Mining area ecological restoration effect evaluation method in combination with multi-source data

Abstract

The invention discloses a mining area ecological restoration effect evaluation method combined with multi-source data, which comprises the following steps of: firstly, constructing a mining area ecological restoration evaluation system through multi-source remote sensing data and soil physicochemical property data, and starting from two criterion layers of stability and adaptability by adopting an analytic hierarchy process; establishing a multi-layer index structure including soil nutrients, volume weight, water content, gradient, earth surface deformation, vegetation coverage and diversity; an optical remote sensing image and a radar image are processed through an SBAS-InSAR technology to obtain earth surface deformation and vegetation information, and physical and chemical properties of soil are analyzed in combination with field sampling; and finally, quantitative evaluation of the ecological restoration effect of the mining area is realized through weight calculation and consistency check. The application result of the method in the Shengli north waste dump shows that the method can comprehensively and objectively reflect the ecological restoration condition of the mining area, and a scientific basis is provided for continuous management and optimization of ecological restoration of the mining area.

Description

Technical Field

[0001] This invention belongs to the field of ecological restoration evaluation technology, specifically involving a method for evaluating the effect of ecological restoration in mining areas by combining multi-source data. Background Technology

[0002] Mining activities in mining areas lead to ecological problems such as land occupation, soil degradation, and vegetation destruction, severely impacting the regional ecological environment and land use. To restore the ecological functions of mining areas, ecological restoration projects have been widely implemented. However, traditional evaluation methods for ecological restoration effectiveness often rely on single data sources or limited indicators, making it difficult to comprehensively reflect the stability and adaptability of the restored ecosystem. Existing methods have shortcomings in data integration, indicator systematization, and evaluation accuracy, limiting the scientific rigor and practicality of the evaluation results. Therefore, there is an urgent need to construct a method for evaluating the effectiveness of ecological restoration in mining areas that integrates multi-source data and multi-level indicators to improve the comprehensiveness and reliability of the evaluation. Summary of the Invention

[0003] To address the problems of single data sources, incomplete indicators, and strong subjectivity in existing evaluation methods for the ecological restoration effects of mining areas, this invention proposes a method for evaluating the ecological restoration effects of mining areas that integrates multi-source data. This method integrates soil physicochemical data, optical remote sensing data, and radar remote sensing data to construct an evaluation system that includes stability and adaptability criteria layers. It uses the analytic hierarchy process (AHP) to determine the weights of the indicators and combines SBAS-InSAR technology to obtain high-precision surface deformation information, thereby achieving a quantitative evaluation of the ecological restoration effects of mining areas. In practical application at the Shengli Mine's North Waste Dump Site, the comprehensive score can be used to determine the restoration effect level. Comparison with traditional methods verifies its accuracy and evaluation efficiency, providing reliable technical support for the continuous optimization of ecological restoration in mining areas.

[0004] To achieve the above objectives, the present invention adopts the following technical solution: Step 1: Constructing an evaluation system Based on the ecological restoration goals of the mining area, a hierarchical model was established, comprising a target layer, a criterion layer, and an indicator layer. The criterion layer includes stability and adaptability, while the indicator layer covers soil nutrients, bulk density, moisture content, slope, surface deformation, vegetation cover, and diversity.

[0005] Step 2: Data Acquisition and Preprocessing Soil samples were collected to determine the effective N, P, K content, bulk density, and moisture content; vegetation cover information was extracted from optical remote sensing images; surface deformation data was obtained by processing radar images with SBAS-InSAR; and slope information was extracted from DEM data.

[0006] Step 3: Weight Determination and Consistency Check This invention employs the analytic hierarchy process (AHP) to construct a judgment matrix through expert scoring, calculates the weights of each layer using the geometric mean method, and conducts a consistency check to ensure the rationality of the weight allocation. As a mature weight determination tool, this method guarantees the logical consistency of the evaluation system construction in this invention. Its process is clear, highly operable, and suitable for the multi-criteria comprehensive evaluation of the ecological restoration effects in mining areas.

[0007]

[0008]

[0009] The consistency metric is defined as CI, and its formula is as follows:

[0010] When CI = 0, there is perfect consistency; the closer CI is to 0, the more satisfactory the consistency; the larger the CI, the more severe the inconsistency. When CI alone cannot determine whether consistency is met, the random consistency index RI is introduced for comparison with CI, and the index CR is used to determine whether consistency is met. The formula is as follows:

[0011] A key indicator for judging the rationality of a matrix is ​​the CR value. A CR value < 0.1 indicates a reasonable judgment; a CR value > 0.1 suggests the matrix's importance needs adjustment, indicating the matrix is ​​not reasonable, meaning the importance of each indicator is inconsistent. The consistency of the weights is tested using the formula: CR represents the criterion layer's judgment indicator, CR1 represents the stability judgment indicator, and CR2 represents the adaptability judgment indicator. CR = 0 indicates complete consistency; CR1 = 0.0133 < 0.1 satisfies the consistency test; CR2 = 0 indicates complete consistency.

[0012] Step 4: Indicator Scoring and Comprehensive Calculation Each indicator is scored according to the preset indicator grading standard, and the score of the criterion layer and the total comprehensive evaluation score are calculated by combining the weights.

[0013]

[0014] Each indicator layer is scored according to the grading standards, multiplied by its weight, and then summed to obtain the total score for the criterion layer. The ecological restoration effect is rated as excellent, good, or poor based on the total criterion layer score. The criterion layer scores are then multiplied by their respective weights and summed to obtain the final score for the ecological restoration of the Shengli Mine North Waste Disposal Site, thus determining the restoration effect. Based on the calculated weights and the scoring standards for each indicator layer, the calculation standard for the total score of the post-ecological restoration effect evaluation system is determined, as shown in the formula:

[0015]

[0016]

[0017] Step 5: Determining the Effect Level Based on the comprehensive scoring results, the ecological restoration effect of the mining area is divided into excellent, good, and poor levels, providing a basis for decision-making in subsequent ecological restoration and management. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating the method for evaluating the ecological restoration effect of mining areas as described in this invention. Figure 2 This is a schematic diagram of the study area; Figure 3 This is an SBAS-InSAR interferometric baseline map; Figures 4-9 These are spatial distribution maps of available N, P, and K content in the soil, soil moisture content, soil bulk density, slope, cumulative surface deformation, and vegetation cover. Detailed Implementation

[0019] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0020] like Figure 1 As shown, the method of the present invention includes five main steps: evaluation system construction, multi-source data collection, weight calculation, indicator scoring and effect judgment.

[0021] Taking the Shengli Mine North Waste Dump as an example, an evaluation system was first established with ecological restoration effect as the target layer, stability and adaptability as the criterion layer, and soil nutrients, bulk density, moisture content, slope, surface deformation, vegetation cover and diversity as indicator layers. Data for each indicator were obtained through field sampling and remote sensing data. Sentinel-1A radar images were processed using SBAS-InSAR technology to obtain surface deformation information for 2017 (such as...). Figures 4-9 According to the indicator grading standards (Tables 8-13), each indicator was scored, and the stability score (3.33), adaptability score (1.34), and comprehensive score (4.24) were calculated based on the weights. The ecological restoration effect of the spoil heap was determined to be "moderate to low".

[0022] The results show that the method of the present invention can effectively integrate multi-source data, systematically evaluate the ecological restoration effect of mining areas, and provide a scientific basis for subsequent restoration projects.

Claims

1. A method for evaluating the effectiveness of ecological restoration in mining areas by combining multi-source data, characterized in that, Includes the following steps: S1: Construct an evaluation index system for the ecological restoration effect of mining areas, including a target layer, a criterion layer, and an indicator layer; the criterion layer includes stability criteria that characterize the stability of the geological environment and adaptability criteria that characterize the ecological status of vegetation; the indicator layer includes surface deformation and slope gradient for stability criteria, and soil nutrient content, soil bulk density, soil moisture content, vegetation coverage, and vegetation diversity for adaptability criteria. S2: The Analytic Hierarchy Process (AHP) is used to construct pairwise judgment matrices for each element in the criterion layer and the indicator layer, calculate the weight of each element, and perform consistency checks until they pass. S3: Synchronously collect multi-source data of the mining area at multiple time series, including: soil physicochemical property data collected and measured in the field by grid point method, acquired optical remote sensing images, and acquired radar images; S4: Use Small Baseline Set Interferometric Radar (SBAS-InSAR) technology to process the multi-time-series radar images, obtain the time series data of surface deformation in the mining area during the evaluation period, and calculate its average deformation rate as the surface deformation index value. S5: Process the optical remote sensing image to retrieve vegetation coverage and vegetation diversity index; S6: Based on spatial location, the soil physicochemical property data of each grid point, the InSAR surface deformation data corresponding to the grid point, and the vegetation parameter data retrieved by remote sensing are spatially registered and fused to form a spatial dataset containing multi-indicator information. S7: Based on the preset index layer classification standard, score each index of each evaluation unit in the spatial dataset; S8: Using a weighted summation model, the scores of each indicator are combined with their weights determined in S2, and calculated step by step upwards to obtain the stability criterion score, the adaptability criterion score, and the final comprehensive evaluation score. S9: Determine the level of ecological restoration effect of the mining area based on the total comprehensive evaluation score.

2. The method according to claim 1, characterized in that, In step S2, the analytic hierarchy process (AHP) is used to construct the judgment matrix, and a consistency check is performed. The specific formula and requirements are as follows: After determining the weights of the criteria layer and each indicator layer, a consistency check must be performed on the determined weights to determine whether the matrix is ​​reasonable. The consistency index is defined as CI, and its formula is as follows: When CI = 0, there is perfect consistency; the closer CI is to 0, the more satisfactory the consistency; the larger the CI, the more severe the inconsistency. When CI alone cannot determine whether consistency is met, the random consistency index RI is introduced for comparison with CI, and the index CR is used to determine whether consistency is met. The formula is as follows: The key indicator for judging whether a matrix is ​​reasonable is the value of CR. When the CR value is less than 0.1, it indicates that the judgment is reasonable. If the CR value is greater than 0.1, the importance of the matrix needs to be modified, indicating that the given matrix is ​​not reasonable, that is, the importance of each indicator is unreasonable.

3. The method according to claim 1, characterized in that, The radar imagery used in step S4 is Sentinel-1A de-orbiting data, and SBAS-InSAR technology is used to obtain surface deformation sequence information.

4. The method according to claim 1, characterized in that, In step S3, soil sampling points are set up using a grid method, and additional sampling points are added in the slope area. The measured indicators include soil available nitrogen, available phosphorus, available potassium content, soil bulk density, and soil moisture content.

5. The method according to claim 1, characterized in that, In step S6, the sampling point data is converted into spatially continuous layer data using Kriging interpolation.

6. The method according to claim 1, characterized in that, In step S7, the area ratio method or the grade division method is used to score the indicator layer, and the score of the criterion layer and the total comprehensive evaluation score are calculated by weighted summation.

7. The method according to claim 1, characterized in that, In step S9, the ecological restoration effect of the mining area is divided into three levels: excellent, good, and poor, based on the total score, which is used to guide the subsequent management and optimization of the ecological restoration project.

Images