Remediation target region delimiting method and system based on three-dimensional diffusion data of soil pollutants

Abstract

The invention discloses a remediation target region delimiting method and system based on three-dimensional diffusion data of soil pollutants, and relates to the technical field of soil pollutant analysis, and the method comprises the steps: extracting historical terrains, pollutant components, soil characteristics and diffusion data; constructing a three-dimensional pollutant diffusion model based on the historical terrain and the diffusion data; segmenting and intercepting topographic change features in the model to form historical pollutant diffusion segment groups, and screening matched historical segment groups by using real-time soil features and pollutant component data; and the pollutant diffusion boundary is predicted and updated by comparing the boundary cut point data with the reference segment group, and the latest boundary is used as a restoration target region. According to the method, through refined matching of historical and real-time data, the three-dimensional diffusion model and dynamic boundary updating are combined, accurate and efficient remediation target region delimitation is achieved, and the method is suitable for complex terrain soil pollution treatment.

Description

Technical Field

[0001] The present invention relates to the technical field of soil pollutant analysis, and in particular to a method and system for delineating remediation target areas based on three-dimensional diffusion data of soil pollutants. Background Art

[0002] With the acceleration of industrialization and the expansion of agricultural activities, soil pollution is becoming increasingly serious, posing a major threat to the ecological environment, food safety, and human health. The diffusion of soil pollutants (such as heavy metals and organic pollutants) in soil media exhibits significant three-dimensional spatial characteristics, influenced by a variety of factors including topographic characteristics, soil physical and chemical properties, and pollutant composition. Accurately defining soil remediation target areas is a prerequisite for implementing precision pollution control, directly related to remediation efficiency, cost control, and environmental benefits.

[0003] Traditional methods for delineating target areas for soil pollution remediation are mostly based on two-dimensional plane analysis, and the pollution range is usually estimated by spatial interpolation of pollutant concentrations at sampling points. However, this method ignores the changes in terrain height, soil layering structure, and the non-uniform diffusion characteristics of pollutants in three-dimensional space, resulting in insufficient target area delineation accuracy, and the remediation scope is prone to being too large (increasing costs) or too small (missing contaminated areas). In addition, existing methods have shortcomings in handling the integration of historical and real-time data, making it difficult to fully utilize historical diffusion data to predict real-time pollution boundaries, especially under complex terrain conditions. There is a lack of effective means to dynamically update the pollutant diffusion boundary. Summary of the Invention

[0004] The purpose of the present invention is to provide a method and system for accurately delineating remediation target areas for the spread of soil pollutants.

[0005] The present invention discloses a method for delineating remediation target areas based on three-dimensional diffusion data of soil pollutants, comprising:

[0006] Step S100: Acquire historical soil pollutant diffusion record data, and analyze each historical soil pollutant diffusion record data to determine the historical terrain feature data, historical pollutant composition data, historical soil feature data, and historical pollutant diffusion data therein;

[0007] Step S200: constructing a historical three-dimensional pollutant diffusion model based on historical terrain feature data and historical pollutant diffusion data. The historical three-dimensional pollutant diffusion model includes a three-dimensional terrain model and the diffusion path of pollutants over time, and associating historical pollutant composition data and historical soil feature data with the historical three-dimensional pollutant diffusion model.

[0008] Step S300: Segmentally extract the terrain change characteristics in the historical three-dimensional pollutant diffusion model and determine corresponding pollutant diffusion characteristic segments. The pollutant diffusion characteristic segments are combined with the terrain change characteristic segments to obtain historical pollutant diffusion segment groups, and historical soil characteristic data and historical pollutant composition data are associated with the historical pollutant diffusion segment groups.

[0009] Step S400: Real-time soil pollutant diffusion data, real-time terrain characteristic data, real-time soil characteristic data, and real-time pollutant composition data are respectively acquired, and a real-time three-dimensional pollutant diffusion model is constructed. The real-time soil characteristic data and real-time pollutant composition data are used to filter out corresponding historical pollutant diffusion segment groups;

[0010] Step S500: determine the real-time pollutant composition data and real-time terrain feature data of the boundary interception point of the real-time three-dimensional pollutant diffusion model, and find the corresponding reference pollutant segmentation group in the screened historical pollutant segmentation group, predict and fill the pollutant diffusion characteristics of the boundary interception point, and obtain a new pollutant diffusion boundary of the real-time three-dimensional pollutant diffusion model. Gradually update the pollutant diffusion boundary of the real-time three-dimensional pollutant diffusion model, and use the latest pollutant diffusion boundary as the repair target area.

[0011] In some embodiments disclosed herein, a method for constructing a three-dimensional pollutant diffusion model includes:

[0012] Step S201: Construct a three-dimensional coordinate system and a base horizontal plane. Based on the terrain feature data, determine the soil contaminant detection block corresponding to the terrain feature data, determine the block average height plane of the soil contaminant detection block, lock and associate the relative height positions between the block average height plane and the soil contamination detection block, and then overlap the block average height plane with the base horizontal plane.

[0013] Step S202: A number of vertical height mapping points are set for the base horizontal surface. A straight line is projected perpendicularly relative to each vertical height mapping point. The intersection of the straight line and the historical soil contaminant detection block is recorded as a terrain height mapping point. The line segment between the terrain height mapping point and the vertical height mapping point is intercepted and retained, and recorded as a terrain height mapping line.

[0014] In step S203, the historical pollutant composition data is adapted on each terrain height mapping line, and adjacent terrain height mapping lines marked with pollutant composition data are combined and compared to determine the direction of pollutant composition decline, and component decline vector lines are connected between the tops of the terrain height mapping lines.

[0015] In some embodiments disclosed herein, a method for determining a soil contaminant detection area includes:

[0016] Step S2011: determining a detection area of ​​interest based on the terrain feature data, and marking different position nodes on the detection area of ​​interest based on the pollutant composition data;

[0017] In step S2012, the position nodes with similar pollutant composition data are smoothly connected to form a pollutant diffusion circle, the pollutant composition data corresponding to the pollutant diffusion circle is compared with the preset value, and the block corresponding to the closest pollutant diffusion circle is identified as the soil pollutant detection block.

[0018] In some embodiments disclosed herein, a method for segmentally intercepting terrain change features in a historical three-dimensional pollutant diffusion model includes:

[0019] Step S301: construct a terrain scanning frame and move it over the soil pollutant detection block of the historical three-dimensional pollutant diffusion model. After each movement, the soil pollutant detection sub-block corresponding to the terrain scanning frame is recorded.

[0020] In step S302 , the terrain height mapping line array corresponding to the soil pollutant detection sub-block is determined as a terrain change characteristic segment, and its corresponding component drop vector line is simultaneously recorded as a pollutant diffusion characteristic segment.

[0021] In some embodiments disclosed herein, a method for screening corresponding historical pollutant diffusion segment groups using real-time soil feature data and real-time pollutant composition data includes:

[0022] Step S401: determining a plurality of soil characteristic factor parameters in the soil feature data, and setting a plurality of soil characteristic factor parameter intervals for each soil characteristic factor parameter; determining a plurality of pollutant component factor parameters in the pollutant component data, and setting a plurality of pollutant component factor parameter intervals for each pollutant component factor parameter;

[0023] In step S402, if each soil characteristic factor parameter of the real-time soil physical characteristic data and the historical soil characteristic data belongs to the same soil characteristic factor parameter interval at the same time, and each pollutant component factor parameter of the real-time pollutant composition data and the historical pollutant composition data belongs to the same soil characteristic factor parameter interval at the same time, then several historical pollutant diffusion segment groups corresponding to the historical soil physical characteristic data and the historical pollutant component data at this time are screened out.

[0024] In some embodiments disclosed herein, a method for finding a matching reference pollutant segment group from a screened historical pollutant segment group includes:

[0025] Step S501: Construct a terrain scanning frame and move it until its center point coincides with the boundary interception point of the real-time three-dimensional pollutant diffusion model. Then, determine the real-time terrain height mapping line array corresponding to the terrain scanning frame and the corresponding real-time component drop vector line in the real-time terrain height mapping line array to obtain a real-time pollutant diffusion segment group.

[0026] In step S502, the selected historical pollutant diffusion segment groups are compared with the real-time pollutant diffusion segment groups respectively, and based on the comparison and matching performance, the selected historical pollutant diffusion segment groups are determined and identified as the reference pollutant segment groups.

[0027] In some embodiments disclosed herein, a method for determining a selected historical pollutant diffusion segment group based on the comparison and matching performance includes:

[0028] Step S5021: Compare the historical terrain height mapping line array of the historical pollutant diffusion segment group with the real-time terrain height mapping line array of the real-time pollutant diffusion segment group to determine the mapping line height difference of each corresponding terrain height mapping line. If the mapping line height difference is less than or equal to a preset value, mark the corresponding terrain height mapping line as being consistent.

[0029] Step S5022, performing statistical analysis and coherence analysis on the terrain height mapping lines without matching marks, and determining matching sub-parameters based on the analysis results;

[0030] Step S5023, and compare the real-time component descent vector line and the historical component descent vector line, analyze the coincidence relationship between all real-time component descent vector lines and the corresponding historical component descent vector lines, and calculate the coincidence vector line ratio of the real-time component descent vector lines to all real-time component descent vector lines;

[0031] Step S5024: If the matching sub-parameter and the matching vector line ratio are both greater than or equal to the preset value, it is determined that the historical pollutant diffusion segment group and the real-time pollutant diffusion segment group are consistent.

[0032] In some embodiments disclosed herein, the expression for determining the anastomosis parameter is:

[0033]

[0034] Among them, W is the anastomosis parameter, W max is the preset maximum matching sub-parameter, X1 is the number of terrain height mapping lines without matching marks, and X zongis the number of all terrain height mapping lines, δ(i) is the block size parameter of the i-th coherent non-matching terrain block, a coherent non-matching terrain block is a block corresponding to several adjacent terrain height mapping lines without matching marks, the block size parameter is the number of terrain height mapping lines, K is the matching sub-parameter adjustment conversion coefficient, n is the total number of coherent non-matching terrain blocks, L is the coherent non-matching impact adjustment coefficient, and b is the coherent non-matching impact adjustment constant.

[0035] In some embodiments disclosed herein, a remediation target area delineation system based on three-dimensional diffusion data of soil contaminants is also disclosed, which is characterized by comprising:

[0036] The first module is used to obtain historical soil pollutant diffusion record data and analyze each historical soil pollutant diffusion record data to determine the historical terrain feature data, historical pollutant composition data, historical soil feature data and historical pollutant diffusion data;

[0037] The second module is used to construct a historical three-dimensional pollutant diffusion model based on historical terrain feature data and historical pollutant diffusion data. The historical three-dimensional pollutant diffusion model includes a three-dimensional terrain model and the diffusion path of pollutants over time, and associates historical pollutant composition data and historical soil feature data with the historical three-dimensional pollutant diffusion model;

[0038] The third module is used to segment the terrain change characteristics in the historical three-dimensional pollutant diffusion model and determine the corresponding pollutant diffusion characteristic segments. The pollutant diffusion characteristic segments are combined with the terrain change characteristic segments to obtain historical pollutant diffusion segment groups, and the historical soil characteristic data and historical pollutant composition data are associated with them.

[0039] The fourth module is used to separately acquire real-time soil pollutant diffusion data, real-time terrain feature data, real-time soil feature data, and real-time pollutant composition data, and to construct a real-time three-dimensional pollutant diffusion model. The real-time soil feature data and real-time pollutant composition data are used to screen out the corresponding historical pollutant diffusion segment groups.

[0040] The fifth module is used to determine the real-time pollutant composition data and real-time terrain feature data of the boundary interception points of the real-time three-dimensional pollutant diffusion model, and to find the corresponding reference pollutant segmentation group in the screened historical pollutant segmentation group, and to predict and fill the pollutant diffusion characteristics of the boundary interception points to obtain a new pollutant diffusion boundary of the real-time three-dimensional pollutant diffusion model, and gradually update the pollutant diffusion boundary of the real-time three-dimensional pollutant diffusion model, and use the latest pollutant diffusion boundary as the repair target area.

[0041] The present invention discloses a method and system for delineating remediation target areas based on three-dimensional diffusion data of soil pollutants, which relates to the technical field of soil pollutant analysis, including: extracting historical topography, pollutant composition, soil characteristics, and diffusion data; constructing a three-dimensional pollutant diffusion model based on historical topography and diffusion data; segmenting the terrain change characteristics in the model to form historical pollutant diffusion segment groups, and using real-time soil characteristics and pollutant composition data to screen and match historical segment groups; comparing boundary interception point data with reference segment groups, predicting and updating pollutant diffusion boundaries, and using the latest boundaries as remediation target areas. The present invention achieves accurate and efficient remediation target area delineation through refined matching of historical and real-time data, combined with a three-dimensional diffusion model and dynamic boundary updates, and is suitable for soil pollution control in complex terrains.

[0042] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 A diagram showing the steps of the remediation target area delineation method based on three-dimensional diffusion data of soil pollutants. DETAILED DESCRIPTION

[0044] The technical solution of the present invention is further described below with reference to the accompanying drawings and embodiments.

[0045] The following will be combined with the accompanying drawings and specific embodiments to clearly and completely describe the technical solutions of the present invention. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention and cannot be understood as limiting the scope of protection of the present invention. Those skilled in the art in this field can make some non-essential improvements and adjustments based on the content of the present invention described below. In the present invention, unless otherwise clearly specified and limited, the technical terms used in the present invention should have the common meanings understood by those skilled in the art of the present invention.

[0046] Example:

[0047] The present invention discloses a method for delineating remediation target areas based on three-dimensional diffusion data of soil pollutants. Figure 1 ,include:

[0048] Step S100: Acquire historical soil pollutant diffusion record data, and analyze each historical soil pollutant diffusion record data to determine the historical terrain feature data, historical pollutant composition data, historical soil feature data, and historical pollutant diffusion data.

[0049] This step aims to provide basic data support for the subsequent construction of a three-dimensional diffusion model by collecting and analyzing historical soil pollutant diffusion record data. Historical data usually come from long-term environmental monitoring, soil sampling and pollutant analysis records, including terrain characteristics (such as terrain height and slope), pollutant composition (such as heavy metal and organic pollutant concentrations), soil characteristics (such as soil type, porosity, pH value) and pollutant diffusion data (such as concentration distribution and diffusion range changes over time). Through data cleaning, classification and feature extraction, each record is analyzed to clarify the above four types of key characteristic data. For example, by analyzing the historical data of an industrial pollution area, the concentration distribution of lead pollutants, the sandy characteristics of the soil, the terrain undulations of the area, and the diffusion paths of pollutants in the past 10 years can be extracted. These data provide multi-dimensional input for the construction of a historical diffusion model, ensuring that the model can reflect the actual diffusion behavior of pollutants in a specific terrain and soil environment.

[0050] In step S200, a historical three-dimensional pollutant diffusion model is constructed based on historical terrain feature data and historical pollutant diffusion data. The historical three-dimensional pollutant diffusion model includes a three-dimensional terrain model and the diffusion path of pollutants over time, and historical pollutant composition data and historical soil feature data are associated with the historical three-dimensional pollutant diffusion model.

[0051] Based on the historical terrain feature data and pollutant diffusion data extracted in step S100, this step constructs a historical three-dimensional pollutant diffusion model using three-dimensional modeling technology, which includes a three-dimensional terrain model and the diffusion path of pollutants that changes over time. The three-dimensional terrain model is generated using terrain height data and a coordinate system to reflect the spatial morphology of the soil surface; the diffusion path is simulated by the change of pollutant concentration over time and space, reflecting the migration pattern of pollutants.

[0052] Step S300, segmenting and intercepting the terrain change characteristics in the historical three-dimensional pollutant diffusion model, and determining the corresponding pollutant diffusion characteristic segments, combining the pollutant diffusion characteristic segments with the terrain change characteristic segments to obtain a historical pollutant diffusion segment group, and associating it with historical soil characteristic data and historical pollutant composition data.

[0053] This step extracts local patterns related to pollutant diffusion characteristics by segmenting the terrain change features in the historical three-dimensional pollutant diffusion model, and forms historical pollutant diffusion segment groups. Terrain change characteristics (such as height gradient and slope) are gradually moved within the model by a scanning frame, and the corresponding soil pollutant detection sub-block and its terrain characteristics are recorded for each movement. For example, in an undulating terrain, the scanning frame may capture the downward trend of pollutants in a steep slope area. Pollutant diffusion feature segments are determined based on pollutant concentration changes or diffusion paths (such as concentration drop vectors) and combined with corresponding terrain change feature segments to form historical pollutant diffusion segment groups. Each segment group is associated with corresponding historical soil characteristic data (such as soil moisture) and pollutant composition data (such as cadmium concentration) to reflect the diffusion patterns under specific terrain and environmental conditions. For example, pollutant diffusion in flat areas may appear uniformly circular, while in steep slope areas it may appear as narrow strips. This segmentation process decomposes complex diffusion models into manageable local features, facilitating subsequent matching with real-time data.

[0054] In step S400, real-time soil pollutant diffusion data, real-time terrain feature data, real-time soil feature data, and real-time pollutant composition data are acquired respectively, and a real-time three-dimensional pollutant diffusion model is constructed. The corresponding historical pollutant diffusion segment groups are screened out using the real-time soil feature data and real-time pollutant composition data.

[0055] This step constructs a real-time three-dimensional pollutant diffusion model to simulate the current pollution status by acquiring real-time soil pollutant diffusion data (such as current pollutant concentration distribution), terrain feature data (such as the latest terrain measurement), soil feature data (such as real-time soil pH value) and pollutant composition data (such as current pollutant types). The construction principle of the real-time model is similar to that of the historical model, but emphasizes the timeliness of the data. For example, in a newly discovered polluted area, a real-time model can be generated based on terrain data measured by drones and on-site sampling data. Using real-time soil feature data (such as soil type) and pollutant composition data (such as lead concentration), the most similar segment groups are screened out from the historical pollutant diffusion segment groups through characteristic factor parameter interval matching. For example, if the real-time soil is sandy and the pollutant is lead, the segment groups of lead diffusion in sandy soil in history are screened out. This screening is based on the similarity of soil characteristics and pollutant composition, ensuring that the historical segment groups can provide a reliable reference for real-time diffusion prediction, thereby improving the accuracy of target area delineation.

[0056] Step S500: determine the real-time pollutant composition data and real-time terrain feature data of the boundary interception point of the real-time three-dimensional pollutant diffusion model, and find the corresponding reference pollutant segmentation group in the screened historical pollutant segmentation group, predict and fill the pollutant diffusion characteristics of the boundary interception point, and obtain a new pollutant diffusion boundary of the real-time three-dimensional pollutant diffusion model. Gradually update the pollutant diffusion boundary of the real-time three-dimensional pollutant diffusion model, and use the latest pollutant diffusion boundary as the repair target area.

[0057] This step analyzes pollutant composition data (such as pollutant concentration at the boundary intercept points) and terrain characteristic data (such as elevation at the boundary intercept points) at the boundary intercept points of the real-time 3D pollutant diffusion model. It then searches for matching reference pollutant segment groups within the selected historical pollutant diffusion segment groups, predicts and fills in the diffusion characteristics of the boundary intercept points, and ultimately updates the pollutant diffusion boundary. Boundary intercept points are edge points in the real-time model where pollutant concentration approaches a threshold and represent the diffusion front. For example, at the boundary point of a contaminated area, a lead concentration of 50 mg / kg is detected, and the terrain is gently sloping. By comparing the terrain height mapping lines and component descent vectors with those of the historical segment group, similar historical diffusion patterns (such as the lead diffusion trend on gentle slopes) are identified, and the future diffusion direction and range of the boundary point are predicted. The predicted results are used to fill in the boundary of the real-time model, generating a new diffusion boundary. Through iterative updates, the boundary accuracy is gradually optimized. Ultimately, the updated pollutant diffusion boundary is used as the remediation target area. For example, if the prediction indicates that pollution will spread along a low-lying area, the target area may prioritize coverage of that area. This dynamic update mechanism ensures that the target area can adapt to real-time changes in pollutant diffusion, improving the targetedness and efficiency of remediation.

[0058] In some embodiments disclosed herein, a method for constructing a three-dimensional pollutant diffusion model includes:

[0059] Step S201: construct a three-dimensional coordinate system, construct a basic horizontal plane, determine the soil pollutant detection block corresponding to the terrain feature data based on the terrain feature data, and determine the block average height plane of the soil pollutant detection block, and lock and associate the relative height position between the block average height plane and the soil pollution detection block, and then overlap the block average height plane with the basic horizontal plane.

[0060] In step S202, a number of block height vertical mapping points are set for the basic horizontal plane, and a straight line is vertically emitted relative to each block height vertical mapping point. The intersection of the straight line and the historical soil pollutant detection block is recorded as a terrain height mapping point, and the line segment between the terrain height mapping point and the height vertical mapping point is intercepted and retained, and recorded as a terrain height mapping line.

[0061] In step S203, the historical pollutant composition data is adapted on each terrain height mapping line, and adjacent terrain height mapping lines marked with pollutant composition data are combined and compared to determine the direction of pollutant composition decline, and component decline vector lines are connected between the tops of the terrain height mapping lines.

[0062] In some embodiments disclosed herein, a method for determining a soil contaminant detection area includes:

[0063] Step S2011: Based on the terrain feature data, determine the detection focus block, and mark different position nodes on the detection focus block based on the pollutant composition data.

[0064] In step S2012, the position nodes with similar pollutant composition data are smoothly connected to form a pollutant diffusion circle, the pollutant composition data corresponding to the pollutant diffusion circle is compared with the preset value, and the block corresponding to the closest pollutant diffusion circle is identified as the soil pollutant detection block.

[0065] In some embodiments disclosed herein, a method for segmentally intercepting terrain change features in a historical three-dimensional pollutant diffusion model includes:

[0066] In step S301, a terrain scanning frame is constructed and moved in the soil pollutant detection block of the historical three-dimensional pollutant diffusion model. After each movement, the soil pollutant detection sub-block corresponding to the terrain scanning frame is recorded.

[0067] In step S302 , the terrain height mapping line array corresponding to the soil pollutant detection sub-block is determined as a terrain change characteristic segment, and its corresponding component drop vector line is simultaneously recorded as a pollutant diffusion characteristic segment.

[0068] In some embodiments disclosed herein, a method for screening corresponding historical pollutant diffusion segment groups using real-time soil feature data and real-time pollutant composition data includes:

[0069] Step S401: determine several soil characteristic factor parameters in the soil feature data, and set several soil characteristic factor parameter intervals for each soil characteristic factor parameter; determine several pollutant component factor parameters in the pollutant component data, and set several pollutant component factor parameter intervals for each pollutant component factor parameter.

[0070] In step S402, if each soil characteristic factor parameter of the real-time soil physical characteristic data and the historical soil characteristic data belongs to the same soil characteristic factor parameter interval at the same time, and each pollutant component factor parameter of the real-time pollutant composition data and the historical pollutant composition data belongs to the same soil characteristic factor parameter interval at the same time, then several historical pollutant diffusion segment groups corresponding to the historical soil physical characteristic data and the historical pollutant component data at this time are screened out.

[0071] In some embodiments disclosed herein, a method for finding a matching reference pollutant segment group from a screened historical pollutant segment group includes:

[0072] In step S501, a terrain scanning frame is constructed and moved until its center point coincides with the boundary interception point of the real-time three-dimensional pollutant diffusion model. The real-time terrain height mapping line array corresponding to the terrain scanning frame is determined, and the corresponding real-time component descent vector line in the real-time terrain height mapping line array is determined to obtain a real-time pollutant diffusion segment group.

[0073] In step S502, the selected historical pollutant diffusion segment groups are compared with the real-time pollutant diffusion segment groups respectively, and based on the comparison and matching performance, the selected historical pollutant diffusion segment groups are determined and identified as the reference pollutant segment groups.

[0074] In some embodiments disclosed herein, a method for determining a selected historical pollutant diffusion segment group based on the comparison and matching performance includes:

[0075] Step S5021, compare the historical terrain height mapping line array of the historical pollutant diffusion segment group and the real-time terrain height mapping line array of the real-time pollutant diffusion segment group to determine the mapping line height difference of each corresponding terrain height mapping line. If the mapping line height difference is less than or equal to the preset value, the corresponding terrain height mapping line is marked as matching.

[0076] This step evaluates the similarity of the terrain features between the historical pollutant diffusion segment group and the real-time pollutant diffusion segment group by comparing the terrain height mapping line arrays, providing a basis for subsequent screening. The terrain height mapping line array is a collection of terrain height mapping lines, each of which represents the terrain height characteristics of the soil pollutant detection block at a specific location. During the comparison process, the height difference between the corresponding mapping lines in the historical and real-time arrays is calculated (for example, the historical height of a point is 10 meters, the real-time height is 10.2 meters, and the difference is 0.2 meters). If the difference is less than or equal to a preset value (such as 0.5 meters), the pair of mapping lines is considered similar in terrain features and marked as matching. For example, in a polluted area, historical data may show that the height mapping lines of flat terrain are similar in height, while the real-time data has slightly changed due to slight settlement. By setting a reasonable threshold (such as 0.5 meters), matching mapping lines with smaller height changes can be screened out. This marking mechanism ensures that only historical segment groups with highly similar terrain heights are retained, and segment groups with excessively large terrain differences are filtered out, providing an accurate basis for subsequent analysis.

[0077] Step S5022: Perform statistical analysis and continuity analysis on the terrain height mapping lines without matching marks, and determine matching sub-parameters based on the analysis results.

[0078] This step performs statistical and consistency analysis on the terrain height mapping lines that are not marked as matching, quantifies the characteristic differences of the non-matching parts, and calculates the matching sub-parameters to evaluate the overall similarity. The statistical analysis calculates the number and proportion of non-matching mapping lines. For example, if there are 10 non-matching mapping lines out of a total of 100 mapping lines, the non-matching ratio is 10%. The consistency analysis focuses on whether the non-matching mapping lines are concentrated in continuous areas (forming "coherent non-matching terrain blocks"), because continuous non-matching may indicate local terrain changes (such as landslides), which have a greater impact on diffusion. For example, in a polluted area, 5 consecutive non-matching mapping lines may correspond to a newly formed low-lying area. The matching sub-parameter is calculated by combining factors such as the number of non-matching lines and the size of the coherent blocks through a formula (such as the expression in the technical solution) to reflect the overall degree of topographic matching between the historical and real-time segmentation groups. The higher the matching sub-parameter, the smaller the impact of the non-matching part and the more likely the segmentation group is to match.

[0079] Step S5023, and compare the real-time component descent vector line and the historical component descent vector line, analyze the matching relationship between all real-time component descent vector lines and the corresponding historical component descent vector lines, and calculate the matching vector line ratio of the matching real-time component descent vector lines to all real-time component descent vector lines.

[0080] This step evaluates the similarity of pollutant diffusion trends by comparing the component drop vector lines of the real-time and historical pollutant diffusion segment groups, further verifying the matching degree of the segment groups. The component drop vector line indicates the direction and magnitude of the decline in pollutant concentration between the terrain height mapping lines. For example, the vector direction from a high concentration point to a low concentration point reflects the trend of pollutants descending along the slope. During the comparison, the direction and magnitude differences between the real-time vector line and the historical vector line are analyzed (for example, the real-time vector angle is 30° and the historical vector angle is 32°, which is a small difference). The matching vector lines must meet the direction and magnitude differences within the preset range. The proportion of matching real-time component drop vector lines to the total vector lines is calculated. For example, if 80 out of 100 real-time vector lines match the historical vector lines, the matching ratio is 80%. For example, in a heavy metal pollution area, historical data may show that lead concentrations are decreasing in a northwest direction. If the real-time data also shows a similar trend, the matching ratio is high, indicating that the diffusion pattern of the historical segment group is consistent with the real-time situation. This ratio quantifies the similarity of pollutant diffusion behavior and provides a key basis for the final matching.

[0081] Step S5024: If the matching sub-parameter and the matching vector line ratio are both greater than or equal to the preset value, it is determined that the historical pollutant diffusion segment group and the real-time pollutant diffusion segment group are consistent.

[0082] In some embodiments disclosed herein, the expression for determining the anastomosis parameter is:

[0083]

[0084] Among them, W is the anastomosis parameter, W max is the preset maximum matching sub-parameter, X1 is the number of terrain height mapping lines without matching marks, and X zong is the number of all terrain height mapping lines, δ(i) is the block size parameter of the i-th coherent non-matching terrain block, a coherent non-matching terrain block is a block corresponding to several adjacent terrain height mapping lines without matching marks, the block size parameter is the number of terrain height mapping lines, K is the matching sub-parameter adjustment conversion coefficient, n is the total number of coherent non-matching terrain blocks, L is the coherent non-matching impact adjustment coefficient, and b is the coherent non-matching impact adjustment constant.

[0085] In some embodiments disclosed herein, a remediation target area delineation system based on three-dimensional diffusion data of soil contaminants is also disclosed, which is characterized by comprising:

[0086] The first module is used to obtain historical soil pollutant diffusion record data and analyze each historical soil pollutant diffusion record data to determine the historical terrain feature data, historical pollutant composition data, historical soil feature data and historical pollutant diffusion data;

[0087] The second module is used to construct a historical three-dimensional pollutant diffusion model based on historical terrain feature data and historical pollutant diffusion data. The historical three-dimensional pollutant diffusion model includes a three-dimensional terrain model and the diffusion path of pollutants over time, and associates historical pollutant composition data and historical soil feature data with the historical three-dimensional pollutant diffusion model;

[0088] The third module is used to segment the terrain change characteristics in the historical three-dimensional pollutant diffusion model and determine the corresponding pollutant diffusion characteristic segments. The pollutant diffusion characteristic segments are combined with the terrain change characteristic segments to obtain historical pollutant diffusion segment groups, and the historical soil characteristic data and historical pollutant composition data are associated with them.

[0089] The fourth module is used to separately acquire real-time soil pollutant diffusion data, real-time terrain feature data, real-time soil feature data, and real-time pollutant composition data, and to construct a real-time three-dimensional pollutant diffusion model. The real-time soil feature data and real-time pollutant composition data are used to screen out the corresponding historical pollutant diffusion segment groups.

[0090] The fifth module is used to determine the real-time pollutant composition data and real-time terrain feature data of the boundary interception points of the real-time three-dimensional pollutant diffusion model, and to find the corresponding reference pollutant segmentation group in the screened historical pollutant segmentation group, and to predict and fill the pollutant diffusion characteristics of the boundary interception points to obtain a new pollutant diffusion boundary of the real-time three-dimensional pollutant diffusion model, and gradually update the pollutant diffusion boundary of the real-time three-dimensional pollutant diffusion model, and use the latest pollutant diffusion boundary as the repair target area.

[0091] The present invention discloses a method and system for delineating remediation target areas based on three-dimensional diffusion data of soil pollutants, which relates to the technical field of soil pollutant analysis, including: extracting historical topography, pollutant composition, soil characteristics, and diffusion data; constructing a three-dimensional pollutant diffusion model based on historical topography and diffusion data; segmenting the terrain change characteristics in the model to form historical pollutant diffusion segment groups, and using real-time soil characteristics and pollutant composition data to screen and match historical segment groups; comparing boundary interception point data with reference segment groups, predicting and updating pollutant diffusion boundaries, and using the latest boundaries as remediation target areas. The present invention achieves accurate and efficient remediation target area delineation through refined matching of historical and real-time data, combined with a three-dimensional diffusion model and dynamic boundary updates, and is suitable for soil pollution control in complex terrains.

[0092] Through the description of the above embodiments, those skilled in the art can clearly understand that the present invention can be implemented through hardware or by using software plus the necessary general hardware platform. Based on this understanding, the technical solution of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, a USB flash drive, a mobile hard disk, etc.) and includes a number of instructions for enabling a computer device (such as a personal computer, a server, or a network device) to execute the methods described in various implementation scenarios of the present invention.

[0093] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit the same. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solutions of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for delineating remediation target areas based on three-dimensional diffusion data of soil pollutants, characterized in that: include: Step S100: Acquire historical soil pollutant diffusion record data, and analyze each historical soil pollutant diffusion record data to determine the historical terrain feature data, historical pollutant composition data, historical soil feature data, and historical pollutant diffusion data therein; Step S200: constructing a historical three-dimensional pollutant diffusion model based on historical terrain feature data and historical pollutant diffusion data. The historical three-dimensional pollutant diffusion model includes a three-dimensional terrain model and the diffusion path of pollutants over time, and associating historical pollutant composition data and historical soil feature data with the historical three-dimensional pollutant diffusion model. Step S300: Segmentally extract the terrain change characteristics in the historical three-dimensional pollutant diffusion model and determine corresponding pollutant diffusion characteristic segments. The pollutant diffusion characteristic segments are combined with the terrain change characteristic segments to obtain historical pollutant diffusion segment groups, and historical soil characteristic data and historical pollutant composition data are associated with the historical pollutant diffusion segment groups. Step S400: Real-time soil pollutant diffusion data, real-time terrain characteristic data, real-time soil characteristic data, and real-time pollutant composition data are respectively acquired, and a real-time three-dimensional pollutant diffusion model is constructed. The real-time soil characteristic data and real-time pollutant composition data are used to filter out corresponding historical pollutant diffusion segment groups; Step S500: determine the real-time pollutant composition data and real-time terrain feature data of the boundary interception point of the real-time three-dimensional pollutant diffusion model, and find the corresponding reference pollutant segmentation group in the screened historical pollutant segmentation group, predict and fill the pollutant diffusion characteristics of the boundary interception point, and obtain a new pollutant diffusion boundary of the real-time three-dimensional pollutant diffusion model. Gradually update the pollutant diffusion boundary of the real-time three-dimensional pollutant diffusion model, and use the latest pollutant diffusion boundary as the repair target area.

2. The method for delineating remediation target areas based on three-dimensional soil pollution diffusion data according to claim 1, characterized in that: Methods for constructing a three-dimensional pollutant dispersion model include: Step S201: Construct a three-dimensional coordinate system and a base horizontal plane. Based on the terrain feature data, determine the soil contaminant detection block corresponding to the terrain feature data, determine the block average height plane of the soil contaminant detection block, lock and associate the relative height positions between the block average height plane and the soil contamination detection block, and then overlap the block average height plane with the base horizontal plane. Step S202: A number of vertical height mapping points are set for the base horizontal surface. A straight line is projected perpendicularly relative to each vertical height mapping point. The intersection of the straight line and the historical soil contaminant detection block is recorded as a terrain height mapping point. The line segment between the terrain height mapping point and the vertical height mapping point is intercepted and retained, and recorded as a terrain height mapping line. In step S203, the historical pollutant composition data is adapted on each terrain height mapping line, and adjacent terrain height mapping lines marked with pollutant composition data are combined and compared to determine the direction of pollutant composition decline, and component decline vector lines are connected between the tops of the terrain height mapping lines.

3. The method for delineating remediation target areas based on three-dimensional soil pollution diffusion data according to claim 2, characterized in that: Methods for determining soil contaminant detection areas include: Step S2011: determining a detection area of ​​interest based on the terrain feature data, and marking different position nodes on the detection area of ​​interest based on the pollutant composition data; In step S2012, the position nodes with similar pollutant composition data are smoothly connected to form a pollutant diffusion circle, the pollutant composition data corresponding to the pollutant diffusion circle is compared with the preset value, and the block corresponding to the closest pollutant diffusion circle is identified as the soil pollutant detection block.

4. The method for delineating remediation target areas based on three-dimensional soil pollution diffusion data according to claim 2, characterized in that: Methods for segmenting the terrain change characteristics in the historical three-dimensional pollutant dispersion model include: Step S301: construct a terrain scanning frame and move it over the soil pollutant detection block of the historical three-dimensional pollutant diffusion model. After each movement, the soil pollutant detection sub-block corresponding to the terrain scanning frame is recorded. In step S302 , the terrain height mapping line array corresponding to the soil pollutant detection sub-block is determined as a terrain change characteristic segment, and its corresponding component drop vector line is simultaneously recorded as a pollutant diffusion characteristic segment.

5. The method for delineating remediation target areas based on three-dimensional diffusion data of soil pollutants according to claim 2, characterized in that: Methods for screening out corresponding historical pollutant diffusion segment groups using real-time soil feature data and real-time pollutant composition data include: Step S401: determining a plurality of soil characteristic factor parameters in the soil feature data, and setting a plurality of soil characteristic factor parameter intervals for each soil characteristic factor parameter; determining a plurality of pollutant component factor parameters in the pollutant component data, and setting a plurality of pollutant component factor parameter intervals for each pollutant component factor parameter; In step S402, if each soil characteristic factor parameter of the real-time soil physical characteristic data and the historical soil characteristic data belongs to the same soil characteristic factor parameter interval at the same time, and each pollutant component factor parameter of the real-time pollutant composition data and the historical pollutant composition data belongs to the same soil characteristic factor parameter interval at the same time, then several historical pollutant diffusion segment groups corresponding to the historical soil physical characteristic data and the historical pollutant component data at this time are screened out.

6. The method for delineating remediation target areas based on three-dimensional diffusion data of soil pollutants according to claim 2, characterized in that: Methods for finding matching reference pollutant segment groups from the screened historical pollutant segment groups include: Step S501: Construct a terrain scanning frame and move it until its center point coincides with the boundary interception point of the real-time three-dimensional pollutant diffusion model. Then, determine the real-time terrain height mapping line array corresponding to the terrain scanning frame and the corresponding real-time component drop vector line in the real-time terrain height mapping line array to obtain a real-time pollutant diffusion segment group. In step S502, the selected historical pollutant diffusion segment groups are compared with the real-time pollutant diffusion segment groups respectively, and based on the comparison and matching performance, the selected historical pollutant diffusion segment groups are determined and identified as the reference pollutant segment groups.

7. The method for delineating remediation target areas based on three-dimensional diffusion data of soil pollutants according to claim 6, characterized in that: Methods for determining selected historical pollutant dispersion segment groups based on the comparison and matching performance include: Step S5021: Compare the historical terrain height mapping line array of the historical pollutant diffusion segment group with the real-time terrain height mapping line array of the real-time pollutant diffusion segment group to determine the mapping line height difference of each corresponding terrain height mapping line. If the mapping line height difference is less than or equal to a preset value, mark the corresponding terrain height mapping line as being consistent. Step S5022, performing statistical analysis and coherence analysis on the terrain height mapping lines without matching marks, and determining matching sub-parameters based on the analysis results; Step S5023, and compare the real-time component descent vector line and the historical component descent vector line, analyze the coincidence relationship between all real-time component descent vector lines and the corresponding historical component descent vector lines, and calculate the coincidence vector line ratio of the real-time component descent vector lines to all real-time component descent vector lines; Step S5024: If the matching sub-parameter and the matching vector line ratio are both greater than or equal to the preset value, it is determined that the historical pollutant diffusion segment group and the real-time pollutant diffusion segment group are consistent.

8. The method for delineating remediation target areas based on three-dimensional diffusion data of soil pollutants according to claim 6, characterized in that: The expression for determining the anastomosis parameter is: Among them, W is the anastomosis parameter, W max is the preset maximum matching sub-parameter, X1 is the number of terrain height mapping lines without matching marks, and X zong is the number of all terrain height mapping lines, δ(i) is the block size parameter of the i-th coherent non-matching terrain block, a coherent non-matching terrain block is a block corresponding to several adjacent terrain height mapping lines without matching marks, the block size parameter is the number of terrain height mapping lines, K is the matching sub-parameter adjustment conversion coefficient, n is the total number of coherent non-matching terrain blocks, L is the coherent non-matching impact adjustment coefficient, and b is the coherent non-matching impact adjustment constant.

9. The remediation target area delineation system based on three-dimensional diffusion data of soil pollutants is characterized by: include: The first module is used to obtain historical soil pollutant diffusion record data and analyze each historical soil pollutant diffusion record data to determine the historical terrain feature data, historical pollutant composition data, historical soil feature data and historical pollutant diffusion data; The second module is used to construct a historical three-dimensional pollutant diffusion model based on historical terrain feature data and historical pollutant diffusion data. The historical three-dimensional pollutant diffusion model includes a three-dimensional terrain model and the diffusion path of pollutants over time, and associates historical pollutant composition data and historical soil feature data with the historical three-dimensional pollutant diffusion model; The third module is used to segment the terrain change characteristics in the historical three-dimensional pollutant diffusion model and determine the corresponding pollutant diffusion characteristic segments. The pollutant diffusion characteristic segments are combined with the terrain change characteristic segments to obtain historical pollutant diffusion segment groups, and the historical soil characteristic data and historical pollutant composition data are associated with them. The fourth module is used to separately acquire real-time soil pollutant diffusion data, real-time terrain feature data, real-time soil feature data, and real-time pollutant composition data, and to construct a real-time three-dimensional pollutant diffusion model. The real-time soil feature data and real-time pollutant composition data are used to screen out the corresponding historical pollutant diffusion segment groups. The fifth module is used to determine the real-time pollutant composition data and real-time terrain feature data of the boundary interception points of the real-time three-dimensional pollutant diffusion model, and to find the corresponding reference pollutant segmentation group in the screened historical pollutant segmentation group, and to predict and fill the pollutant diffusion characteristics of the boundary interception points to obtain a new pollutant diffusion boundary of the real-time three-dimensional pollutant diffusion model, and gradually update the pollutant diffusion boundary of the real-time three-dimensional pollutant diffusion model, and use the latest pollutant diffusion boundary as the repair target area.

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