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by
R. Sokouti |
Total Records (
3 ) for
R. Sokouti |
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R. Sokouti
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M.H. Mahdian
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This research was conducted to study spatial distribution of soil nutrients including nitrogen, phosphorus and potassium and to compare the efficacy of various geo statistical approaches in the estimation of these nutrients and the preparation of spatial variability maps of these elements aimed to righteous management of fertilizers in Urmia plain, West Azerbaijan Province, Iran. To estimate the rates of soil nutrients including nitrogen, phosphorus and potassium of non-sampled areas, the Kriging, Co-kriging and Weighted Moving Average methods were used in a GIS system, instead. To compare these methods, cross-validation method with two statistical parameters Mean Absolute Error and Mean Bias Error were applied. Present studies implied that Kriging method has the least MAE of 0.450 and MBE of 0.025. This method with correlation coefficient of 0.99% and Gaussian semi variogram was of high preciseness in the estimation of nutrient rates in the points with no former information available. The estimation error in this method ranged between 0.18 and 0.75 and its deviation was between -0.002 to 0.12 meq/100 g of soil. |
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M. H. Mahdian
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S. Rahimi Bandarabady
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R. Sokouti
and
Y. Norouzi Banis
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Three geostatistical methods were evaluated for estimation of monthly and annual temperature. These methods consist of Thin Plate Smoothing Splines (TPSS) with and without co variable, Weighted Moving Average (WMA) and Kriging (ordinary and cokriging). Moreover, the elevation was used as co variable. Cross Validation technique was used for comparison of the above-mentioned methods. Based on the results obtained in this study, regression coefficients between elevation and monthly or annual temperature was greater than 0.8. Variography analysis shows good spatial correlation for monthly and annual temperature in these regions. The TPSS method with power of 2 and with elevation as co variable was recognized as the most precise method in estimating monthly and annual temperature. Mean absolute error values for annual and monthly temperature was calculated 1.02 and 1.45°C, respectively). Also, the Cokriging method is ranked as the second method in estimating temperature with MAE = 1.5°C in this study. |
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R. Sokouti
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M.H. Mahdian
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The present research was conducted to analyze spatial
changes in soil salinity distribution as an aspect of soil degradation
and to compare the efficacy of different Geostatistical methods in its
estimation and the preparation of maps of the spatial distribution of
soil salinity. To estimate soil salinity of non-sampled areas, the methods
of Kriging, Co-Kriging and Weighted Moving Average were applied in Geographical
Information System (GIS) medium. To evaluate the efficacy of the methods,
the cross-evaluation approach with two statistical parameters of mean
bias error and mean absolute error was taken in practice. Results indicated
the high precise of Kriging method with regression coefficient of 0.98
for the estimation of salinity rates in the areas, for where no data were
available before. Estimation error for this method was 1.31 and biass
was -0.34 dS m-1 which indicates high accuracy of Kriging method
to estimate topsoil salinity and its precise. |
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