Assessing uncertainty in estimates with ordinary and indicator kriging

摘要: The objective of this paper is to examine the applicability three geostatistical approaches, ordinary kriging (OK), with a trend model (KT), and indicator (IK), assessment uncertainty in estimates. This uses OK KT standard error conditional cumulative distribution function (ccdf) derived through IK assess estimates elevation. mean error, using data sampled from remotely sensed digital terrain (DTM), were used ascertain elevation assessed reference complete DTM. Judgement on success approaches was made basis difference between error. errors represent estimation more accurately than (or KT) values accurate those for IK. Furthermore, may be significantly costly implement terms expenditure time effort. Also, implementation demonstrated problematic presence low-frequency trend. A modified form also employed whereby thresholds ccdfs adapted locally available observations. approach markedly reduced problems encountered employing fixed (global) thresholds. adaptive provided guide local or KT. It suggested that recommended where accuracy specified will need implemented further improve results.