**Author details**

*Applied Geochemistry with Case Studies on Geological Formations, Exploration Techniques…*

The shortcoming of rasterized geochemical images mainly lies in that the raster format occupy a relative larger data storage space, and if the sampling sites is sparse,

The increased geochemical density makes this kind of method to get more indepth application. No doubt geochemical survey with larger scale can provide more information. China recently carries out geological survey on main metallogenic belts, and their sampling density was bigger. The sampling density in the northern

1:50,000; therefore the sampling density has been greatly increased. Followed by reducing the analysis data of geochemical elements, the usual analyzed elements now are Au, Ag, Cu, Pb, Zn, As, Sb, Hg, W, Sn, Bi, Mo, and so on; the purpose is for mineral exploration. With the increase of sampling data in unit area, the spatial resolutions of geochemical image will increase. The following job is to merge 39 geochemical elements of 1:200,000 with geochemical elements in 1:50,000 to create

Integration with other types of geoscience data is also imperative. The geological map can finally transform to a rasterized image. The strata, magmatism, and so forth may be assigned values through various kinds of logical operations in rasterized image. Regional geophysical survey, for instance, aeromagnetic, airborne gravity, geomagnetic, gravity, and regional electrical method, may form the corresponding rasterized image. These data combined with the geochemical data will undoubtedly increase the information content of geosciences; therefore, it will develop a broader approach for intensive geological study and the comprehensive

Regional geochemical data of 1:200,000 in the northern Daxinganling area were rasterized using a method that triangulates a planar set of points. Consequently, a multilayered image database containing 39 elements/oxides was formed. The images were enhanced using an image enhancement technique and algebraic operations. The images were handled as multidimensional vector data. Accordingly, hyperspectral tools could be used for the processing. The geochemical signatures of deposits were extracted from the images. Enriched and depleted elements were distinguished by comparing them with regional geochemical statistics. The geochemical signatures represented the geochemical characteristics of ore deposits. The rock types were classified using the K-Means method, which assisted in the regional geological mapping, especially in the areas of dense forest. The geochemical signature of a typical ore deposit was processed by SAM, which determined the similarity between the deposit and pixels in the region. The prospecting target area was determined according to the angle. With increased geochemical data sampling density, as well as further integration with other geophysical, geological, and remote sensing data, rasterized geochemical images can be fully

This research was supported by funds from the Chinese Ministry of Science and Technology (grant no. 2016YFC0600103) and the "Comprehensive integration and service of mineral geology and its metallogenic regularity in China" project of the China Geological Survey (grant no. DD20160346). In the process of drafting this

in the scale of

and the spatial resolution is set largely, a clear lattice shape will be displayed.

Daxinganling metallogenic belt was averagely 4–8 sites per km<sup>2</sup>

the multielement geochemical atlas with a relative higher resolution.

application of geosciences data.

**6. Conclusions**

used in the future.

**Acknowledgements**

**66**

Jiang Chen\*, Zhaoxia Mao, Yan Zhao, Chunpeng Zhang and Shan Jiang Shenyang Geological Center, CGS, Shenyang, Liaoning, China

\*Address all correspondence to: chen07761@itc.nl

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