Table 2.

Characteristics parameters of variogram models

Parameters	Best fitted model	Nugget (C0)	Sill (C0 + C)	Nugget/Sill*100	Spatial dependency	AIC	ME	RMSE	ASE	MSE	RMSSE	G
TF	Gaussian	0.0214	0.1198	17.86	Strong	−100.5	0.0020	0.178	0.165	−0.002	1.08	42.57
TR	Gaussian	4.86	19.8600	24.47	Strong	64.5	0.0393	2.747	1.906	0.019	1.33	8.37
TR1	Gaussian	1.06	5.0070	21.17	Strong	27.1	0.0068	1.407	1.082	0.010	1.28	19.15
TR2	Gaussian	4.05	13.2600	30.54	Moderate	52.5	−0.0333	2.284	1.832	−0.008	1.17	2.64
TSS	Gaussian	0.23	10.8700	2.12	Strong	78.4	−0.1877	3.897	3.712	−0.050	1.05	−12.99
TF1	Gaussian	0.000075	0.0013	5.91	Strong	−207.1	0.0004	0.026	0.026	0.012	0.98	43.64
TF2	Exponential	0.000002	0.0029	0.07	Strong	−170.9	−0.0005	0.056	0.056	−0.011	1.00	4.05
TF3	Gaussian	0.001686	0.0034	49.85	Moderate	−187.6	0.0006	0.049	0.046	0.007	1.05	−1.92
TF4	Gaussian	0.00538	0.0169	31.91	Moderate	−160.6	−0.0006	0.090	0.085	−0.009	1.04	−10.26
TDE	Gaussian	0.58	2.85	20.35	Strong	−89.3	0.0067	0.067	0.68	0.069	1.08	−17.01
Brightness	Gaussian	0.252	1.6910	14.90	Strong	−19.2	0.0258	0.570	0.606	0.037	0.95	56.57
Briskness	Gaussian	0.372	1.9050	19.53	Strong	−19.7	0.0338	0.712	0.739	0.043	0.97	30.09
Strength	Gaussian	0.265	1.8910	14.01	Strong	−28.6	0.0172	0.613	0.643	0.025	0.96	30.03
Quality	Gaussian	0.326	1.6730	19.49	Strong	−25.2	0.0245	0.650	0.702	0.032	0.93	38.51

AIC – Akaike Information Criterion; ME – Mean error; MSE – Mean square error; RMSE – Root mean square error; ASE – Average standard error;

G – Goodnees-of-prediction