Sampling design optimization for spatial functions |
| |
| Authors: | Ricardo A Olea |
| |
| Institution: | (1) Kansas Geological Survey, 1930 Avenue A, 66044 Lawrence, Kansas, USA;(2) Present address: Empresa Nacional del Petróleo, Casilla 3556 Santiago, Chile |
| |
| Abstract: | A new procedure is presented for minimizing the sampling requirements necessary to estimate a mappable spatial function at a specified level of accuracy. The technique is based on universal kriging, an estimation method within the theory of regionalized variables. Neither actual implementation of the sampling nor universal kriging estimations are necessary to make an optimal design. The average standard errorand maximum standard error of estimationover the sampling domain are used as global indices of sampling efficiency. The procedure optimally selects those parameters controlling the magnitude of the indices, including the density and spatial pattern of the sample elements and the number of nearest sample elements used in the estimation. As an illustration, the network of observation wells used to monitor the water table in the Equus Beds of Kansas is analyzed and an improved sampling pattern suggested. This example demonstrates the practical utility of the procedure, which can be applied equally well to other spatial sampling problems, as the procedure is not limited by the nature of the spatial function. |
| |
| Keywords: | spatial function sampling sample element universal kriging standard error contour mapping |
| 本文献已被 SpringerLink 等数据库收录！ |
|
