**1. Introduction**

Geochemical data are typically reported as compositions, in the form of such proportions as weight percents, parts per million, etc., subject to a constant sum (e.g., 100%, 1,000,000 ppm). As an important source of geo-information, geochemical data recording multiple element concentration have been successfully processed by advanced multivariate analytical methods (e.g., factor analysis, cluster analysis, etc.) to identify geological bodies and delineate mineralization-favored space [1–6]. The results of these geochemical data were mainly expressed by vector format, including the colorful geochemical map.

The raster image application in geology was further improved with the development of remote sensing technology. With respect to the application of remote sensing in geology, several books on the geological structural interpretation were published [7, 8]. As the multispectral and hyperspectral imaging rapidly grows, most of the researches paid much attention to the extraction of altered mineral information which were often related to different types of ore deposits [9–16]. These ore deposits include Carlin-type deposit, Archean massive sulfide deposit, skarn-type deposit, and volcanic massive sulfide deposit. Some studies also focused on lithology mapping with hyperspectral tools [17–22].

Only little geochemical data was rasterized. It is partly because the rastering process is more complex, and also the formed raster image could not produce good visual effect due to the low sample density. It is worth mentioning that the geochemical data with vector format can provide relatively simple results; thus the rasterized image appears superfluous. A small amount of research focused on geochemical data rasterization. A technique of metal content on maps was developed [23]. Utilizing ALKEMIA software, Gustavsson et al. [24] designed an interpolation and smoothing method to generate maps including dot maps, color maps, and shaded relief maps.

In this study, geochemical data of the northern Daxinganling metallogenic belt were taken as the experiment area.

A geochemical survey with the scale of 1:200,000 was conducted in a large area of the Daxinganling region [6]. In follow-up to that research, the objectives of the present study are to evaluate the rasterization method of geochemical data obtained from the northern Daxinganling region, use rasterized geochemical data to assist in geological mapping and prospecting target selection, and propose an application of rasterized geochemical data.
