOLESTAN PROVINCE

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AYOUBI SH.A.; KHORMALI F.; SHATAEI JOUYBARI SH.

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Journal: Year:2008 | Volume:20 | Issue:4 (77 IN NATURAL RESOURCES) Page(s): 122-129

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Title

OPTIMAL RESOLUTION INVESTIGATION OF DIGITAL ELEVATION MODELS BY GOESTATISTCAL TECHNIQUE TO COMPUTE TOPOGRAPHIC FACTOR (LS) FOR RUSLE EQUATION IN TALESHOLIA DISTRICT, GOLESTAN PROVINCE

Author(s)

AYOUBI SH.A. | KHORMALI F. | SHATAEI JOUYBARI SH. | Issue Writer Certificate

Keywords

SOIL EROSIONQ3

DIGITAL ELEVATION MODELQ3

TOPOGRAPHY FACTORQ3

GEOSTATISTICSQ2

Abstract

Continuous men’s needs to soil resources and increase of the common knowledge of soil degradation and erosion have aggravated need for confident evaluation and assessment of soil degradation rate and potential for food production. Revised Universal Soil Loss Equation is a model to predict longtime annual soil loss, related to rainfall-runoff, soil erodibility, slope length, steepness and support practice. The product of slope length L and steepness S is called topographic factor LS, implying the topographic effect on soil loss. The topographic factor is the most sensitive one in the prediction of soil loss. This study was conducted to predict spatial variability of LS factor using DIGITAL ELEVATION MODEL, in hill slopes of Talesholia district in Golestan Province, approximately covered 650 ha. Digital elevation data were prepared with 20m spacing. By using nearest neighbor resampling, new DEMs with 50, 100, 200 and 400 m resolution were derived from the original DEM. The LS factor was calculated according to a physically based topological factor LS equation for each DEM. Appropriate semi variogram models were fitted to semi variances and the best parameters were derived. Finally, the best DEM was chosen based on geostatistical parameters, total variances and mean semi variances at a lag of one cell. The results showed that with increasing the cell spacing (resolution), sill and nugget effect decreased and range increased from 92 to 171m. Spatial dependency increased with increasing cell spacing up to 50 m, but decreased extremely in the longer cell spacing. Total variances and mean semi variances also increased with increasing cell spacing to 50m. According to best spatial dependency and high variances and diversity of 50 m cell spacing, this DEM was proposed to predict LS factor by physical based model. Overall results of this study confirmed that geostatistical analysis accompanying with the statistical approaches could be applied to select suitable cell spacing in DEM to predict topographical factor in RUSLE model.

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APA: Copy

AYOUBI, SH.A., KHORMALI, F., & SHATAEI JOUYBARI, SH.. (2008). OPTIMAL RESOLUTION INVESTIGATION OF DIGITAL ELEVATION MODELS BY GOESTATISTCAL TECHNIQUE TO COMPUTE TOPOGRAPHIC FACTOR (LS) FOR RUSLE EQUATION IN TALESHOLIA DISTRICT, GOLESTAN PROVINCE. PAJOUHESH-VA-SAZANDEGI, 20(4 (77 IN NATURAL RESOURCES)), 122-129. SID. https://sid.ir/paper/19876/en

Vancouver: Copy

AYOUBI SH.A., KHORMALI F., SHATAEI JOUYBARI SH.. OPTIMAL RESOLUTION INVESTIGATION OF DIGITAL ELEVATION MODELS BY GOESTATISTCAL TECHNIQUE TO COMPUTE TOPOGRAPHIC FACTOR (LS) FOR RUSLE EQUATION IN TALESHOLIA DISTRICT, GOLESTAN PROVINCE. PAJOUHESH-VA-SAZANDEGI[Internet]. 2008;20(4 (77 IN NATURAL RESOURCES)):122-129. Available from: https://sid.ir/paper/19876/en

IEEE: Copy

SH.A. AYOUBI, F. KHORMALI, and SH. SHATAEI JOUYBARI, “OPTIMAL RESOLUTION INVESTIGATION OF DIGITAL ELEVATION MODELS BY GOESTATISTCAL TECHNIQUE TO COMPUTE TOPOGRAPHIC FACTOR (LS) FOR RUSLE EQUATION IN TALESHOLIA DISTRICT, GOLESTAN PROVINCE,” PAJOUHESH-VA-SAZANDEGI, vol. 20, no. 4 (77 IN NATURAL RESOURCES), pp. 122–129, 2008, [Online]. Available: https://sid.ir/paper/19876/en

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