%0 Conference Proceedings
%T Using Sequential Gaussian Simulation to Assess Geochemical Anomaly Areas of Lead Element
%+ Henan University
%+ Central South University [Changsha]
%+ Qinghai Institute of Geological Survey
%A Chen, Fengrui
%A Chen, Shiqiang
%A Peng, Guangxiong
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B 6th Computer and Computing Technologies in Agriculture (CCTA)
%C Zhangjiajie, China
%Y Daoliang Li
%Y Yingyi Chen
%I Springer
%3 Computer and Computing Technologies in Agriculture VI
%V AICT-393
%N Part II
%P 69-76
%8 2012-10-19
%D 2012
%R 10.1007/978-3-642-36137-1_9
%K geochemical anomaly
%K geostatistics
%K sequential Gaussian simulation
%Z Computer Science [cs]Conference papers
%X Mapping geochemical anomaly is essential for prospecting. Kriging is often used to characterize the spatial variability of geochemistry. However, due to its smooth effects, it is incapable of detecting multi-location uncertainty of geochemistry estimate. Sequential gaussian simulation (SGS) can model the spatial uncertainty through generation of several equally probable stochastic realizations. In this study, SGS is used to map Pb spatial distribution and to provide a quantitative measure of its spatial uncertainty in particular. The results show that the spatial pattern of Pb is well recognized using the SGS. The different among realizations is used to provide a quantitative measure of spatial uncertainty of Pb estimate. Knowledge of spatial uncertainty is helpful to evaluate anormal areas of Pb element.
%G English
%Z TC 5
%Z WG 5.14
%2 https://inria.hal.science/hal-01348216/document
%2 https://inria.hal.science/hal-01348216/file/978-3-642-36137-1_9_Chapter.pdf
%L hal-01348216
%U https://inria.hal.science/hal-01348216
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-TC5
%~ IFIP-WG5-14
%~ IFIP-CCTA
%~ IFIP-AICT-393