A soil environment environmental protection detection data management processing system and method

Abstract

The application discloses a kind of soil environment environmental protection detection data management processing method and system, wherein the method comprises the following steps: S1, the first soil monitoring area corresponding first soil area attribute data is obtained, wherein the first soil area attribute data at least contains pollution attribute, geographical position and land use mode;S2, according to first soil area attribute data to determine the first important level corresponding to the first soil monitoring area;S3, according to the first important level corresponding to the first soil monitoring area to allocate resources.The application scheme uses multi-dimensional soil attribute parameters to determine the importance of the soil area, which is more accurate and more in line with the actual situation, thereby reducing the value loss and negative impact caused by the higher importance of the soil area being delayed resource allocation.The application scheme can be widely applied in the field of soil environmental protection detection monitoring.

Description

TECHNICAL FIELD

[0001] The present application relates to environmental protection data analysis and processing technology, in particular to a soil environmental protection detection data management and processing system and method. BACKGROUND

[0002] Currently, for known / suspected contaminated industrial land or ecologically important areas, regular or irregular monitoring is carried out as needed to monitor changes in soil pollution, so as to update the environmental risk assessment conclusion in a timely manner and adjust the treatment measures. In view of this, there may be multiple different soil areas that need to perform corresponding monitoring work in the same time period, and the related equipment resources for soil pollution monitoring are limited, so when allocating resources, the soil areas need to be sorted and then the resources are allocated in sequence. However, the current sorting basis for soil areas mainly relies on the historical experience of workers or single-dimensional consideration factors, resulting in low processing accuracy of resource allocation priority, causing soil areas with high actual importance to be delayed in resource allocation, resulting in greater loss and negative impact. SUMMARY

[0003] The present application aims to at least solve one of the technical problems existing in the prior art. To this end, the present application provides a soil environmental protection detection data management and processing system and method, which can improve the accuracy of resource allocation priority of soil monitoring areas to avoid causing excessive value loss and reducing negative impact.

[0004] In a first aspect, the embodiments of the present application provide a soil environmental protection detection data management and processing method, which comprises the following steps:

[0005] S1, acquiring first soil region attribute data corresponding to a first soil monitoring area, wherein the first soil region attribute data at least includes pollution attribute, geographical position and land use mode;

[0006] S2, determining a first importance level corresponding to the first soil monitoring area according to the first soil region attribute data;

[0007] S3, resource allocation according to the first importance level corresponding to the first soil monitoring area.

[0008] In some embodiments, the step S3 specifically comprises the following steps:

[0009] S301, using the first pollution diffusion estimated area corresponding to the first soil monitoring area to allocate resources to the first soil monitoring areas with the same first importance level.

[0010] In some embodiments, the step S301 specifically comprises the following steps:

[0011] S3011, in response to the monitoring trigger instruction, obtaining an initial pollution diffusion estimation area corresponding to the first soil monitoring area;

[0012] S3012, after obtaining the influence factor characteristic value, determining a first adjustment coefficient according to the influence factor characteristic value;

[0013] S3013, adjusting the initial pollution diffusion estimation area according to the first adjustment coefficient to obtain a first pollution diffusion estimation area;

[0014] S3014, using the first pollution diffusion estimation area to allocate resources to the first soil monitoring area with the same first important level.

[0015] In some embodiments, the influence factor characteristic value includes a first precipitation and a first water evaporation, wherein the first precipitation refers to the total precipitation of the first soil monitoring area within a monitoring time interval, and the first water evaporation refers to the total water evaporation of the first soil monitoring area within the monitoring time interval.

[0016] In some embodiments, the influence factor characteristic value further includes a first vegetation increase rate, which is obtained by the following steps:

[0017] Obtaining a first soil area image and a second soil area image, wherein the first soil area image refers to an initial shooting image of the first soil monitoring area, and the second soil area image is a shooting image obtained by triggering the first shooting device to shoot the first soil monitoring area in response to the monitoring trigger instruction;

[0018] The first vegetation target object in the first soil area image and the second vegetation target object in the second soil area image are identified by image recognition technology;

[0019] The first vegetation increase rate is determined according to the first vegetation target object and the second vegetation target object.

[0020] In some embodiments, the step of determining the first vegetation increase rate according to the first vegetation target object and the second vegetation target object specifically includes:

[0021] Determining the current vegetation coverage area according to the pixel proportion of the second vegetation target object in the second soil area image;

[0022] Determining the initial vegetation coverage area according to the pixel proportion of the first vegetation target object in the first soil area image;

[0023] Determining the first vegetation increase rate according to the current vegetation coverage area and the initial vegetation coverage area.

[0024] In some embodiments, the step S3014 specifically includes the following steps:

[0025] S30141, when the first vegetation increase rate is less than the preset threshold, determining the total number of device resources corresponding to the first soil monitoring area according to the initial number of device resources corresponding to the first soil monitoring area and the first number of device resources corresponding to the first pollution diffusion estimation area;

[0026] S30142, when the first vegetation increase rate is greater than or equal to the preset threshold, adjusting the initial number of device resources to obtain a second number of device resources, and determining the total number of device resources according to the second number of device resources and the first number of device resources;

[0027] S30143, resource allocation is performed on the first soil monitoring area with the same first importance level according to the total number of device resources.

[0028] In some embodiments, the step S30143 specifically includes the following steps:

[0029] S301431, summing the total number of device resources corresponding to the first soil monitoring area with the same first importance level to obtain a first summation result;

[0030] S301432, when the first summation result is less than or equal to the number of idle device resources, resource allocation is performed on the first soil monitoring area with the same first importance level according to the total number of device resources corresponding to the first soil monitoring area;

[0031] S301433, when the first summation result is greater than the number of idle device resources, resource allocation is performed on the first soil monitoring area with the same first importance level in descending order according to the total number of device resources corresponding to the first soil monitoring area.

[0032] In some embodiments, the step S3012 specifically includes the following steps:

[0033] S30121, after obtaining a plurality of influence factor characteristic values, the plurality of influence factor characteristic values are constructed into a first feature data input matrix;

[0034] S30122, after inputting the first feature data input matrix into the first machine learning model for processing, outputting a first adjustment coefficient.

[0035] In a second aspect, the embodiments of the present application provide a soil environment environmental protection detection data management processing system, which comprises:

[0036] A first soil detection monitoring device is used to obtain soil detection monitoring data by detecting and monitoring a soil monitoring area.

[0037] The background processing system comprises at least one processor for loading a program to execute a soil environment environmental protection detection data management processing method provided by the first aspect.

[0038] The first soil detection monitoring device is in communication connection with the background processing system.

[0039] The present application can achieve one of the following technical effects: The present application obtains soil region attribute data corresponding to the soil monitoring region, wherein the soil region attribute data includes the pollution attribute corresponding to the soil monitoring region, the geographical position and the land use mode, thereby determining the important level corresponding thereto, and taking the important level as the resource allocation priority of the soil region, so as to sequentially allocate the corresponding resources to the multiple soil monitoring regions. It can be seen that the present application uses multi-dimensional soil attribute parameters to determine the importance of the soil region, which is more accurate and more in line with the actual situation, thereby reducing the value loss and negative impact caused by the delay of resource allocation of the soil region with high importance. BRIEF DESCRIPTION OF DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced.

[0041] Figure 1 A soil environment environmental protection detection data management processing method is provided for the embodiment of the present application.

[0042] Figure 2 A simple schematic diagram of the first soil monitoring region V1 and the first pollution diffusion estimation region V2 in the embodiment of the present application is provided.

[0043] Figure 3 A structural block diagram of a soil environment environmental protection detection data management processing system is provided for the embodiment of the present application. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical scheme and advantages of the present application more clear, the technical scheme of the present application will be described in detail below with reference to the drawings in the embodiment of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0045] In order to realize the soil environment protection, it is necessary to monitor the pollution situation of the soil environment, so as to timely reveal the soil pollution situation and provide a scientific basis for formulating targeted control measures. Conventionally, for the known / suspected contaminated or key concerned soil area, it is necessary to regularly or irregularly monitor the pollution situation again, so as to timely adjust the control measures. In view of this, for the professional monitoring institution, there may be the case that multiple different soil areas need to perform corresponding monitoring work in the same time period, and the equipment resources required for soil pollution monitoring are limited, so it is necessary to prioritize the soil areas. At present, the sorting of the soil areas mainly depends on the historical experience of the staff or a single dimension of the consideration factor to determine, but it is found that the accuracy is low, and the soil area with high actual importance is easily configured with low priority, causing the soil area with high actual importance to be delayed in resource allocation, that is, the monitoring work is delayed, which may easily cause greater value loss and / or negative impact. It can be seen that designing a soil environment protection detection data management processing scheme capable of improving the priority configuration accuracy is one of the technical problems to be solved at present.

[0046] Reference Figure 1 The present application provides a soil environment protection detection data management processing method, which comprises the following steps.

[0047] S1, acquiring first soil monitoring area corresponding first soil area attribute data, wherein the first soil area attribute data at least contains pollution attribute, geographical position and land use mode.

[0048] Specifically, in the present embodiment, the pollution attribute at least contains the pollutant type and the pollutant concentration, wherein different types of pollutants (such as heavy metals, organic compounds, radioactive substances, etc.) have different risk degrees to the environment and human health, so when the risk degree of the pollutant type contained in the soil is higher, the corresponding monitoring importance level is higher; similarly, when the concentration of the pollutant in the soil is higher, the risk degree caused by it is higher, at this time, the corresponding monitoring importance level is higher, that is, the pollution attribute in the soil will have an associated influence on its monitoring importance level.

[0049] For the geographical position, it specifically includes a geographical distance, which mainly refers to the geographical distance between the first soil monitoring area and an important use area (such as a water source area, a residential area, an agricultural land, etc.), and the smaller the geographical distance is, the more likely the first soil monitoring area is to have a negative impact on the important use area and / or the greater the degree of negative impact is, so when the geographical distance is smaller, the monitoring importance level corresponding to the first soil monitoring area is higher (because monitoring work needs to be performed faster and prioritized to adjust the treatment measures as soon as possible to solve the pollution problem as soon as possible), that is, the geographical distance has an associated impact on the monitoring importance level. Further, when there are multiple important use areas near the first soil monitoring area, the geographical distance can be determined by obtaining first geographical sub-distances between the first soil monitoring area and the multiple important use areas, and then calculating a distance average of the multiple first geographical sub-distances as the geographical distance. Under this premise, considering that under the same geographical distance, the more the number of important use areas near the first soil monitoring area is, the more the first soil monitoring area will have an impact on the important use areas, that is, the greater the degree of impact on the important use areas is, so in this embodiment, the geographical position can also include the number of important use areas.

[0050] For the land use mode, it mainly refers to the land use mode type of the first soil monitoring area, for example, if it is a region to be developed for business, the monitoring importance level is higher (because monitoring work needs to be performed faster and prioritized to adjust the treatment measures as soon as possible to solve the pollution problem as soon as possible, avoiding the delay of the region development due to the delay of the monitoring work, which will cause more value loss), on the contrary, if the first soil monitoring area is a region such as wasteland that has no business development plan within a preset time period, the monitoring importance level can be lower, so the land use mode of the soil area has an associated impact on the monitoring importance level. As can be seen, the three dimensions of parameters are used to comprehensively determine the monitoring importance level of the soil area, which can greatly improve the accuracy of the determination of the importance level, that is, the accuracy of the resource allocation priority.

[0051] In addition, for the first soil monitoring area, a current pollution coverage area (i.e., a soil area with pollutants) can be determined by parameters obtained through various detection, monitoring, analysis and processing of soil, and then the first soil monitoring area is determined according to the current pollution coverage area. The various detection, analysis and processing means and the determination, analysis and processing means of the first soil monitoring area can be realized by using existing technical means, which will not be described in detail here.

[0052] S2, determining a first importance level corresponding to the first soil monitoring area according to the first soil region attribute data. Specifically, for step S2, it can include the following two implementation manners.

[0053] Manner ①, the step S2 includes the following steps: A1, querying the highest similarity historical soil region attribute data from the first historical database according to the first soil region attribute data; A2, obtaining the corresponding historical importance level from the mapping relationship between the historical soil region attribute data and the historical importance level according to the highest similarity historical soil region attribute data obtained by querying, and the corresponding historical importance level obtained at this time is the required first importance level.

[0054] It can be seen that for the above-mentioned manner ①, it is necessary to construct the mapping relationship between the historical soil monitoring area corresponding historical soil region attribute data and the corresponding historical importance level, so that when this mapping relationship is stored in the database, the data interface of this database is directly called for subsequent actual operation query, and the corresponding data matching call can be obtained.

[0055] Manner ②, the step S2 includes the following steps: B1, constructing the second feature data input matrix from the first soil region attribute data; B2, inputting the second feature data input matrix into the second machine learning model for processing, and outputting the corresponding first importance level.

[0056] It can be seen that for the above-mentioned manner ②, it is necessary to use the historical soil region attribute data as the first training input data and the historical importance level as the first training output data, and then train the second machine learning model with the first training input and output data until the training end condition is met, so that in actual use, the actual soil region attribute data corresponding to the current soil monitoring area can be used as the data input matrix and input into the trained second machine learning model for processing to obtain the corresponding first importance level.

[0057] For the above-mentioned manners ① and ②, they can be selected and set according to actual conditions, which are not specially limited here.

[0058] S3, resource allocation according to the first importance level corresponding to the first soil monitoring area.

[0059] Specifically, when multiple soil monitoring areas need to be monitored again at the same time period to update the current pollution situation of the soil monitoring area in real time, the first soil monitoring area corresponding to the first importance level can be sorted in order, wherein the higher the first importance level, the higher the resource allocation priority, that is, the earlier the monitoring work is arranged, that is, the above first importance level is mainly used to determine the order priority in resource allocation. The value used to represent the first importance level can be smaller, indicating a higher level, or larger, indicating a higher level, which is selected and set according to actual needs, which is not specially limited here.

[0060] It can be seen that the above-mentioned determination method of the importance level of the soil monitoring area has multiple influencing factor dimensions, so the accuracy of the level determination is better, and it is more consistent with the actual situation, thereby greatly reducing the loss of value and negative impact.

[0061] In some embodiments, multiple soil monitoring areas need to be monitored again at the same time period, and on this basis, there are at least two first soil monitoring areas with the same first importance level. Considering that the larger the area to be detected and monitored, the more detection and monitoring sampling points will be increased, resulting in more detection and monitoring equipment resources required, and the time required for detection and monitoring processing work will also be longer, and according to historical experience data statistics, the longer the detection and monitoring processing work time, the more detection and monitoring sampling points involved, the more unstable factors affecting work errors and / or delays will be more likely to occur and / or occur more frequently, that is, the larger the area of the soil area to be detected and monitored, the more likely it is to delay completion, even with a relatively large delay. In view of this, the resource allocation waiting time of these areas to be detected and monitored (that is, the area requiring a large number of detection and monitoring equipment resources) should be minimized, that is, when the number of idle equipment resources is not enough to allocate resources to all soil monitoring areas to be processed, in order to minimize the resource waiting time of the above-mentioned area, the number of detection and monitoring equipment resources corresponding to the current detection and monitoring area of the soil monitoring area corresponding to the detection and monitoring area to be detected and monitored is sorted in order from large to small. Therefore, in this embodiment, the step S3 specifically comprises the following steps:

[0062] S301, using the first pollution diffusion estimation area corresponding to the first soil monitoring area to allocate resources to the first soil monitoring area with the same first importance level.

[0063] Specifically, in order to predict the estimated area of pollution diffusion corresponding to any soil region, a two-dimensional dynamic pollutant diffusion model such as a finite volume two-dimensional steady-state diffusion model, a GIS interpolation diffusion model, etc. is generally used for estimation and calculation. When relevant data corresponding to the soil monitoring region is collected, such as the type, concentration, and characteristics of the soil (such as soil permeability, water content, porosity, vegetation coverage, etc.), the collected data is input into the corresponding model, and the estimated area of pollution diffusion corresponding to the soil region can be obtained. Different diffusion models require different input data, so the corresponding data required for collection can be determined according to the selected model. The use of these diffusion models to process input sampling data to obtain the corresponding estimated area of pollution diffusion is a prior art, which will not be described in detail here.

[0064] Then, the first equipment resource quantity corresponding to the first pollution diffusion estimated area is determined, and then the total equipment resource quantity required for the soil monitoring region is determined according to the first equipment resource quantity and the initial equipment resource quantity corresponding to the first soil monitoring region (which can be the actual equipment resource quantity used when initially detecting and monitoring the first soil monitoring region). That is, for step S301, it can be specifically: using the initial equipment resource quantity corresponding to the first soil monitoring region and the first equipment resource quantity corresponding to the area of the first pollution diffusion estimated area, to determine the total equipment resource quantity arranged for the first soil monitoring region when detecting and monitoring again, and according to the total equipment resource quantity corresponding to each first soil monitoring region, the resource allocation is performed for the first soil monitoring region with the same first important level. That is, when there are at least two first soil monitoring regions with the same first important level, the resource allocation is performed according to the total equipment resource quantity corresponding to the first soil monitoring region.

[0065] As shown in Figure 2 V1 represents the first soil monitoring region, and V2 represents the estimated pollution diffusion estimated area determined based on the relevant data corresponding to the first monitoring region combined with the model. The area of V2 can be used to obtain the required equipment resource quantity, and the total equipment resource quantity required for detecting and monitoring the soil region again can be estimated and determined according to the actual equipment resource quantity (i.e. the initial equipment resource quantity) corresponding to V1 and the first equipment resource quantity corresponding to the area of V2. When detecting and monitoring again, the pollution change of the current soil region can be understood in time according to the analysis and processing structure of the detection and monitoring data, so as to determine whether the management strategy needs to be adjusted or the corresponding management operation can be ended.

[0066] In some embodiments, since there is a monitoring time interval between the detection monitoring time point of the first soil monitoring area and the time point of re-detection monitoring, and during this interval, the pollution diffusion estimation area changes due to some environmental impact factors, therefore, when re-detection monitoring is needed, these impact factors need to be obtained, and the corresponding adjustment coefficient is determined according to the impact factors, so as to adjust the initial pollution diffusion estimation area. Therefore, the accuracy of the subsequent determined total number of equipment resources is higher. Therefore, step S301 specifically includes the following steps.

[0067] S3011, in response to the monitoring trigger instruction, obtaining the initial pollution diffusion estimation area corresponding to the first soil monitoring area. When the monitoring trigger instruction is received, it means that re-detection monitoring is needed, and then the monitoring time interval can be determined based on the time point and the initial detection monitoring time point of the first soil monitoring area.

[0068] S3012, after obtaining the impact factor characteristic value, determining the first adjustment coefficient according to the impact factor characteristic value.

[0069] In some embodiments, the step S3012 specifically includes the following steps.

[0070] S30121, after obtaining a plurality of impact factor characteristic values, the plurality of impact factor characteristic values are used to form a first feature data input matrix.

[0071] S30122, after inputting the first feature data input matrix into the first machine learning model for processing, outputting the first adjustment coefficient.

[0072] Specifically, the first machine learning model needs to be trained using training input data and training output data to obtain a trained first machine learning model. In this embodiment, historical impact factor characteristic values are used to form second training input data, and historical adjustment coefficients are used as second training output data. The historical adjustment coefficient is determined according to the ratio between the historical initial pollution diffusion estimation area (i.e. historical initial pollution diffusion estimation area) and the historical actual pollution diffusion estimation area actually detected during re-detection monitoring. Further, the historical adjustment coefficient can be directly the ratio, or the ratio can be further adjusted to obtain the final historical adjustment coefficient. This can be selected according to the actual situation, which is not specifically limited here. It can be seen that, in actual operation, the trained first machine learning model is used to process the input actual impact factor characteristic value to obtain the corresponding first adjustment coefficient, which can improve the processing efficiency and the accuracy of the output adjustment coefficient.

[0073] S3013, adjust the initial pollution diffusion estimation area according to the first adjustment coefficient to obtain a first pollution diffusion estimation area.

[0074] S3014, use the first pollution diffusion estimation area to allocate resources to the first soil monitoring area with the same first important level.

[0075] In some embodiments, water is the main physical carrier of pollutants in soil, so the water content of soil will have a significant impact on the diffusion area of pollutants, and the water content of soil is affected by precipitation and soil water evaporation, so in this embodiment, the characteristic value of the influencing factor mainly includes the first precipitation and the first water evaporation. The first precipitation refers to the total precipitation of the first soil monitoring area in the monitoring time interval, that is, the total precipitation experienced by the first soil monitoring area in the monitoring time interval is taken as the first precipitation; the first water evaporation refers to the total water evaporation of the first soil monitoring area in the monitoring time interval. The specific calculation and determination method of the above-mentioned total precipitation and total water evaporation can be calculated and determined by using the existing model, which will not be described in detail here.

[0076] In some embodiments, in the monitoring time interval, there may be new growth of vegetation and / or growth of vegetation in the first pollution diffusion estimation area, which will cause the coverage of vegetation in the area to be higher, and when the coverage is higher, it will increase the water absorption and retention capacity, thus reducing runoff and shortening the moving distance, that is, vegetation can slow down the diffusion area of pollutants, so when the vegetation addition rate of the first pollution diffusion estimation area is greater than 0, it means that the more vegetation, the greater the degree of slowing down the diffusion area of pollutants, that is, this vegetation addition rate parameter will inevitably affect the area of the pollution diffusion estimation area. Therefore, in order to further improve the determination accuracy of the first adjustment coefficient, the vegetation addition rate is introduced as an influencing factor in the first feature data input matrix.

[0077] From the above, the characteristic value of the influencing factor also includes the first vegetation addition rate, and the first vegetation addition rate is obtained by the following steps.

[0078] C1, obtain a first soil area image and a second soil area image, wherein the first soil area image refers to an initial shooting image of the first soil monitoring area, and the second soil area image is a shooting image obtained by triggering the first shooting device to shoot the first soil monitoring area in response to a monitoring trigger instruction.

[0079] Specifically, since the first pollution diffusion estimation area is an area extended outward from the first soil monitoring area, the error between the vegetation addition rate of the first soil monitoring area and the vegetation addition rate corresponding to the first pollution diffusion estimation area is so small that it can be completely ignored, so the vegetation addition rate of the first soil monitoring area is taken as the vegetation addition rate corresponding to the first pollution diffusion estimation area. As for the change of the vegetation in the first soil monitoring area, it can be photographed at an initial detection monitoring time point of the first soil monitoring area to obtain an initial photographed image, and when a monitoring triggering instruction is received, it means that the detection monitoring work needs to be performed again, and a second soil area image is obtained after the first photographing device photographs the first soil monitoring area. The photographing device, the configured photographing parameters, the photographing angle, and the height of the photographing device used for the photographed images before and after should be the same to ensure that the first soil monitoring area is photographed into the picture during the first and second photographing, and the pixel degree and other parameters are the same, so as to ensure that the vegetation target objects in the first and second soil area images are not missed and the accuracy of identification is ensured.

[0080] C2, the first vegetation target object in the first soil area image and the second vegetation target object in the second soil area image are identified by image recognition technology.

[0081] C3, the first vegetation addition rate is determined according to the first vegetation target object and the second vegetation target object.

[0082] Specifically, the first vegetation addition rate is mainly determined by the vegetation addition amount, and the vegetation addition amount can be the number of additions or other units of additions, which can be selected and set as needed.

[0083] In some embodiments, since the existing vegetation grows larger while the vegetation is added, and the growth of the vegetation also slows down the diffusion area of the pollutants, in order to reflect that the vegetation addition amount considers both the number addition and the volume addition, the change of the coverage area of the vegetation in the first soil monitoring area is used to determine the first vegetation addition rate. Therefore, the step C3 of determining the first vegetation addition rate according to the first vegetation target object and the second vegetation target object specifically includes:

[0084] C301, the current vegetation coverage area is determined according to the pixel proportion of the second vegetation target object in the second soil area image.

[0085] C302. Determine the initial vegetation cover area based on the pixel ratio of the first vegetation target object in the first soil area image. Specifically, since the actual area of ​​the first soil monitoring area is known, the actual vegetation cover area can be determined by the pixel ratio of the vegetation target object and the first soil monitoring area.

[0086] C303. Determine the first vegetation growth rate based on the current vegetation coverage area a and the initial vegetation coverage area b.

[0087] Specifically, the determination steps for the first vegetation growth rate include: C3031, calculating the first difference between the current vegetation coverage area *a* and the initial vegetation coverage area *b*; C3032, determining the first vegetation growth rate based on the ratio of the first difference to the initial vegetation coverage area *b*. Further, the calculation formula for the first vegetation growth rate *r* can be: *r* = ((ab) ÷ *b*) × 100%. This method can improve the accuracy of the vegetation growth rate calculation.

[0088] In some embodiments, step S3014 specifically includes the following steps.

[0089] S30141. When the first vegetation growth rate is less than a preset threshold, the total number of equipment resources is determined based on the initial number of equipment resources corresponding to the first soil monitoring area and the first number of equipment resources corresponding to the first pollution diffusion estimated area.

[0090] Specifically, because vegetation can affect pollution diffusion, it is generally not removed during soil pollution detection and monitoring. Therefore, for the first soil monitoring area, if the initial vegetation growth rate is very small, equivalent to no new vegetation, the required number of equipment resources for this first soil monitoring area remains unchanged, still being the number of equipment resources actually used during the initial detection and monitoring work, i.e., the initial equipment resource quantity. Based on this, when detection and monitoring work needs to be performed again, the total number of equipment resources includes the initial equipment resource quantity and the first equipment resource quantity corresponding to the first estimated pollution diffusion area.

[0091] S30142. When the first vegetation growth rate is greater than or equal to the preset threshold, the initial number of equipment resources is adjusted to obtain the second number of equipment resources. The total number of equipment resources is determined based on the second number of equipment resources and the first number of equipment resources.

[0092] Specifically, when the first vegetation increase rate is greater than or equal to a preset threshold, it indicates that the newly added vegetation on the first soil monitoring area is relatively obvious and covers the soil, at this time, the initial device resource quantity can be adjusted according to the first vegetation increase rate. Wherein, the greater the vegetation increase rate, the initial device resource quantity will be reduced, therefore, the mapping relationship between different vegetation increase rates and different second adjustment coefficients can be obtained by using historical data, then the corresponding historical second adjustment coefficient is obtained from the above mapping relationship according to the first vegetation increase rate, and then the initial device resource quantity is adjusted according to the second adjustment coefficient to obtain the second device resource quantity.

[0093] Alternatively, the step of adjusting the initial device resource quantity to obtain the second device resource quantity can specifically include:

[0094] D1, determining the coverage area of the newly added vegetation and the position of the newly added vegetation in the first soil monitoring area according to the first vegetation target object and the second vegetation target object.

[0095] D2, determining the device resource reduction amount according to the coverage area of the newly added vegetation and the position of the newly added vegetation in the first soil monitoring area.

[0096] D3, adjusting the initial device resource quantity according to the device resource reduction amount to obtain the second device resource quantity.

[0097] Specifically, since the pixel proportion and coordinate position of the first vegetation target object and the second vegetation target object in the soil area image, the coordinate position can be converted to the position in the actual soil area through mapping or coordinate conversion, so that the coverage area of the newly added vegetation and the position of the newly added vegetation in the first soil monitoring area can be obtained after comparison and identification. According to the coverage area and position of the newly added vegetation, it can be queried from the historical data of initial detection monitoring execution operation whether the coverage area of the newly added vegetation at the position overlaps with the detection monitoring sampling point at that time. If overlapping, the detection monitoring sampling point corresponding to the overlapping part needs to be removed, and the number of removed detection monitoring sampling points corresponds to the reduced device resource quantity, therefore, in this embodiment, the device resource reduction amount can be determined according to the coverage area of the newly added vegetation and the position of the newly added vegetation in the first soil monitoring area, and then the initial device resource quantity can be adjusted according to the device resource reduction amount to obtain the second device resource quantity. It can be seen that the device resource quantity determined by this method has higher accuracy and is more in line with the actual situation.

[0098] S30143, resource allocation is performed on the first soil monitoring area with the same first important level according to the total number of device resources.

[0099] In some embodiments, the step S30143 specifically comprises the following steps:

[0100] S301431, summing the total number of device resources corresponding to the first soil monitoring areas with the same first importance level to obtain a first summation result.

[0101] S301432, when the first summation result is less than or equal to the number of idle device resources, resource allocation is performed according to the total number of device resources corresponding to the first soil monitoring areas with the same first importance level. At this time, resource conflict is avoided, and resource allocation can be performed simultaneously for the soil monitoring areas with the same first importance level.

[0102] S301433, when the first summation result is greater than the number of idle device resources, resource allocation is performed for the first soil monitoring areas with the same first importance level in descending order of the total number of device resources corresponding to the first soil monitoring areas. In this way, the resource allocation waiting time of the areas to be detected with large monitoring areas (i.e., areas that need to detect a large number of monitoring device resources) can be minimized, so as to avoid the detection and monitoring work of these areas exceeding the specified time node, or even being too long.

[0103] In some embodiments, for the characteristic value of the influencing factor, the effectiveness rate of the adopted treatment measure can also be included. After the first soil monitoring area is detected and monitored for the first time, the effectiveness rate of the adopted treatment measure can slow down the diffusion of pollutants to a certain extent, and there is a certain relationship between the effectiveness rate and the diffusion. The higher the effectiveness rate, the better the diffusion slowing effect. It can be seen that by introducing this dimension of influencing factor, the accuracy can be further improved.

[0104] Referring to Figure 3 The embodiment of the present application also provides a soil environmental protection detection data management processing system, which comprises:

[0105] The first soil detection and monitoring device is used to detect and monitor the soil monitoring area to obtain soil detection and monitoring data.

[0106] The background processing system comprises at least one processor and is used to load a program to perform the method steps of the above-mentioned method embodiments.

[0107] The first soil detection and monitoring device is in communication connection with the background processing system.

[0108] Since the background processing system in the system embodiment comprises at least one processor, and is used to load a program to perform the method steps of the above-mentioned method embodiments, the description and beneficial effects of the system embodiment are the same as those of the method embodiments, and therefore the description is not repeated here.

[0109] Further, an embodiment of the present application also provides a computer readable storage medium, which stores a computer program. The computer program is executed by a processor to implement steps of the above method embodiment.

[0110] For the processor mentioned in the above storage medium embodiment and system embodiment, the number thereof can be at least one, and the processor can execute at least one step of the above method embodiment. When the number is at least two, the at least two processors can be communicatively connected, which is not limited to wired or wireless communication connection, and the at least one processor can be communicatively connected with various smart terminal devices. In addition, the processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor.

[0111] Finally, it should be understood that the size of the serial number of each step in the above embodiment does not mean the execution order, and the execution order of each process should be determined according to its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiment of the present application.

[0112] Note that the above are only the preferred embodiments of the present application and the principles of the technology applied. Those skilled in the art will understand that the present application is not limited to the specific embodiments described herein, and those skilled in the art can make various obvious changes, readjustments and substitutions without departing from the scope of the present application. Therefore, although the present application has been described in detail through the above embodiments, the present application is not limited to the above embodiments, and can include more other equivalent embodiments without departing from the concept of the present application, and the scope of the present application is determined by the scope of the appended claims.

Claims

1. A method for managing and processing soil environmental monitoring data, characterized in that, The method includes the following steps: S1. Obtain the first soil regional attribute data corresponding to the first soil monitoring area, wherein the first soil regional attribute data includes at least pollution attributes, geographical location and land use pattern; S2. Determine the first importance level corresponding to the first soil monitoring area based on the first soil area attribute data; S3. Resource allocation is carried out according to the first importance level corresponding to the first soil monitoring area; step S3 specifically includes the following steps: S3011. In response to the monitoring trigger command, obtain the initial pollution diffusion estimate area corresponding to the first soil monitoring area; S3012. After obtaining the characteristic values ​​of the influencing factors, determine the first adjustment coefficient based on the characteristic values ​​of the influencing factors; wherein, the characteristic values ​​of the influencing factors include the first vegetation growth rate, which is obtained through the following steps: C1. Obtain a first soil area image and a second soil area image, wherein the first soil area image refers to the initial image of the first soil monitoring area, and the second soil area image is the image obtained after the first imaging device is triggered to capture the first soil monitoring area in response to the monitoring trigger command; C2. Identify the first vegetation target object in the first soil area image and the second vegetation target object in the second soil area image respectively through image recognition technology; C3. Determine the first vegetation growth rate based on the first vegetation target object and the second vegetation target object, wherein the first vegetation growth rate r = ((ab) ÷ b) × 100%, a is the current vegetation coverage area, which is determined based on the pixel ratio of the second vegetation target object in the second soil area image, and b is the initial vegetation coverage area, which is determined based on the pixel ratio of the first vegetation target object in the first soil area image. S3013. The first estimated pollution diffusion area is obtained by adjusting the initial pollution diffusion area according to the first adjustment coefficient. S3014. Utilize the estimated area of ​​first pollution diffusion to allocate resources among the first soil monitoring areas of the same first importance level; step S3014 specifically includes the following steps: S30141. When the first vegetation growth rate is less than the preset threshold, the total number of corresponding equipment resources is determined based on the initial number of equipment resources corresponding to the first soil monitoring area and the first number of equipment resources corresponding to the first pollution diffusion estimated area. S30142. When the first vegetation growth rate is greater than or equal to a preset threshold, the initial number of equipment resources is adjusted to obtain a second number of equipment resources. The total number of equipment resources is determined based on the second number of equipment resources and the first number of equipment resources. Specifically, adjusting the initial number of equipment resources to obtain the second number of equipment resources includes: D1. Determining the coverage area of ​​the newly grown vegetation and the location of the newly grown vegetation in the first soil monitoring area based on the first and second vegetation target objects; D2. Determining the reduction in equipment resources based on the coverage area of ​​the newly grown vegetation and the location of the newly grown vegetation in the first soil monitoring area; D3. Adjusting the initial number of equipment resources based on the reduction in equipment resources to obtain the second number of equipment resources. S30143. Based on the total number of equipment resources, resources shall be allocated to the first soil monitoring areas of the same first importance level.

2. The method as described in claim 1, characterized in that, The influencing factor characteristic values ​​also include the first precipitation and the first water evaporation, wherein the first precipitation refers to the total precipitation in the first soil monitoring area within the monitoring time interval, and the first water evaporation refers to the total water evaporation in the first soil monitoring area within the monitoring time interval.

3. The method as described in claim 1, characterized in that, Step S30143 specifically includes the following steps: S301431. Summing up the total number of equipment resources corresponding to the first soil monitoring areas with the same first importance level, we obtain the first summation result; S301432. When the first summation result is less than or equal to the number of idle equipment resources, resource allocation shall be carried out according to the total number of equipment resources corresponding to the first soil monitoring area with the same first importance level. S301433. When the first summation result is greater than the number of idle equipment resources, the resources of the first soil monitoring areas with the same first importance level shall be allocated in descending order according to the total number of equipment resources corresponding to the first soil monitoring area.

4. The method according to any one of claims 1-3, characterized in that, Step S3012 specifically includes the following steps: S30121. After obtaining the feature values ​​of several influencing factors, the feature values ​​of several influencing factors are used to form the first feature data input matrix. S30122. After inputting the first feature data input matrix into the first machine learning model for processing, the first adjustment coefficient is output.

5. A soil environmental monitoring data management and processing system, characterized in that, The system includes: The first soil testing and monitoring equipment is used to obtain soil testing and monitoring data after testing and monitoring the soil monitoring area; A background processing system, comprising at least one processor, for loading a program to execute the method as described in any one of claims 1-4; The first soil testing and monitoring equipment is connected to the background processing system.

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