## 3 Data Processing Methods
### Calculation Methods of Geochemical Background Values and Geochemical Baseline Values
In this case, the true value of the value obtained by \(M_{0}\) and 2 times the mean square error \(\sigma\) is the lower limit of the anomaly. Then, draw a horizontal line defined by 0.6 times the maximum frequency, intersecting both sides of the frequency density curve, and the length between the intersection point and the median value is the mean square error \(\sigma\). In this case, the true value of the value obtained by \(M_{0}\) and 2 times the mean square error \(S\) is the lower limit of the anomaly (as shown in Figure 2a). The mass value can be obtained mathematically:  
\[M_{0}=x_{0}+\frac{i(p_{2}-p_{1})}{2p_{2}-p_{1}-p_{3}} \tag{1}\]  
Figure 2: Schematic Diagram of Method Principles. (**a**). Schematic Diagram of Frequency Histogram Distribution; (**b**). Schematic plot of Double Logarithmic Coordinate Curve of Content-Area Method. In Formula (1), \(M_{0}\) is the crowd value, \(x_{0}\) is the lower limit value of the group where the crowd value resides, i is the group distance, \(p_{1}\) is the frequency of the group before the group where the crowd value resides, \(p_{2}\) is the frequency of the group where the crowd value resides, and \(p_{3}\) is the frequency of the group after the group where the crowd value resides. The mass value \(M_{O}\) is used as background \(C_{02}\). Calculation Method 3 for Geochemical Background Values: Concentration-Area Method (C-A method) was first proposed by [PERSON] et al. (1994). Later scholars also call it content-area method [34; 35; 36; 37; 38]. This method is based on the concentration value (that is, the frequency of the magnitude value) to separate outliers from the background; it distinguishes the background field from the abnormal field. These values can also be spatial or geometric features of geochemical indicators. The expression of the C-A model is as follows:  
\[A(\rho>v)\propto\rho^{-\beta} \tag{2}\]  
In Formula (2), \(A(\rho)\) represents the region where the concentration is greater than or equal to the contour value; \(v\) is the threshold; \(\beta\) is the fractal dimension greater than zero. \(A(\rho>v)\) is the area value of the element content \(\rho\) greater than \(A\) certain value \(v\), and with the increase of the value \(v\), \(A(\rho>v)\) will decrease accordingly. The change of \(A\) with \(v\) will depend on the magnitude of the exponent \(\beta\). The fractal dimension \(\beta\) can quantitatively describe the distribution of geochemical element content and the complexity of the variation of element content distribution in this scale-free region. This variation corresponds to different \(\beta\) values in the range of background values and outliers, respectively, which will determine different slopes of the line segments in the schematic plot of double Logarithmic Coordinate Curve. In the C-A method, by the schematic plot of double Logarithmic Coordinate Curve, the area \(A(\geq s)\) with a concentration value greater than \(s\) is established between the concentration value \(s\). The power law relationship can be drawn to map the anomaly and the background region. GeODAS 4.0 has been used to create a double logarithmic coordinate curve for the content-area method (Figure 2b). The data do not necessarily need to follow a normal distribution. The second segment of the fitted line reflects the non-singular background information of element contents [39]. By calculating the arithmetic mean of the numbers that fall within the second segment of the fitted line, the background value \(C_{03}\) is determined. The final geochemical background value \(C_{0}\) is obtained by averaging the values calculated from the three methods. With the Calculation Method for geochemical baseline values [6; 38; 40; 41], the process begins with testing the desert sample data for normality using Python. If the whole dataset conforms to a normal distribution, the arithmetic mean plus or minus two standard deviations is used to denote the baseline value and its range.