Assessing uncertainty in estimates with ordinary and indicator kriging
Assessing uncertainty in estimates with ordinary and indicator kriging
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DOI：
10.1016/s0098-3004(00)00132-1
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发表时间：
2001-10-01
影响因子：
4.4
通讯作者：
Atkinson, PM
中科院分区：
文献类型：
--
作者：
Lloyd, CD;Atkinson, PM
本文的目的是考察三种地统计学方法--普通克立格法(OK)、趋势模型克立格法(KT)和指示克立格法(IK)在估计不确定性评估中的适用性。本文使用由IK得到的条件累积分布函数(CCDF)的OK和KT标准误差以及条件标准误差来评估高程估计的不确定性。使用从遥感数字地形模型(DTM)采集的数据，使用平均OK和KT标准误差以及平均IK标准误差来确定估计的不确定性。参考完整的数字地面模型对海拔高度的估计进行了评估。根据估计的标准误差和平均克立格标准误差之间的差异来判断三种方法的成功与否。平均OK和KT标准误差比平均IK标准误差更准确地表示估计的标准误差，并且高程值的OK(或KT)估计比II(。此外，就时间和精力的开销而言，实施IK的成本可能比OK(或KT)高得多。此外，在存在低频趋势的情况下，IK的实施也被证明是有问题的。还采用了一种经修改的IK形式，即在现有观测的基础上对估计ccdf的阈值进行局部调整。这种方法显著减少了使用固定(全局)阈值的IK遇到的问题。与OK或KT相比，具有局部自适应指标阈值的IK提供了更准确的局部不确定性指南。建议在评估当地估计的不确定度时，建议使用IK，其中需要使用趋势模型来实现对特定估计的准确性的估计，以进一步改进结果。(C)2001爱思唯尔科学有限公司。保留所有权利。
The objective of this paper is to examine the applicability of three geostatistical approaches, ordinary kriging (OK); kriging with a trend model (KT), and indicator kriging (IK), to the assessment of uncertainty in estimates. This paper uses the OK and KT standard error and the conditional standard error of the conditional cumulative distribution function (ccdf) derived through IK to assess uncertainty in estimates of elevation. The mean OK and KT standard error and mean IK standard error, using data sampled from a remotely sensed digital terrain model (DTM), were used to ascertain the uncertainty in estimates. The estimates of elevation were assessed with reference to the complete DTM. Judgement on the success of the three approaches was made on the basis of the difference between the standard error of estimates and the mean kriging standard error. The mean OK and KT standard errors represent the standard error of estimation more accurately than the mean IK standard error, and OK (or KT) estimates of elevation values were more accurate than those for II(. Furthermore, IK may be significantly more costly to implement than OK (or KT) in terms of expenditure of time and effort. Also, the implementation of IK was demonstrated to be problematic in the presence of a low-frequency trend. A modified form of IK was also employed whereby the thresholds for estimation of the ccdfs were adapted locally in the basis of the available observations. This approach markedly reduced the problems encountered with IK employing fixed (global) thresholds. IK with locally adaptive indicator thresholds provided a more accurate guide to uncertainty on a local basis than OK or KT. It is suggested that IK recommended for the assessment of uncertainty in estimates locally where the estimation of accuracy of a specified will need to be implemented with a trend model to further improve results. (C) 2001 Elsevier Science Ltd. All rights reserved.