The efficiency of geostatistical methods in zoning the probability of presence of Persian Oak regeneration

To study on competence of nonparametric geostatistical models including Indicator Kriging, Probability Kriging, Indicator Cokriging and Probability CoKriging, in zoning the probability of presence of Persian oak (Quercus brantii Lindl) regeneration in a forest stand to suggest the most suitable model and produce its related map, a forest stand with an area about 200 ha in nearby Yasouj was inventoried. Using a systematic random grid, 150 m by 250 m, general and silvicultural characteristics of the forest stand were inventoried in circular sample plots with an area of 1000 m2. the number of Persian oak regeneration were counted
To study on competence of nonparametric geostatistical models including Indicator Kriging, Probability Kriging, Indicator Cokriging and Probability CoKriging, in zoning the probability of presence of Persian oak (Quercus brantii Lindl) regeneration in a forest stand to suggest the most suitable model and produce its related map, a forest stand with an area about 200 ha in nearby Yasouj was inventoried. Using a systematic random grid, 150 m by 250 m, general and silvicultural characteristics of the forest stand were inventoried in circular sample plots with an area of 1000 m2. the number of Persian oak regeneration were counted in four small-circular plots with a radius of 1.55 m located with a distance of nine meters from the center of the main plots in line with the four main geographic directions. Using Geostatistic Analysis in ArcGIS10.2, the models of circular, spherical, tetraspherical, pentaspherical, exponential, gaussian, rational quadratic, hole effect, k-bessel, J-Bessel and stable were fited on the variogram. The cross validation method was used to evaluate the accuracy of the model. The results showed that the pantaspherical model of probability kriging have the strongest spatial structure (75.63%) and the highest level of credit in aspect of accuracy, ME (-0.0106), ASE (0.4424), RMSE (0.4470) and RMSS (1.0113) and would be suggested as the suitable model. After drawing semivariogram of regenerations and fixing the suggested model on that, they indicated on anisotropy in semivariogram quantity.
four small-circular plots with a radius of 1.55 m located with a distance of nine meters from the center of the main plots in line with the four main geographic directions. Using Geostatistic Analysis in ArcGIS10.2, the models of circular, spherical, tetraspherical, pentaspherical, exponential, gaussian, rational quadratic, hole effect, k-bessel, J-Bessel and stable were fited on the variogram. The cross validation method was used to evaluate the accuracy of the model. The results showed that the pantaspherical model of probability kriging have the strongest spatial structure (75.63%) and the highest level of credit in aspect of accuracy, ME (-0.0106), ASE (0.4424), RMSE (0.4470) and RMSS (1.0113) and would be suggested as the suitable model. After drawing semivariogram of regenerations and fixing the suggested model on that, they indicated on anisotropy in semivariogram quantity. The map of spatial distribution of regeneration could be an applicable guide in plantation projects in Zagros Region.