A soil remediation monitoring method and system

Abstract

The present invention discloses a soil remediation monitoring method and system. The method includes: inputting historical soil images and real-time soil images into a pre-built image recognition model; determining, based on the image recognition model, whether at least one pixel in the real-time soil image is identical to a pixel at a corresponding position in the historical soil image; if so, marking the at least one pixel in the real-time soil image as an abnormal pixel; clustering at least two adjacent abnormal pixels to obtain at least one abnormal region; and correcting at least one risk region in the real-time soil image based on a preset correction strategy to obtain a real-time contaminated region map at the current acquisition time. This method reduces the amount of soil data collected while improving the accuracy of determining the scope of soil remediation.

Description

Technical Field

[0001] The present invention belongs to the technical field of soil contaminated areas, and in particular relates to a soil remediation monitoring method and system. Background Art

[0002] Due to the wide variety and complex conditions of soil pollutants, different means need to be adopted in the process of soil remediation and the remediation methods need to be adjusted in time according to the conditions of soil pollution remediation. This requires monitoring of the soil pollution remediation effect.

[0003] Currently, during soil remediation, a grid of monitoring points is often set up within the monitoring area. Soil data from these grid points is collected at a preset frequency, and the remediation scope is determined based on this data analysis. However, this monitoring method is inefficient, requiring a large amount of soil data for each monitoring session, which increases the complexity of monitoring. Summary of the Invention

[0004] The present invention provides a soil remediation monitoring method and system, which are used to solve the technical problem that existing monitoring methods are inefficient and each monitoring requires a large amount of soil data to support, thereby increasing the complexity of monitoring.

[0005] In a first aspect, the present invention provides a soil remediation monitoring method, comprising:

[0006] Obtain a historical pollution area map of the area to be monitored at the last collection moment, wherein the historical pollution area map includes historical pollution areas;

[0007] Obtaining a historical soil image of the monitored area at a previous acquisition time and a real-time soil image at a current acquisition time, inputting the historical soil image and the real-time soil image into a pre-built image recognition model, and determining, based on the image recognition model, whether at least one pixel in the real-time soil image is identical to a pixel at a corresponding position in the historical soil image;

[0008] If at least one pixel in the real-time soil image is identical to a pixel at a corresponding position in the historical soil image, marking the at least one pixel in the real-time soil image as an abnormal pixel, and clustering at least two adjacent abnormal pixels to obtain at least one abnormal region;

[0009] Determining whether a distance between a first center point of a first abnormal region and a second center point of a second abnormal region is greater than a preset distance threshold, wherein the first abnormal region and the second abnormal region are both abnormal regions in the at least one abnormal region;

[0010] If the distance is not greater than a preset distance threshold, the first abnormal area and the second abnormal area are fused based on a preset fusion strategy, and the fused area is defined as a risk area;

[0011] Correcting at least one risk area in the real-time soil image based on a preset correction strategy to obtain a real-time contaminated area map at the current acquisition moment, wherein the real-time contaminated area map includes a real-time contaminated area;

[0012] Subtract the historical pollution area from the real-time pollution area to obtain soil remediation.

[0013] In a second aspect, the present invention provides a soil remediation monitoring system, comprising:

[0014] an acquisition module configured to acquire a historical pollution area map of the area to be monitored at a previous collection moment, wherein the historical pollution area map includes historical pollution areas;

[0015] a first judgment module configured to obtain a historical soil image of the monitored area at a previous acquisition time and a real-time soil image at a current acquisition time, input the historical soil image and the real-time soil image into a pre-built image recognition model, and determine, based on the image recognition model, whether at least one pixel in the real-time soil image is identical to a pixel at a corresponding position in the historical soil image;

[0016] a clustering module configured to mark at least one pixel in the real-time soil image as an abnormal pixel if at least one pixel in the real-time soil image is identical to a pixel at a corresponding position in the historical soil image, and cluster at least two adjacent abnormal pixels to obtain at least one abnormal region;

[0017] a second determination module configured to determine whether a distance between a first center point of a first abnormal region and a second center point of a second abnormal region is greater than a preset distance threshold, wherein the first abnormal region and the second abnormal region are both abnormal regions in the at least one abnormal region;

[0018] a fusion module configured to fuse the first abnormal area and the second abnormal area based on a preset fusion strategy if the distance is not greater than a preset distance threshold, and define the fused area as a risk area;

[0019] a correction module configured to correct at least one risk area in the real-time soil image based on a preset correction strategy to obtain a real-time contaminated area map at a current acquisition moment, wherein the real-time contaminated area map includes a real-time contaminated area;

[0020] The output module is configured to subtract the historical pollution area from the real-time pollution area to obtain soil remediation.

[0021] In a third aspect, an electronic device is provided, comprising: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the steps of the soil remediation monitoring method according to any embodiment of the present invention.

[0022] In a fourth aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, wherein when the program instructions are executed by a processor, the processor executes the steps of the soil remediation monitoring method of any embodiment of the present invention.

[0023] The soil remediation monitoring method and system of the present application obtain a historical soil image of the monitored area at the previous acquisition moment and a real-time soil image at the current acquisition moment, and input the historical soil image and the real-time soil image into a pre-constructed image recognition model. According to the image recognition model, it is determined whether at least one pixel point in the real-time soil image is the same as the pixel point at the corresponding position in the historical soil image. If at least one pixel point in the real-time soil image is the same as the pixel point at the corresponding position in the historical soil image, at least one pixel point in the real-time soil image is marked as an abnormal pixel point, and at least two adjacent abnormal pixels are clustered to obtain at least one abnormal area. At least one risk area in the real-time soil image is corrected based on a preset correction strategy to obtain a real-time contaminated area map at the current acquisition moment. While reducing the amount of soil data collected, it can improve the accuracy of determining the scope of soil remediation. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following is a brief introduction to the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0025] Figure 1 A flow chart of a soil remediation monitoring method provided by one embodiment of the present invention;

[0026] Figure 2 A structural block diagram of a soil remediation monitoring system provided by one embodiment of the present invention;

[0027] Figure 3 It is a structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0028] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0029] See also Figure 1 , which shows a flow chart of a soil remediation monitoring method of the present application.

[0030] like Figure 1 As shown, the soil remediation monitoring method specifically includes the following steps:

[0031] Step S101 : obtaining a historical pollution area map of the area to be monitored at the last collection moment, wherein the historical pollution area map includes historical pollution areas.

[0032] Step S102: Obtain a historical soil image of the monitored area at the previous acquisition moment and a real-time soil image at the current acquisition moment, input the historical soil image and the real-time soil image into a pre-built image recognition model, and determine, based on the image recognition model, whether at least one pixel point in the real-time soil image is identical to a pixel point at a corresponding position in the historical soil image.

[0033] In this step, the image recognition model can be obtained by training a convolutional neural network. For example, the training sample containing the labeled box is input into the convolutional neural network for training.

[0034] It should be noted that after determining whether at least one pixel point in the real-time soil image is the same as the pixel point at the corresponding position in the historical soil image based on the image recognition model, if at least one pixel point in the real-time soil image is different from the pixel point at the corresponding position in the historical soil image, then at least one pixel point in the real-time soil image is marked as a normal pixel point, and at least two adjacent normal pixels are clustered to obtain a normal area.

[0035] For example, after remediation, vegetation may grow on the surface of the soil, and the area with vegetation can be defined as a normal area; however, the soil surface may not have undergone substantial changes after remediation, so steps S103-S107 need to be executed to further determine the scope of soil remediation.

[0036] Step S103: If at least one pixel in the real-time soil image is the same as a pixel at a corresponding position in the historical soil image, at least one pixel in the real-time soil image is marked as an abnormal pixel, and at least two adjacent abnormal pixels are clustered to obtain at least one abnormal area.

[0037] Step S104 , determining whether a distance between a first center point of a first abnormal region and a second center point of a second abnormal region is greater than a preset distance threshold, wherein the first abnormal region and the second abnormal region are both abnormal regions in the at least one abnormal region.

[0038] In a specific embodiment, after determining whether the distance between the first center point of the first abnormal area and the second center point of the second abnormal area is greater than a preset distance threshold, if it is greater than the preset distance threshold, the first abnormal area and the second abnormal area are directly defined as risk areas respectively.

[0039] Step S105: If the distance is not greater than a preset distance threshold, the first abnormal area and the second abnormal area are fused based on a preset fusion strategy, and the fused area is defined as a risk area.

[0040] In this step, the first center point of the first abnormal area and the second center point of the second abnormal area are obtained, and the first center point and the second center point are connected to obtain a target line segment; it is determined whether the distance from the third center point of the normal area to the target line segment is greater than the length of the target line segment; if it is greater, a preset sliding window is slid on the target line segment, and the area covered by the sliding window, the first abnormal area and the second abnormal area are fused, and the fused area is defined as a risk area, wherein the radius of the sliding window is the length of the target line segment; if it is not greater, the first abnormal area and the second abnormal area are directly defined as risk areas.

[0041] It should be noted that if the distance from the third center point of the normal area to the target segment is greater than the length of the target segment, it means that the first abnormal area and the second abnormal area are far away from the center point of the normal area. In actual application scenarios, the occurrence of this phenomenon indicates that a part of the normal area between the first abnormal area and the second abnormal area is in the recovery stage, that is, the pollutant concentration is gradually decreasing, but it does not mean that the pollutant concentration has dropped below the preset concentration. Therefore, it is necessary to merge this part of the normal area with the abnormal area to facilitate subsequent soil data collection and analysis. In this way, the polluted area at the current moment can be obtained more accurately.

[0042] Step S106: correct at least one risk area in the real-time soil image based on a preset correction strategy to obtain a real-time contaminated area map at the current acquisition moment, wherein the real-time contaminated area map includes a real-time contaminated area.

[0043] In this step, first soil sample data of each monitoring point in a certain risk area is obtained; the certain risk area is corrected according to each first soil sample data to obtain at least one target risk area.

[0044] Specifically, soil data is obtained through field sampling and experimental analysis of the sampled soil. Soil data reflects the concentration of pollutants in the soil. By measuring pollutant concentrations in risk areas, the amount of data collected can be minimized while more accurately determining the scope of contamination.

[0045] Step S107: Subtract the historical pollution area from the real-time pollution area to obtain soil remediation.

[0046] In this step, the historical pollution area map and the real-time pollution area map are input into a pre-built image deduplication model. The image deduplication model removes the real-time pollution area on the historical pollution area map and outputs soil remediation.

[0047] It should be noted that the image deduplication model can be trained by residual neural network.

[0048] In summary, the method of the present application obtains a historical soil image of the monitored area at the previous acquisition moment and a real-time soil image at the current acquisition moment, and inputs the historical soil image and the real-time soil image into a pre-constructed image recognition model. According to the image recognition model, it is determined whether at least one pixel point in the real-time soil image is the same as the pixel point at the corresponding position in the historical soil image. If at least one pixel point in the real-time soil image is the same as the pixel point at the corresponding position in the historical soil image, at least one pixel point in the real-time soil image is marked as an abnormal pixel point, and at least two adjacent abnormal pixels are clustered to obtain at least one abnormal area. Based on a preset correction strategy, at least one risk area in the real-time soil image is corrected to obtain a real-time contaminated area map at the current acquisition moment. While reducing the amount of soil data collected, it can improve the accuracy of determining the scope of soil remediation.

[0049] See also Figure 2 , which shows a structural block diagram of a soil remediation monitoring system of the present application.

[0050] like Figure 2As shown, the soil remediation monitoring system 200 includes an acquisition module 210 , a first judgment module 220 , a clustering module 230 , a second judgment module 240 , a fusion module 250 , a correction module 260 and an output module 270 .

[0051] Among them, the acquisition module 210 is configured to obtain a historical pollution area map of the area to be monitored at the last acquisition moment, wherein the historical pollution area map contains historical pollution areas; the first judgment module 220 is configured to obtain a historical soil image of the area to be monitored at the last acquisition moment, and a real-time soil image at the current acquisition moment, and input the historical soil image and the real-time soil image into a pre-built image recognition model, and judge whether at least one pixel point in the real-time soil image is the same as the pixel point at the corresponding position in the historical soil image according to the image recognition model; the clustering module 230 is configured to mark at least one pixel point in the real-time soil image as an abnormal pixel point if at least one pixel point in the real-time soil image is the same as the pixel point at the corresponding position in the historical soil image, and cluster at least two adjacent abnormal pixels to obtain to at least one abnormal area; a second judgment module 240 is configured to judge whether the distance between the first center point of the first abnormal area and the second center point of the second abnormal area is greater than a preset distance threshold, wherein the first abnormal area and the second abnormal area are both abnormal areas in the at least one abnormal area; a fusion module 250 is configured to fuse the first abnormal area and the second abnormal area based on a preset fusion strategy if it is not greater than the preset distance threshold, and define the fused area as a risk area; a correction module 260 is configured to correct at least one risk area in the real-time soil image based on a preset correction strategy to obtain a real-time contaminated area map at the current acquisition moment, wherein the real-time contaminated area map contains a real-time contaminated area; an output module 270 is configured to subtract the historical contaminated area from the real-time contaminated area to obtain soil remediation.

[0052] It should be understood that Figure 2 Modules and references documented in Figure 1 Therefore, the operations and features described above for the method and the corresponding technical effects also apply to Figure 2 The modules in it will not be described in detail here.

[0053] In other embodiments, embodiments of the present invention further provide a computer-readable storage medium having a computer program stored thereon, wherein when the program instructions are executed by a processor, the processor is caused to execute the soil remediation monitoring method in any of the above method embodiments;

[0054] As an embodiment, the computer-readable storage medium of the present invention stores computer-executable instructions, and the computer-executable instructions are configured as follows:

[0055] Obtain a historical pollution area map of the area to be monitored at the last collection moment, wherein the historical pollution area map includes historical pollution areas;

[0056] Obtaining a historical soil image of the monitored area at a previous acquisition time and a real-time soil image at a current acquisition time, inputting the historical soil image and the real-time soil image into a pre-built image recognition model, and determining, based on the image recognition model, whether at least one pixel in the real-time soil image is identical to a pixel at a corresponding position in the historical soil image;

[0057] If at least one pixel in the real-time soil image is identical to a pixel at a corresponding position in the historical soil image, marking the at least one pixel in the real-time soil image as an abnormal pixel, and clustering at least two adjacent abnormal pixels to obtain at least one abnormal region;

[0058] Determining whether a distance between a first center point of a first abnormal region and a second center point of a second abnormal region is greater than a preset distance threshold, wherein the first abnormal region and the second abnormal region are both abnormal regions in the at least one abnormal region;

[0059] If the distance is not greater than a preset distance threshold, the first abnormal area and the second abnormal area are fused based on a preset fusion strategy, and the fused area is defined as a risk area;

[0060] Correcting at least one risk area in the real-time soil image based on a preset correction strategy to obtain a real-time contaminated area map at the current acquisition moment, wherein the real-time contaminated area map includes a real-time contaminated area;

[0061] Subtract the historical pollution area from the real-time pollution area to obtain soil remediation.

[0062] The computer-readable storage medium may include a program storage area and a data storage area. The program storage area may store an operating system and application programs required for at least one function; the data storage area may store data generated based on the use of the soil remediation monitoring system. Furthermore, the computer-readable storage medium may include high-speed random access memory and may also include storage, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some embodiments, the computer-readable storage medium may optionally include storage remote from the processor. Such remote storage may be connected to the soil remediation monitoring system via a network. Examples of such networks include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0063] Figure 3 Schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. Figure 3 As shown, the device includes: a processor 310 and a memory 320. The electronic device may also include: an input device 330 and an output device 340. The processor 310, the memory 320, the input device 330 and the output device 340 may be connected via a bus or other means. Figure 3 The example of a bus connection is shown. Memory 320 is the aforementioned computer-readable storage medium. Processor 310 executes the various server functional applications and data processing by running the non-volatile software programs, instructions, and modules stored in memory 320, thereby implementing the soil remediation monitoring method described in the aforementioned method embodiment. Input device 330 can receive input digital or character information and generate key signal input related to user settings and function control of the soil remediation monitoring system. Output device 340 can include a display device such as a display screen.

[0064] The electronic device can execute the method provided by the embodiment of the present invention, and has the functional modules and beneficial effects corresponding to the execution method. For technical details not fully described in this embodiment, please refer to the method provided by the embodiment of the present invention.

[0065] As an embodiment, the electronic device is applied to a soil remediation monitoring system and is used for a client, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to:

[0066] Obtain a historical pollution area map of the area to be monitored at the last collection moment, wherein the historical pollution area map includes historical pollution areas;

[0067] Obtaining a historical soil image of the monitored area at a previous acquisition time and a real-time soil image at a current acquisition time, inputting the historical soil image and the real-time soil image into a pre-built image recognition model, and determining, based on the image recognition model, whether at least one pixel in the real-time soil image is identical to a pixel at a corresponding position in the historical soil image;

[0068] If at least one pixel in the real-time soil image is identical to a pixel at a corresponding position in the historical soil image, marking the at least one pixel in the real-time soil image as an abnormal pixel, and clustering at least two adjacent abnormal pixels to obtain at least one abnormal region;

[0069] Determining whether a distance between a first center point of a first abnormal region and a second center point of a second abnormal region is greater than a preset distance threshold, wherein the first abnormal region and the second abnormal region are both abnormal regions in the at least one abnormal region;

[0070] If the distance is not greater than a preset distance threshold, the first abnormal area and the second abnormal area are fused based on a preset fusion strategy, and the fused area is defined as a risk area;

[0071] Correcting at least one risk area in the real-time soil image based on a preset correction strategy to obtain a real-time contaminated area map at the current acquisition moment, wherein the real-time contaminated area map includes a real-time contaminated area;

[0072] Subtract the historical pollution area from the real-time pollution area to obtain soil remediation.

[0073] Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented using software plus a necessary general-purpose hardware platform, or of course, hardware. Based on this understanding, the essence of the above technical solution, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, or an optical disk, and includes a number of instructions for causing a computer device (such as a personal computer, server, or network device) to execute the methods of each embodiment or certain portions of the embodiments.

[0074] 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 it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A soil remediation monitoring method, characterized in that: include: Obtain a historical pollution area map of the area to be monitored at the last collection moment, wherein the historical pollution area map includes historical pollution areas; Acquire a historical soil image of the area to be monitored at a previous acquisition moment and a real-time soil image at a current acquisition moment, input the historical soil image and the real-time soil image into a pre-built image recognition model, and determine, based on the image recognition model, whether at least one pixel in the real-time soil image is identical to a pixel at a corresponding position in the historical soil image. After determining, based on the image recognition model, whether at least one pixel in the real-time soil image is identical to a pixel at a corresponding position in the historical soil image, the method further includes: If at least one pixel in the real-time soil image is different from a pixel at a corresponding position in the historical soil image, marking the at least one pixel in the real-time soil image as a normal pixel, and clustering at least two adjacent normal pixels to obtain a normal area; If at least one pixel in the real-time soil image is identical to a pixel at a corresponding position in the historical soil image, marking the at least one pixel in the real-time soil image as an abnormal pixel, and clustering at least two adjacent abnormal pixels to obtain at least one abnormal region; Determining whether a distance between a first center point of a first abnormal region and a second center point of a second abnormal region is greater than a preset distance threshold, wherein the first abnormal region and the second abnormal region are both abnormal regions in the at least one abnormal region; If the distance is not greater than a preset distance threshold, the first abnormal area and the second abnormal area are fused based on a preset fusion strategy, and the fused area is defined as a risk area, wherein the fusion of the first abnormal area and the second abnormal area based on a preset fusion strategy and defining the fused area as a risk area includes: Obtaining a first center point of the first abnormal area and a second center point of the second abnormal area, and connecting the first center point and the second center point to obtain a target line segment; Determining whether the distance from the third center point of the normal area to the target line segment is greater than the length of the target line segment; If it is greater than, sliding a preset sliding window on the target segment, fusing the area covered by the sliding window, the first abnormal area, and the second abnormal area, and defining the fused area as a risk area, wherein the radius of the sliding window is the length of the target segment; If not, the first abnormal area and the second abnormal area are directly defined as risk areas; Correcting at least one risk area in the real-time soil image based on a preset correction strategy to obtain a real-time contaminated area map at the current acquisition moment, wherein the real-time contaminated area map includes a real-time contaminated area; Subtract the historical pollution area from the real-time pollution area to obtain soil remediation.

2. A soil remediation monitoring method according to claim 1, characterized in that: After determining whether the distance between the first center point of the first abnormal area and the second center point of the second abnormal area is greater than a preset distance threshold, the method further includes: If the distance is greater than a preset distance threshold, the first abnormal area and the second abnormal area are directly defined as risk areas respectively.

3. A soil remediation monitoring method according to claim 1, characterized in that: The step of correcting at least one risk area in the real-time soil image based on a preset correction strategy to obtain a real-time contaminated area map at the current acquisition moment includes: Obtaining first soil sample data at each monitoring point in a risk area; The risk area is corrected according to each first soil sample data to obtain at least one target risk area.

4. A soil remediation monitoring method according to claim 1, characterized in that: Subtracting the historical contaminated area from the real-time contaminated area to obtain soil remediation includes: The historical pollution area map and the real-time pollution area map are input into a pre-built image deduplication model. The image deduplication model removes the real-time pollution area from the historical pollution area map and outputs soil remediation.

5. A soil remediation monitoring system, characterized in that: include: An acquisition module is configured to acquire a historical pollution area map of the area to be monitored at a previous collection moment, wherein the historical pollution area map includes historical pollution areas; A first judgment module is configured to obtain a historical soil image of the monitored area at a previous acquisition moment and a real-time soil image at a current acquisition moment, and input the historical soil image and the real-time soil image into a pre-built image recognition model, and judge whether at least one pixel point in the real-time soil image is identical to a pixel point at a corresponding position in the historical soil image according to the image recognition model, wherein, after judging whether at least one pixel point in the real-time soil image is identical to a pixel point at a corresponding position in the historical soil image according to the image recognition model, the module further includes: If at least one pixel in the real-time soil image is different from a pixel at a corresponding position in the historical soil image, marking the at least one pixel in the real-time soil image as a normal pixel, and clustering at least two adjacent normal pixels to obtain a normal area; a clustering module configured to mark at least one pixel in the real-time soil image as an abnormal pixel if at least one pixel in the real-time soil image is identical to a pixel at a corresponding position in the historical soil image, and cluster at least two adjacent abnormal pixels to obtain at least one abnormal region; a second determination module configured to determine whether a distance between a first center point of a first abnormal region and a second center point of a second abnormal region is greater than a preset distance threshold, wherein the first abnormal region and the second abnormal region are both abnormal regions in the at least one abnormal region; A fusion module is configured to fuse the first abnormal area and the second abnormal area based on a preset fusion strategy if the distance is not greater than a preset distance threshold, and define the fused area as a risk area, wherein the fusing the first abnormal area and the second abnormal area based on the preset fusion strategy and defining the fused area as a risk area includes: Obtaining a first center point of the first abnormal area and a second center point of the second abnormal area, and connecting the first center point and the second center point to obtain a target line segment; Determining whether the distance from the third center point of the normal area to the target line segment is greater than the length of the target line segment; If it is greater than, sliding a preset sliding window on the target segment, fusing the area covered by the sliding window, the first abnormal area, and the second abnormal area, and defining the fused area as a risk area, wherein the radius of the sliding window is the length of the target segment; If not, the first abnormal area and the second abnormal area are directly defined as risk areas; a correction module configured to correct at least one risk area in the real-time soil image based on a preset correction strategy to obtain a real-time contaminated area map at a current acquisition moment, wherein the real-time contaminated area map includes a real-time contaminated area; The output module is configured to subtract the historical pollution area from the real-time pollution area to obtain soil remediation.

6. An electronic device, characterized in that: include: At least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 4 is implemented.

Images