Consider a series of the sampling configuration given in Figure 1 that shows estimation domains (DE) and information domains (Di). If the variogram is linear then compute kriging variances for each case, tabulate results in Table 1 and comment the table considering the resulting kriging variances. a) 50m DE=P, D=B P B b) 50m 50m DE=P, D=A+B A P P B c) 35m 30m 35m DE=CD, D=A+B A D B d) 50m 35m 15m 15m DE=CD, D=A+B B Figure 1 A series of sampling configuration for estimation and information domains Table 1. Results B u o Case a, B P b, A+B P C, A + B + CD d, A+B CD Consider a series of the sampling configuration given in Figure 1 that shows estimation domains (DE) and information domains (Di). If the variogram is linear then compute kriging variances for each case, tabulate results in Table 1 and comment the table considering the resulting kriging variances. a) 50m DE=P, D=B P B b) 50m 50m DE=P, D=A+B A P P B c) 35m 30m 35m DE=CD, D=A+B A D B d) 50m 35m 15m 15m DE=CD, D=A+B B Figure 1 A series of sampling configuration for estimation and information domains Table 1. Results B u o Case a, B P b, A+B P C, A + B + CD d, A+B CD