Research on Remote Sensing Geochemical Modeling Based on Surface to Surface Model
发布时间：2023-11-08
点击次数：
DOI码：10.1088/1742-6596/2597/1/012013
发表刊物：Journal of Physics: Conference Series
关键字：Remote sensing geochemistry; Geochemical data; Modeling; Kriging interpolation; Quantitative inversion
摘要：Remote sensing geochemistry is a simple, fast and economical advanced prospecting method, which carries out inversion and prediction of surface element content using the empirical model by regression or machine learning. The key problem faced by quantitative remote sensing is the low inversion accuracy of the model due to the mismatch of “point surface" information. How to overcome this problem? This paper proposes a “surface to surface " modeling method, which converts point data into surface data through Kriging interpolation to solve this problem. This paper uses geochemical interpolation data of Cu elements at different scales in the Qishitan gold mine area, Xinjiang, and ASTER remote sensing data to conduct geochemical modeling. In order to test the effect of Kriging on decreasing the scale effect, five sets of experiments were designed for comparison. The first four sets of sample data were interpolated according to different cell sizes, and the last set of data was not interpolated. The results show that the Kriging interpolation based on the ground resolution of the remote sensing image can effectively improve the accuracy of the remote sensing quantitative inversion model. When the square interpolation is close to the ground resolution of the used remote sensing data, the modeling accuracy gets the best value. This paper provides a new idea for improving the accuracy of remote sensing geochemical modeling.
第一作者：Gong Cheng
论文类型：论文集
通讯作者：Yufang Li
论文编号：012013
学科门类：工学
一级学科：地质资源与地质工程
文献类型：C
卷号：2597
期号：1
页面范围：1-12
ISSN号：1742-6596
是否译文：否
发表时间：2023-08-30
收录刊物：EI
附件：
Research on Remote Sensing Geochemical Modeling Based on Surface to Surface Model.pdf