Soil pollution real-time detection and analysis method and system based on spectral analysis

Abstract

The invention relates to the technical field of soil pollution detection, in particular to a soil pollution real-time detection and analysis method and system based on spectral analysis, and the system comprises a soil pollution detection platform, a soil database, a regional pollution division unit, a sample check analysis unit, a regional identification analysis unit, a pollution diffusion analysis unit and a display response unit. Analysis is carried out from two points of an unmanned aerial vehicle hyperspectral technology and a sample collection and detection technology, namely, regional pollution division feedback analysis is carried out on a spectral feature image to judge whether a heavy metal pollution area exists in a target soil area or not and the pollution degree condition, and regional pollution matching check analysis is carried out on sample parameters to judge whether the target soil area has a heavy metal pollution area or not. According to the method, the unmanned aerial vehicle hyperspectral detection can be checked and fed back through sample experiment detection, and whether the two types of detection are consistent or not can be visually known through an information feedback display mode, so that the availability of a detection result is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of soil pollution detection, and in particular to a real-time soil pollution detection and analysis method and system based on spectral analysis. Background Art

[0002] As a key resource for human survival, soil plays a vital role in human production and life. With the rapid development of urbanization, industrialization and agricultural intensification, a large amount of chemical fertilizers and drugs are used in soil, resulting in increasingly serious soil heavy metal pollution. Since the soil itself has a buffering effect on pollutants, when heavy metals enter the soil, they can be quickly fixed and "aged" by soil colloids with strong adsorption capacity, thereby reducing the nutrient supply of the soil and its effectiveness to plants.

[0003] However, in the existing technology, it is impossible to verify and feedback the results of soil pollution detection, which is not conducive to targeted management of soil, and it is impossible to accurately understand the content and degree of pollution of various polluting metal elements in the soil heavy metal pollution area, and thus it is impossible to comprehensively and meticulously reflect the pollution situation. At the same time, it is impossible to evaluate the pollution spread risk of the soil heavy metal pollution area, and thus it is impossible to rationally remediate the soil heavy metal pollution area;

[0004] In view of the above technical defects, a solution is now proposed. Summary of the invention

[0005] The purpose of the present invention is to provide a real-time detection and analysis method and system for soil pollution based on spectral analysis to solve the above-mentioned technical defects. The present invention analyzes from two points of view: UAV hyperspectral technology and sample collection detection technology, and intuitively understands whether the two detections are consistent through information feedback display to ensure the availability of the detection results. The analysis is performed from two points of view: pollution identification processing and pollution diffusion, that is, regional pollution identification processing and analysis are performed on the pre-collected hyperspectral data, which helps to intuitively understand the degree and content of heavy metal pollution in each high-pollution area and low-pollution area, and can more comprehensively and meticulously reflect the pollution status, providing more reliable data support for pollution control, and performing regional pollution diffusion risk assessment feedback analysis on heavy metal polluted areas, so as to intuitively understand the heavy metal pollution diffusion risk situation in the target soil area, so as to rationally repair and manage the heavy metal pollution in the target soil area.

[0006] The object of the present invention can be achieved by the following technical solutions: A real-time soil pollution detection and analysis system based on spectral analysis, comprising a soil pollution detection platform, a soil database, a regional pollution division unit, a sample verification and analysis unit, a regional identification analysis unit, a pollution diffusion analysis unit and a display response unit;

[0007] The soil pollution detection platform is used to retrieve the spectral characteristic image of the target soil area from the soil database and send the spectral characteristic image to the regional pollution division unit;

[0008] The regional pollution division unit is used to perform regional pollution division feedback analysis on the received spectral feature image, judge the obtained heavy metal pollution concentration to obtain high pollution areas and low pollution areas, and discriminate the obtained pollution hazard coefficient to obtain local pollution signals or overall pollution signals;

[0009] The sample checking and analysis unit is used to retrieve the sample parameters of the soil samples in the target soil area, and perform regional pollution matching checking and analysis on the sample parameters, and perform discriminant analysis on the obtained pollution matching deviation values ​​to obtain a standard signal or a deviation signal;

[0010] The regional identification analysis unit is used to respond to the standard signal and simultaneously perform regional pollution identification processing and analysis on the pre-collected hyperspectral data to obtain a regional identification string;

[0011] The pollution diffusion analysis unit is used to respond to standard signals and conduct feedback analysis on regional pollution diffusion risk assessment of heavy metal polluted areas to obtain the diffusion assessment grade KS.

[0012] Preferably, the regional pollution division feedback analysis process is as follows:

[0013] Set a monitoring period, obtain the spectral characteristic image of the target soil area within the monitoring period through the UAV hyperspectral technology, and preprocess the collected spectral characteristic image, including noise removal, atmospheric correction, and geometric correction;

[0014] Retrieving a heavy metal pollution identification model from a soil database, obtaining a heavy metal pollution area in a target soil area based on a preprocessed spectral feature image and the heavy metal pollution identification model, obtaining a heavy metal pollution concentration in the heavy metal pollution area, performing judgment processing on the heavy metal pollution concentration, setting an area corresponding to a heavy metal pollution concentration greater than or equal to a preset heavy metal pollution concentration threshold as a high pollution area, and setting an area corresponding to a heavy metal pollution concentration less than a preset heavy metal pollution concentration threshold as a low pollution area;

[0015] The ratio of the area corresponding to the heavy metal pollution area to the total area corresponding to the target soil area is set as the pollution hazard coefficient, and the pollution hazard coefficient is discriminated and processed to obtain a local pollution signal or an overall pollution signal.

[0016] Preferably, the regional pollution matching verification and analysis process is as follows:

[0017] Obtaining sample parameters of soil samples in the target soil area, the sample parameters including sampling point coordinates and sample hyperspectral data;

[0018] Based on the sample parameters, the coordinates of high-pollution points and low-pollution points in the target soil area are obtained, and the high-pollution area and low-pollution area of ​​the target soil area are obtained at the same time. The high-pollution point coordinates and the low-pollution point coordinates are matched and analyzed with the high-pollution area and the low-pollution area to obtain the pollution matching deviation value of the target soil area. The pollution matching deviation value represents the sum of the number of high-pollution point coordinates that do not belong to the high-pollution area and the number of low-pollution point coordinates that do not belong to the low-pollution area. The pollution matching deviation value is discriminated and analyzed to obtain a standard signal or a deviation signal.

[0019] Preferably, the regional pollution identification processing and analysis process is as follows:

[0020] The hyperspectral data of each high-pollution area and low-pollution area in the target soil area are obtained. The hyperspectral data represent a hyperspectral characteristic image. The hyperspectral characteristic image is compared and analyzed with the standard spectral library, that is, the heavy metal information of each high-pollution area and low-pollution area is obtained. The heavy metal information includes lead metal concentration and mercury metal concentration. The parameter in the heavy metal information is set to g, where g is a natural number greater than zero. The numerical value corresponding to each parameter in the heavy metal information is obtained and set as the metal content value Jg. The metal content value Jg is discriminated and processed, and the metal name corresponding to the metal content value Jg greater than or equal to the preset metal content value threshold is set as the polluted metal name.

[0021] Preferably, the metal content value corresponding to each polluting metal name is obtained, and the combination of the polluting metal name and the corresponding metal content value is set as a polluting metal phrase, and based on the size relationship of the metal content values ​​corresponding to each polluting metal name, the polluting metal phrases are sorted in order from large to small, and characters are extracted from the sorted polluting metal phrases, and the identification string composed of the characters extracted from the sorted polluting metal phrases is set as the area identification string.

[0022] Preferably, the regional pollution diffusion risk assessment feedback analysis process is as follows:

[0023] The area corresponding to the heavy metal pollution area of ​​the target soil area within the monitoring period is obtained, and it is set as the initial pollution area. The pollution area of ​​the target soil area is collected every t1 time period, and the collection is n times, where t1 is greater than zero and n is a natural number greater than 3. At the same time, the value obtained by subtracting the initial pollution area from the pollution area of ​​the collected target soil area is set as the pollution diffusion coefficient. The number of pollution diffusion coefficients greater than the preset pollution diffusion coefficient threshold is obtained and set as the diffusion trend index. The diffusion trend index is discriminated: if the diffusion trend index is less than the preset diffusion trend index threshold, a stable signal is generated; if the diffusion trend index is greater than or equal to the preset diffusion trend index threshold, a diffusion signal is generated.

[0024] Preferably, when a diffusion signal is generated: the total time corresponding to the collection of the pollution area of ​​the target soil area n times is obtained, and it is set as the diffusion assessment time, the pollution area change value of the target soil area within the diffusion assessment time is obtained, and it is set as the pollution area floating value, the ratio between the pollution area floating value and the diffusion assessment time is set as the diffusion impact ratio, and the diffusion impact ratio is discriminated and processed to obtain first-level risk, second-level risk and third-level risk, and the first-level risk, second-level risk and third-level risk are set as diffusion assessment levels KS, KS=1, 2, 3.

[0025] The beneficial effects of the present invention are as follows:

[0026] (1) The present invention analyzes the UAV hyperspectral technology and sample collection and detection technology from two perspectives, namely, regional pollution division feedback analysis is performed on the spectral feature image to determine whether there is a heavy metal pollution area and the degree of pollution in the target soil area, and regional pollution matching verification analysis is performed on the sample parameters, so as to verify and feedback the UAV hyperspectral detection through sample experimental detection, so as to verify and feedback the UAV hyperspectral detection through sample experimental detection, and at the same time, the information feedback display method is used to intuitively understand whether the two detections are consistent, so as to ensure the availability of the detection results;

[0027] (2) The present invention analyzes from two points of view: pollution identification and pollution diffusion. That is, the pre-collected hyperspectral data is analyzed for regional pollution identification, which helps to intuitively understand the pollution degree and content of each heavy metal in each high-pollution area and low-pollution area, and can reflect the pollution situation more comprehensively and meticulously, providing more reliable data support for pollution control. The regional pollution diffusion risk assessment feedback analysis is conducted on the heavy metal polluted area, so as to intuitively understand the heavy metal pollution diffusion risk situation in the target soil area, so as to rationally remediate and manage the heavy metal pollution in the target soil area. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The present invention will be further described below in conjunction with the accompanying drawings;

[0029] Figure 1 It is a flowchart of the system of the present invention;

[0030] Figure 2 It is a reference analysis diagram of the method of the present invention. DETAILED DESCRIPTION

[0031] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in 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. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0032] Embodiment 1:

[0033] See also Figure 1 to Figure 2 As shown, the present invention is a real-time soil pollution detection and analysis system based on spectral analysis, including a soil pollution detection platform, a soil database, a regional pollution division unit, a sample verification and analysis unit, a regional identification analysis unit, a pollution diffusion analysis unit and a display response unit, the soil database is connected to the soil pollution detection platform in a one-way communication, the soil pollution detection platform is connected to the regional pollution division unit and the sample verification and analysis unit in a one-way communication, the regional pollution division unit is connected to the sample verification and analysis unit and the display response unit in a one-way communication, the sample verification and analysis unit is connected to the regional identification analysis unit in a one-way communication, the regional identification analysis unit is connected to the pollution diffusion analysis unit and the display response unit in a one-way communication, and the pollution diffusion analysis unit is connected to the display response unit in a one-way communication;

[0034] The soil pollution detection platform is used to retrieve the spectral characteristic image of the target soil area from the soil database and send the spectral characteristic image to the regional pollution division unit;

[0035] The regional pollution division unit is used to perform regional pollution division feedback analysis on the received spectral feature image to determine whether there is a heavy metal pollution area in the target soil area and the degree of pollution. The specific regional pollution division feedback analysis process is as follows:

[0036] Set a monitoring period, use the UAV hyperspectral technology to obtain the spectral characteristic images of the target soil area within the monitoring period, and preprocess the collected spectral characteristic images, including noise removal, atmospheric correction, geometric correction, etc.

[0037] Retrieving a heavy metal pollution identification model from a soil database, obtaining a heavy metal pollution area in a target soil area based on a preprocessed spectral feature image and the heavy metal pollution identification model, obtaining a heavy metal pollution concentration in the heavy metal pollution area, performing judgment processing on the heavy metal pollution concentration, setting an area corresponding to a heavy metal pollution concentration greater than or equal to a preset heavy metal pollution concentration threshold as a high pollution area, and setting an area corresponding to a heavy metal pollution concentration less than a preset heavy metal pollution concentration threshold as a low pollution area;

[0038] The ratio of the area corresponding to the heavy metal pollution area to the total area corresponding to the target soil area is set as the pollution hazard coefficient, and the pollution hazard coefficient is discriminated:

[0039] If the pollution hazard coefficient is less than the preset pollution hazard coefficient threshold, a local pollution signal is generated;

[0040] If the pollution hazard coefficient is greater than or equal to the preset pollution hazard coefficient threshold, an overall pollution signal is generated, and the local pollution signal or the overall pollution signal is sent to the display response unit. After receiving the local pollution signal or the overall pollution signal, the display response unit immediately performs a preset warning operation corresponding to the local pollution signal or the overall pollution signal, so as to intuitively understand the situation and degree of heavy metal pollution in the target soil area, so as to carry out reasonable and targeted remediation management of the heavy metal pollution area in the target soil area;

[0041] The sample verification and analysis unit is used to retrieve the sample parameters of the soil samples in the target soil area and perform regional pollution matching verification and analysis on the sample parameters, so as to verify and feedback the UAV hyperspectral detection through sample experimental detection to improve the accuracy of the detection results. The specific regional pollution matching verification and analysis process is as follows:

[0042] Obtaining sample parameters of soil samples in the target soil area, including sampling point coordinates, sample hyperspectral data, etc.;

[0043] Based on the sample parameters, the coordinates of high-pollution points and low-pollution points in the target soil area are obtained, and the high-pollution area and low-pollution area of ​​the target soil area are obtained at the same time. The high-pollution point coordinates and the low-pollution point coordinates are matched and analyzed with the high-pollution area and the low-pollution area to obtain the pollution matching deviation value of the target soil area. The pollution matching deviation value represents the sum of the number of high-pollution point coordinates that do not belong to the high-pollution area and the number of low-pollution point coordinates that do not belong to the low-pollution area;

[0044] In the embodiment of the present invention, the high pollution point coordinates represent the sampling point coordinates corresponding to the heavy metal pollution concentration being greater than or equal to the preset heavy metal pollution concentration threshold; the low pollution point coordinates represent the sampling point coordinates corresponding to the heavy metal pollution concentration being less than the preset heavy metal pollution concentration threshold;

[0045] Perform discriminant analysis on the contamination match deviation value:

[0046] If the contamination match deviation value is equal to zero, a standard signal is generated;

[0047] If the contamination matching deviation value is not equal to zero, a deviation signal is generated, and the standard signal or the deviation signal is sent to the display response unit. After receiving the standard signal or the deviation signal, the display response unit immediately performs the preset warning operation corresponding to the standard signal or the deviation signal, so as to intuitively understand whether the two tests are consistent, so as to ensure the availability of the test results.

[0048] Embodiment 2:

[0049] When the standard signal is generated, the regional identification analysis unit is used to respond to the standard signal and perform regional pollution identification processing and analysis on the pre-collected hyperspectral data, which helps to intuitively understand the pollution degree and content of each heavy metal in each high-pollution area and low-pollution area, and can more comprehensively and meticulously reflect the pollution status, providing more reliable data support for pollution control. The specific regional pollution identification processing and analysis process is as follows:

[0050] Obtain hyperspectral data of each high-pollution area and low-pollution area in the target soil area, the hyperspectral data represents a hyperspectral characteristic image, compare and analyze the hyperspectral characteristic image with the standard spectral library, that is, obtain heavy metal information of each high-pollution area and low-pollution area, the heavy metal information includes lead metal concentration, mercury metal concentration, etc., set the parameter in the heavy metal information to g, g is a natural number greater than zero, obtain the value corresponding to each parameter in the heavy metal information, and set it as the metal content value Jg, and perform discrimination processing on the metal content value Jg, and set the metal name corresponding to the metal content value Jg greater than or equal to the preset metal content value threshold as the polluted metal name;

[0051] The metal content value corresponding to each polluting metal name is obtained, and the combination of the polluting metal name and the corresponding metal content value is set as a polluting metal phrase, and based on the size relationship of the metal content values ​​corresponding to each polluting metal name, the polluting metal phrases are sorted in descending order, and characters are extracted from the sorted polluting metal phrases, and the identification string composed of the character extraction of the sorted polluting metal phrases is set as the area identification string, and the area identification string is sent to the display response unit. After receiving the area identification string, the display response unit immediately displays the name of the corresponding area identification string on the high-pollution area and the low-pollution area, which helps to intuitively understand the pollution degree and content of each heavy metal in each high-pollution area and the low-pollution area, and can more comprehensively and meticulously reflect the pollution status, providing more reliable data support for pollution control;

[0052] In the embodiment of the present invention, for example, when g=1, it indicates the concentration of lead metal, when g=2, it indicates the concentration of mercury metal, and so on; the concentration of each heavy metal can be obtained by calculating the content of each metal element by using the quantitative relationship between the intensity of the spectral line and the content of the metal element (such as the Lamper-Beer law);

[0053] When a standard signal is generated, the pollution diffusion analysis unit is used to respond to the standard signal and conduct feedback analysis on the regional pollution diffusion risk assessment of the heavy metal pollution area, so as to intuitively understand the heavy metal pollution diffusion risk situation in the target soil area, so as to rationally remediate the heavy metal pollution in the target soil area. The specific regional pollution diffusion risk assessment feedback analysis process is as follows:

[0054] The area corresponding to the heavy metal pollution area of ​​the target soil area within the monitoring period is obtained, and it is set as the initial pollution area. The pollution area of ​​the target soil area is collected every t1 time period, and the collection is n times, where t1 is greater than zero and n is a natural number greater than 3. At the same time, the value obtained by subtracting the initial pollution area from the pollution area of ​​the collected target soil area is set as the pollution diffusion coefficient. The number of pollution diffusion coefficients greater than the preset pollution diffusion coefficient threshold is obtained and set as the diffusion trend index, and the diffusion trend index is discriminated:

[0055] If the diffusion trend index is less than the preset diffusion trend index threshold, a stable signal is generated and sent to the display response unit. After receiving the stable signal, the display response unit immediately performs a preset early warning operation corresponding to the stable signal to understand the diffusion of heavy metal pollution in the target soil area;

[0056] If the diffusion trend index is greater than or equal to a preset diffusion trend index threshold, a diffusion signal is generated;

[0057] When generating a diffusion signal:

[0058] The total duration corresponding to the collection of the pollution area of ​​the target soil area n times is obtained, and it is set as the diffusion assessment duration. The change value of the pollution area of ​​the target soil area within the diffusion assessment duration is obtained, and it is set as the pollution area floating value. The ratio between the pollution area floating value and the diffusion assessment duration is set as the diffusion impact ratio, and the diffusion impact ratio is discriminated:

[0059] If the diffusion impact ratio is greater than the maximum value in the preset diffusion impact ratio range, it is determined to be a level 1 risk;

[0060] If the diffusion impact ratio falls within the preset diffusion impact ratio range, it is determined to be a level 2 risk;

[0061] If the diffusion impact ratio is less than the minimum value in the preset diffusion impact ratio interval, it is determined to be a third-level risk, wherein the soil pollution diffusion risks corresponding to the first-level risk, the second-level risk and the third-level risk decrease in turn, and the first-level risk, the second-level risk and the third-level risk are set as the diffusion assessment level KS, KS=1, 2, 3, that is, the diffusion assessment level KS=1 indicates a first-level risk, the diffusion assessment level KS=2 indicates a second-level risk, and the diffusion assessment level KS=3 indicates a third-level risk. The diffusion assessment level KS is sent to the display response unit. After receiving the diffusion assessment level KS, the display response unit immediately collects the preset warning text corresponding to the diffusion assessment level KS, so as to intuitively understand the heavy metal pollution diffusion risk situation in the target soil area, so as to rationally remediate the heavy metal pollution in the target soil area.

[0062] Embodiment three:

[0063] A real-time soil pollution detection and analysis method based on spectral analysis comprises the following steps:

[0064] Step 1: retrieve the spectral characteristic image of the target soil area to conduct regional pollution division feedback analysis, obtain the heavy metal pollution concentration and pollution hazard coefficient, and obtain the high pollution area and low pollution area based on the comparison of heavy metal pollution concentration;

[0065] Step 2: Based on the pollution hazard coefficient analysis, the local pollution signal or the overall pollution signal is output and fed back;

[0066] Step 3: retrieve the sample parameters of the soil sample in the target soil area to perform regional pollution matching verification analysis, perform discriminant analysis on the obtained pollution matching deviation value, and output the obtained standard signal or deviation signal as feedback;

[0067] Step 4: Perform regional pollution identification processing and analysis on the hyperspectral data based on the information progressive method to obtain the regional identification string;

[0068] Step 5: Based on the information progressive method, the obtained heavy metal pollution area is subjected to regional pollution diffusion risk assessment feedback analysis, and the obtained diffusion trend index is subjected to discrimination processing. If a stable signal is obtained, feedback is output; if a diffusion signal is obtained, step 6 is performed;

[0069] Step 6: Based on the diffusion evaluation level acquisition analysis under the information feedback method, the obtained diffusion influence ratio is discriminated and processed to obtain the diffusion evaluation level KS;

[0070] In summary, the present invention analyzes from two points of view: UAV hyperspectral technology and sample collection and detection technology. That is, regional pollution division feedback analysis is performed on spectral feature images to determine whether there is a heavy metal pollution area and the degree of pollution in the target soil area, and regional pollution matching verification analysis is performed on sample parameters, so as to verify and feedback the UAV hyperspectral detection through sample experimental detection, and at the same time, the consistency of the two detections can be intuitively understood through the information feedback display method to ensure the availability of the detection results;

[0071] Analyzing from the two points of pollution identification processing and pollution diffusion, that is, conducting regional pollution identification processing and analysis on the pre-collected hyperspectral data, can help to intuitively understand the degree and content of heavy metal pollution in each high-pollution area and low-pollution area, and can reflect the pollution situation more comprehensively and meticulously, providing more reliable data support for pollution control. Regional pollution diffusion risk assessment feedback analysis is conducted on heavy metal polluted areas, so as to intuitively understand the risk of heavy metal pollution diffusion in the target soil area, so as to rationally remediate and manage the heavy metal pollution in the target soil area.

[0072] The threshold is set to facilitate comparison. The threshold depends on the amount of sample data and the number of bases set by technicians in this field for each set of sample data. It does not affect the proportional relationship between the parameter and the quantized value.

[0073] The size of the coefficient is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the coefficient depends on the amount of sample data and the preliminary setting of the corresponding operating coefficient for each set of sample data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0074] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A real-time soil pollution detection and analysis system based on spectral analysis, characterized in that: It includes a soil pollution detection platform, a soil database, a regional pollution division unit, a sample verification analysis unit, a regional identification analysis unit, a pollution diffusion analysis unit, and a display response unit; The soil pollution detection platform is used to retrieve the spectral characteristic image of the target soil area from the soil database and send the spectral characteristic image to the regional pollution division unit; The regional pollution division unit is used to perform regional pollution division feedback analysis on the received spectral feature image, judge the obtained heavy metal pollution concentration to obtain high pollution areas and low pollution areas, and discriminate the obtained pollution hazard coefficient to obtain local pollution signals or overall pollution signals; The sample checking and analysis unit is used to retrieve the sample parameters of the soil samples in the target soil area, and perform regional pollution matching checking and analysis on the sample parameters, and perform discriminant analysis on the obtained pollution matching deviation values ​​to obtain a standard signal or a deviation signal; The regional identification analysis unit is used to respond to the standard signal and simultaneously perform regional pollution identification processing and analysis on the pre-collected hyperspectral data to obtain a regional identification string; The pollution diffusion analysis unit is used to respond to standard signals and conduct feedback analysis on regional pollution diffusion risk assessment of heavy metal polluted areas to obtain the diffusion assessment grade KS.

2. According to claim 1, a soil pollution real-time detection and analysis system based on spectral analysis is characterized in that: The regional pollution division feedback analysis process is as follows: Set a monitoring period, obtain the spectral characteristic image of the target soil area within the monitoring period through the UAV hyperspectral technology, and preprocess the collected spectral characteristic image, including noise removal, atmospheric correction, and geometric correction; Retrieving a heavy metal pollution identification model from a soil database, obtaining a heavy metal pollution area in a target soil area based on a preprocessed spectral feature image and the heavy metal pollution identification model, obtaining a heavy metal pollution concentration in the heavy metal pollution area, performing judgment processing on the heavy metal pollution concentration, setting an area corresponding to a heavy metal pollution concentration greater than or equal to a preset heavy metal pollution concentration threshold as a high pollution area, and setting an area corresponding to a heavy metal pollution concentration less than a preset heavy metal pollution concentration threshold as a low pollution area; The ratio of the area corresponding to the heavy metal pollution area to the total area corresponding to the target soil area is set as the pollution hazard coefficient, and the pollution hazard coefficient is discriminated and processed to obtain a local pollution signal or an overall pollution signal.

3. The real-time soil pollution detection and analysis system based on spectral analysis according to claim 1 is characterized in that: The regional pollution matching verification and analysis process is as follows: Obtaining sample parameters of soil samples in the target soil area, the sample parameters including sampling point coordinates and sample hyperspectral data; Based on the sample parameters, the coordinates of high-pollution points and low-pollution points in the target soil area are obtained, and the high-pollution area and low-pollution area of ​​the target soil area are obtained at the same time. The high-pollution point coordinates and the low-pollution point coordinates are matched and analyzed with the high-pollution area and the low-pollution area to obtain the pollution matching deviation value of the target soil area. The pollution matching deviation value represents the sum of the number of high-pollution point coordinates that do not belong to the high-pollution area and the number of low-pollution point coordinates that do not belong to the low-pollution area. The pollution matching deviation value is discriminated and analyzed to obtain a standard signal or a deviation signal.

4. The real-time soil pollution detection and analysis system based on spectral analysis according to claim 1 is characterized in that: The regional pollution identification processing and analysis process is as follows: The hyperspectral data of each high-pollution area and low-pollution area in the target soil area are obtained. The hyperspectral data represent a hyperspectral characteristic image. The hyperspectral characteristic image is compared and analyzed with the standard spectral library, that is, the heavy metal information of each high-pollution area and low-pollution area is obtained. The heavy metal information includes lead metal concentration and mercury metal concentration. The parameter in the heavy metal information is set to g, where g is a natural number greater than zero. The numerical value corresponding to each parameter in the heavy metal information is obtained and set as the metal content value Jg. The metal content value Jg is discriminated and processed, and the metal name corresponding to the metal content value Jg greater than or equal to the preset metal content value threshold is set as the polluted metal name.

5. The real-time soil pollution detection and analysis system based on spectral analysis according to claim 4 is characterized in that: The metal content value corresponding to each polluted metal name is obtained, and the combination of the polluted metal name and the corresponding metal content value is set as a polluted metal phrase, and based on the size relationship of the metal content values ​​corresponding to each polluted metal name, the polluted metal phrases are sorted in descending order, and characters are extracted from the sorted polluted metal phrases, and the identification string composed of the character extraction of the sorted polluted metal phrases is set as the area identification string.

6. The real-time soil pollution detection and analysis system based on spectral analysis according to claim 1 is characterized in that: The feedback analysis process of regional pollution diffusion risk assessment is as follows: The area corresponding to the heavy metal pollution area of ​​the target soil area within the monitoring period is obtained, and it is set as the initial pollution area. The pollution area of ​​the target soil area is collected every t1 time period, and the collection is n times, where t1 is greater than zero and n is a natural number greater than 3. At the same time, the value obtained by subtracting the initial pollution area from the pollution area of ​​the collected target soil area is set as the pollution diffusion coefficient. The number of pollution diffusion coefficients greater than the preset pollution diffusion coefficient threshold is obtained and set as the diffusion trend index. The diffusion trend index is discriminated: if the diffusion trend index is less than the preset diffusion trend index threshold, a stable signal is generated; if the diffusion trend index is greater than or equal to the preset diffusion trend index threshold, a diffusion signal is generated.

7. The real-time soil pollution detection and analysis system based on spectral analysis according to claim 6 is characterized in that: When a diffusion signal is generated: the total duration corresponding to the collection of the pollution area of ​​the target soil area n times is obtained, and it is set as the diffusion assessment duration; the change value of the pollution area of ​​the target soil area within the diffusion assessment duration is obtained, and it is set as the pollution area floating value; the ratio between the pollution area floating value and the diffusion assessment duration is set as the diffusion impact ratio; the diffusion impact ratio is discriminated and processed to obtain first-level risk, second-level risk and third-level risk; the first-level risk, second-level risk and third-level risk are set as diffusion assessment levels KS, KS=1, 2, 3.

8. A method for real-time detection and analysis of soil pollution based on spectral analysis, the method being applicable to a real-time detection and analysis system for soil pollution based on spectral analysis as claimed in any one of claims 1 to 7, characterized in that: The following steps are involved: Step 1: retrieve the spectral characteristic image of the target soil area to conduct regional pollution division feedback analysis, obtain the heavy metal pollution concentration and pollution hazard coefficient, and obtain the high pollution area and low pollution area based on the comparison of heavy metal pollution concentration; Step 2: Based on the pollution hazard coefficient analysis, the local pollution signal or the overall pollution signal is output and fed back; Step 3: retrieve the sample parameters of the soil sample in the target soil area to perform regional pollution matching verification analysis, perform discriminant analysis on the obtained pollution matching deviation value, and output the obtained standard signal or deviation signal as feedback; Step 4: Perform regional pollution identification processing and analysis on the hyperspectral data based on the information progressive method to obtain the regional identification string; Step 5: Based on the information progressive method, the obtained heavy metal pollution area is subjected to regional pollution diffusion risk assessment feedback analysis, and the obtained diffusion trend index is subjected to discrimination processing. If a stable signal is obtained, feedback is output; if a diffusion signal is obtained, step 6 is performed; Step 6: Based on the diffusion evaluation level acquisition analysis under the information feedback method, the obtained diffusion influence ratio is discriminated and processed to obtain the diffusion evaluation level KS.

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