### 1. Introduction

^{7}ha. In addition, heavy metal levels near factories and mining areas seriously exceed the standard, thus causing regional pollution [4]. For example, studies have shown that the near soil lead-zinc mines was highly polluted [5, 6]. Soil concentrations of many heavy metals such as Pb, Zn and Cd were tens or even hundreds of times higher than the environmental background, posing a serious threat to the growth of local vegetables and the quality of agricultural products [7].

### 2. Materials and Methods

### 2.1. Study Area

^{2}was selected based on factors such as soil texture, vegetation types and land-use patterns.

### 2.2. Sample Collection and Analysis

^{2}, was roughly rectangular with a length of 110 meters and a width of 60 meters. A total of 84 points were sampled with a 5 cm diameter soil auger. Three replicates were collected for each point, the soil was mixed and placed in sealed plastic bags and brought back to the laboratory for air-drying.

^{−1}ammonium acetate solution. Heavy metals were measured by inductively coupled plasma mass spectrometry (ICP-MS); precision and recovery were tested by spiking reference samples (GSS-1) [17]. By comparison, the recovery of samples was between 86.7–92.6 and satisfied analytical standards.

### 2.3. Analysis Method

#### 2.3.1. Data statistics

#### 2.3.2. Semi-variance function

^{2}of Z(x) and spatial covariance C(h) as: (h) = S

^{2}-C(h), where (h) represents the Z(x) in the spatial relevant, which is equal to mathematical expectation of square of difference value of measured value of interval samples. In general, the semi-variance function increases with the separation distance of samples, finally becoming constant at some distance. The commonly used variation functions include spherical, base station, exponential, and Gaussian models. In this study, according to the multiple fittings of the data, the exponential and spherical models were selected:

##### (1)

$$\text{y}(\text{h})=\{\begin{array}{c}{C}_{0}+{C}_{1}\hspace{0.17em}\left[1.5{\scriptstyle \frac{h}{{A}_{0}}}-0.5\hspace{0.17em}{\left({\scriptstyle \frac{h}{{A}_{0}}}\right)}^{3}\right],\mathrm{\hspace{0.17em}\u200a\u200a}\mathrm{\hspace{0.17em}\u200a\u200a}\mathrm{\hspace{0.17em}\u200a\u200a}0\ll h\ll {A}_{0}\\ {C}_{0}+{C}_{1},\mathrm{\hspace{0.17em}\u200a\u200a}\mathrm{\hspace{0.17em}\u200a\u200a}\mathrm{\hspace{0.17em}\u200a\u200a}h>{A}_{0}\end{array}$$##### (2)

$$\text{y}(\text{h})={C}_{0}+{C}_{1}\hspace{0.17em}\left(1-{e}^{{\scriptstyle \frac{-h}{{A}_{0}}}}\right){A}_{0}\ne 0$$*C*

_{0}is the nugget value representing the amount of random variation;

*C*

_{1}is the sill, representing structural variance of variable space variation; and

*A*

_{0}is the range, (m). The nugget coefficient is the ratio of the nugget to the sill, which is the value of the function as semi-variance tends to 0, representing random variation caused by measurement errors or variations in soil properties.

#### 2.3.3. The rate of heavy metals exceeding

#### 2.3.4. The method of Cluster analysis

#### 2.3.5. Single factor pollution index

*P*

_{i}is the pollution index;

*C*

_{i}(mg/kg) is the measured concentration of heavy metal in the soil; and

*S*

_{i}is the evaluation standard for that heavy metal. In this experiment, the secondary level standard of soil environmental quality (Table S1) [21] was used as the evaluation standard. If

*P*

_{i}≤ 1, the sample is not contaminated; samples with

*P*

_{i}> 1 are contaminated, and the greater the value, the more serious the pollution.

#### 2.3.6. The Nemerow integrated pollution index

*P*is the comprehensive pollution index of the monitoring points;

*P*

_{imax}is the largest single pollution index;

*P*

_{iavg}is the average single pollution index. Soil quality is classified according to

*P*value. The Nemerow comprehensive pollution index was used to determine the pollution level [24]; details are listed in Table S2.

#### 2.3.7. Coefficient of Variation (CV)

*w*here

*SD*is the standard deviation, and

*MN*is the mean concentration of soil heavy metal.

### 3. Results and Discussion

### 3.1. Descriptive Statistical Analysis

### 3.2. Characteristics of Soil Properties and Semi-Variance Function

_{0}) is the corresponding value of the function at the origin, reflecting the random variation within the system; the Sill (C

_{0}+ C) represents the total variation within the system; the Range (A

_{0}) is the maximum spatial correlation distance, which reflects the physical extent of spatial autocorrelation of the variables. The ratio of Nugget to Sill (C

_{0}/C

_{0}+ C) is called the Nugget effect, which reflects the spatial dependence of soil properties and indicates the degree of spatial correlation of system variables. When the ratio is less than 25%, the spatial correlation between variables is strong. Between 25% and 75% indicates moderate spatial correlation. When the ratio is more than 75%, the spatial correlation between variables is weak [31, 32].