Soil environment protection detection data management processing system and method

Abstract

The invention discloses a soil environment protection detection data management processing method and system, and the method comprises the following steps: S1, obtaining first soil region attribute data corresponding to a first soil monitoring region, the first soil region attribute data at least comprising a pollution attribute, a geographic position and a land utilization mode; s2, determining a first importance level corresponding to the first soil monitoring area according to the first soil area attribute data; and S3, performing resource allocation according to the first importance level corresponding to the first soil monitoring area. According to the scheme, the importance degree of the soil area is determined by adopting the multi-dimensional soil attribute parameters, the accuracy is higher, and the method is more in line with the actual situation, so that the value loss and the negative influence caused by delayed resource allocation of the soil area with higher importance can be reduced. The scheme of the invention can be widely applied to the field of soil environmental protection detection and monitoring.

Description

Technical Field

[0001] The present invention relates to environmental data analysis and processing technology, and in particular to a soil environment and environmental testing data management and processing system and method. Background Art

[0003] At present, for industrial land with known / suspected pollution or ecological areas of key concern, regular or irregular monitoring will be carried out as needed to monitor changes in soil pollution, so as to timely update the environmental risk assessment conclusions and adjust the control measures. In view of this, there will be a situation where there are multiple different soil areas that need to perform corresponding monitoring work in the same time period, and the relevant equipment resources for soil pollution monitoring are limited. Therefore, when allocating resources, it is necessary to consider sorting the soil areas and then allocate resources in order. However, the current basis for sorting soil areas mainly relies on the historical experience of staff or single-dimensional considerations, which leads to low accuracy in the processing of resource allocation priorities, resulting in delayed resource allocation for soil areas with higher actual importance, resulting in greater losses and negative impacts. Summary of the invention

[0004] The present application aims to solve at least one of the technical problems existing in the prior art. To this end, the present application proposes a soil environment environmental protection detection data management and processing system and method, which can improve the accuracy of resource allocation priority in the soil monitoring area to avoid excessive value loss and reduce negative impact.

[0005] In a first aspect, an embodiment of the present application provides a method for managing and processing soil environment environmental protection detection data, the method comprising the following steps:

[0006] S1. Acquire first soil region attribute data corresponding to a first soil monitoring region, wherein the first soil region attribute data at least includes pollution attributes, geographical location, and land use pattern;

[0007] S2. determining a first importance level corresponding to the first soil monitoring area according to the first soil area attribute data;

[0008] S3. Allocate resources according to the first importance level corresponding to the first soil monitoring area.

[0009] In some embodiments, step S3 specifically includes the following steps:

[0010] S301. Allocate resources for first soil monitoring areas with the same first importance level by using a first estimated pollution diffusion area corresponding to the first soil monitoring area.

[0011] In some embodiments, step S301 specifically includes the following steps:

[0012] S3011. In response to a monitoring trigger instruction, obtaining an initial pollution diffusion estimated area corresponding to a first soil monitoring area;

[0013] S3012, after obtaining the characteristic value of the influencing factor, determine a first adjustment coefficient according to the characteristic value of the influencing factor;

[0014] S3013, adjusting the initial pollution diffusion estimated area according to the first adjustment coefficient to obtain a first pollution diffusion estimated area;

[0015] S3014. Use the first estimated pollution diffusion area to allocate resources to the first soil monitoring area with the same first importance level.

[0016] In some embodiments, the characteristic value of the influencing factor includes a first precipitation amount and a first water evaporation amount, wherein the first precipitation amount refers to the total precipitation amount corresponding to the first soil monitoring area within the monitoring time interval, and the first water evaporation amount refers to the total water evaporation amount corresponding to the first soil monitoring area within the monitoring time interval.

[0017] In some embodiments, the influencing factor characteristic value further includes a first vegetation addition rate, and the first vegetation addition rate is obtained by the following steps:

[0018] Acquire a first soil region image and a second soil region image, wherein the first soil region image refers to an initial captured image of the first soil monitoring region, and the second soil region image is a captured image obtained after the first capturing device is triggered to capture the first soil monitoring region in response to a monitoring trigger instruction;

[0019] Respectively identifying a first vegetation target object in the first soil region image and a second vegetation target object in the second soil region image by using an image recognition technology;

[0020] A first vegetation addition rate is determined according to the first vegetation target object and the second vegetation target object.

[0021] In some embodiments, the step of determining the first vegetation addition rate according to the first vegetation target object and the second vegetation target object specifically includes:

[0022] Determine the current vegetation coverage area according to the pixel ratio of the second vegetation target object in the second soil region image;

[0023] Determine an initial vegetation coverage area according to a pixel ratio of the first vegetation target object in the first soil region image;

[0024] The first vegetation addition rate is determined according to the current vegetation coverage area and the initial vegetation coverage area.

[0025] In some embodiments, step S3014 specifically includes the following steps:

[0026] S30141. When the first vegetation addition rate is less than a preset threshold, the corresponding total number of equipment resources is determined according to 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;

[0027] S30142. When the first vegetation addition rate is greater than or equal to a preset threshold, the initial device resource quantity is adjusted to obtain a second device resource quantity, and the total device resource quantity is determined based on the second device resource quantity and the first device resource quantity;

[0028] S30143. Allocate resources for the first soil monitoring areas with the same first importance level according to the total number of equipment resources.

[0029] In some embodiments, the step S30143 specifically includes the following steps:

[0030] S301431. Summing the total number of equipment resources corresponding to the first soil monitoring areas with the same first importance level to obtain a first summation result;

[0031] S301432. When the first summation result is less than or equal to the number of idle equipment resources, allocate resources according to the total number of equipment resources corresponding to the first soil monitoring area with the same first importance level;

[0032] S301433. When the first summation result is greater than the number of idle equipment resources, resources are allocated to the first soil monitoring areas with the same first importance level in order from largest to smallest according to the total number of equipment resources corresponding to the first soil monitoring areas.

[0033] In some embodiments, step S3012 specifically includes the following steps:

[0034] S30121. After obtaining a plurality of influencing factor eigenvalues, the plurality of influencing factor eigenvalues ​​are used to form a first eigendata input matrix;

[0035] S30122. After inputting the first feature data input matrix into the first machine learning model for processing, output the first adjustment coefficient.

[0036] In a second aspect, an embodiment of the present application provides a soil environment environmental protection detection data management and processing system, the system comprising:

[0037] The first soil detection and monitoring equipment is used to detect and monitor the soil monitoring area and obtain soil detection and monitoring data;

[0038] A background processing system, comprising at least one processor, for loading a program to execute and implement a soil environment environmental protection detection data management and processing method as provided in the first aspect above;

[0039] The first soil detection and monitoring device is communicatively connected to the background processing system.

[0040] The present application can achieve at least one of the following technical effects: The present application scheme obtains the soil area attribute data corresponding to the soil monitoring area, wherein the soil area attribute data contains the pollution attributes, geographical location and land use mode corresponding to the soil monitoring area, thereby determining the corresponding importance level, and using this importance level as the resource allocation priority corresponding to the soil area, so as to sequentially retrieve and allocate corresponding resources for multiple soil monitoring areas. It can be seen that the present 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 delayed resource allocation to soil areas with higher importance. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments.

[0042] Figure 1 A schematic diagram of the steps of a soil environment environmental protection detection data management and processing method is provided for an embodiment of the present application;

[0043] Figure 2 This is a simplified schematic diagram of the first soil monitoring area V1 and the first pollution diffusion estimation area V2 in the embodiment of the present application;

[0044] Figure 3 A structural block diagram of a soil environment environmental protection detection data management and processing system is provided for an embodiment of the present application. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described through the implementation method with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application.

[0046] In order to achieve soil environmental protection, it is necessary to monitor the pollution of the soil environment, reveal the soil pollution status in time, and provide a scientific basis for the formulation of targeted governance measures. Conventionally, for soil areas known / suspected of pollution or key concerns, it is necessary to monitor the pollution situation again regularly or irregularly, and adjust the governance measures in time. In view of this, for professional monitoring agencies, there will be a situation where there are multiple different soil areas that 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 these soil areas. At present, the basis for sorting soil areas is mainly determined by the historical experience of staff or single-dimensional considerations, but it is found that this accuracy is low, and it is easy to have a lower priority for soil areas with higher actual importance, resulting in delayed resource allocation for soil areas with higher actual importance, that is, the monitoring work is delayed, which will easily lead to greater value loss and / or negative impact. It can be seen that designing a soil environment environmental protection detection data management and processing solution that can improve the accuracy of priority configuration is one of the technical problems that need to be solved urgently.

[0047] Reference Figure 1 The present application provides a method for managing and processing soil environment environmental protection detection data, and the method includes the steps as follows.

[0048] S1. Acquire first soil region attribute data corresponding to a first soil monitoring region, wherein the first soil region attribute data at least includes pollution attributes, geographical location, and land use pattern.

[0049] Specifically, in this embodiment, the pollution attributes at least include the pollutant type and the pollutant concentration, wherein different types of pollutants (such as heavy metals, organic compounds, radioactive substances, etc.) have different risk levels to the environment and human health. Therefore, the higher the risk level of the pollutant type contained in the soil, the higher the corresponding monitoring importance level; similarly, the higher the concentration of the pollutant in the soil, the higher the risk level it causes, and at this time, the higher the corresponding monitoring importance level. In other words, the pollution attributes in the soil will have a correlated impact on its monitoring importance level.

[0050] As for the geographical location, it specifically includes the geographical distance, which mainly refers to the geographical distance between the first soil monitoring area and the important land use area (such as water source area, residential living area, agricultural land, etc.), and the smaller the geographical distance, the easier it is for the first soil monitoring area to have a negative impact on the important land use area and / or the greater the degree of negative impact. Therefore, when the geographical distance is smaller, the monitoring importance level corresponding to the first soil monitoring area should be higher (because it is necessary to perform monitoring work faster and give priority to adjust the control measures as soon as possible, so as to solve its pollution problem as soon as possible), that is, this geographical distance will have an associated impact on its monitoring importance level. Furthermore, when there are multiple important land use areas near the first soil monitoring area, the geographical distance can be determined by obtaining the first geographical sub-distance between the first soil monitoring area and multiple important land use areas, and then calculating the average distance of multiple first geographical sub-distances, and using this distance average as the geographical distance. Under this premise, considering that at the same geographical distance, if the number of nearby important land use areas is greater, it means that the soil monitoring area will have an impact on more important land use areas, that is, the impact on the important land use areas is greater. Therefore, in this embodiment, the geographical location may also include the number of important land use areas.

[0051] For land use, it mainly refers to the type of land use in the first soil monitoring area. For example, if it is an area to be commercially developed, then its monitoring importance level should be higher (also because it is necessary to prioritize the monitoring work faster to adjust the governance measures as soon as possible, so as to solve its pollution problems as soon as possible, and avoid delays in monitoring work, which will lead to delays in regional development, which will cause more value losses). On the contrary, if the first soil monitoring area is a wasteland or other area that does not have a commercial development plan within the preset time period, then its monitoring importance level can be lower. It can be seen that the land use of the soil area has an associated impact on its monitoring importance level. It can be seen that using the parameters of the above three dimensions to comprehensively determine the monitoring importance level of the soil area can greatly improve the accuracy of the determination of the importance level, that is, improve the accuracy of the resource allocation priority.

[0052] In addition, for the first soil monitoring area, the current pollution coverage area (i.e., the soil area with pollutants) can be determined by the parameters obtained after various detection, monitoring, analysis and processing of the soil, and then the first soil monitoring area is determined according to the current pollutant coverage area. Among them, the various detection, analysis and processing means described here and the determination, analysis and processing means of the first soil monitoring area can all be implemented by existing technical means, and will not be specifically elaborated here.

[0053] S2. Determine a first importance level corresponding to the first soil monitoring area according to the first soil area attribute data. Specifically, step S2 may include the following two implementations.

[0054] Method ①, step S2 includes the following steps: A1, querying from the first historical database based on the first soil region attribute data to obtain the historical soil region attribute data with the highest similarity to the first soil region attribute data; A2, based on the historical soil region attribute data with the highest similarity obtained by query, obtaining the corresponding historical importance level from the mapping relationship between the historical soil region attribute data and the historical importance level, and the corresponding historical importance level obtained at this time is the required first importance level.

[0055] It can be seen that for the above method ①, it is necessary to construct a mapping relationship between the historical soil area attribute data corresponding to the historical soil monitoring area and the corresponding historical importance level, so that when this mapping relationship is stored in the database, when the query is actually run later, the data interface of this database can be directly called to match and retrieve the corresponding data.

[0056] Method ②, step S2 includes the following steps: B1, constructing a second feature data input matrix from the first soil area 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.

[0057] It can be seen that for the above method ②, it is necessary to use historical soil regional 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 conditions are met. In this way, when it is actually used, the actual soil regional attribute data corresponding to the current soil monitoring area can be used as the data input matrix and then input into the trained second machine learning model for processing to obtain the corresponding first importance level.

[0058] For the above methods ① and ②, they can be selected and set accordingly according to the actual situation, and no special restrictions are made here.

[0059] S3. Allocate resources according to the first importance level corresponding to the first soil monitoring area.

[0060] Specifically, when multiple soil monitoring areas need to conduct soil testing and monitoring again in the same time period in order to update the current pollution situation of the soil monitoring area in real time, they can be sorted according to the first importance level corresponding to each first soil monitoring area, where the higher the first importance level, the higher the corresponding resource retrieval allocation priority, that is, the higher the order in which it is arranged for monitoring work, that is, the above first importance level is mainly used to determine the order priority in resource retrieval allocation. Among them, the numerical value used to characterize the first importance level can be smaller, indicating a higher level, or larger, indicating a higher level. This can be selected and set according to actual needs, and no special restrictions are made here.

[0061] It can be seen that through the above-mentioned method of determining the importance level of soil monitoring areas, more dimensions of influencing factors are introduced, so the accuracy of the level determination is better and more in line with the actual situation, thereby greatly reducing the loss of value and negative impact.

[0062] In some embodiments, multiple soil monitoring areas will need to conduct soil testing and monitoring again in the same time period. On this basis, there will be at least two or more first soil monitoring areas with the same first importance level. Considering that the larger the area required for testing and monitoring, the more testing and monitoring sampling points will be, resulting in more testing and monitoring equipment resources required, and the time required for the testing and monitoring processing will also be longer. According to historical experience data statistics, the longer the testing and monitoring processing time is, the more testing and monitoring sampling points are involved, and the more unstable factors that affect work errors and / or delays will occur and / or the more times they will occur. In other words, the larger the area of ​​the soil area required for testing and monitoring, the more likely it is that the work will be delayed, and even the delay time is relatively long. In view of this, the resource allocation waiting time of these areas with large monitoring areas to be detected (i.e., areas that require a large number of monitoring equipment resources) should be minimized. In other words, when the number of idle equipment resources is not enough to allocate corresponding resources to all the soil monitoring areas to be processed, in order to minimize the resource waiting time of the above areas, the resources are allocated in order from large to small according to the number of monitoring equipment resources corresponding to the monitoring area to be detected currently corresponding to the soil monitoring area. Therefore, in this embodiment, for the step S3, it specifically includes the following steps:

[0063] S301. Allocate resources for first soil monitoring areas with the same first importance level by using a first estimated pollution diffusion area corresponding to the first soil monitoring area.

[0064] Specifically, in order to predict and evaluate the estimated pollution diffusion area corresponding to any soil area, it generally adopts a finite volume two-dimensional steady-state diffusion model, a GIS interpolation diffusion model and other two-dimensional dynamic pollutant diffusion models for estimated calculations. When the relevant data corresponding to the soil monitoring area is collected, such as the type and concentration of pollutants, and the characteristic data of the soil (such as the permeability, water content, porosity, vegetation coverage, etc. of the soil), the collected data is input into the corresponding model, and the estimated pollution diffusion area corresponding to the soil area can be obtained. Among them, the collected data required to be inputted by different diffusion models will be different, so the corresponding data required to be collected can be determined after the selected model is determined. As for using these diffusion models to process the input sampling data to obtain the corresponding estimated pollution diffusion area, it is an existing technical means, which will not be elaborated here.

[0065] Then, the first number of equipment resources corresponding to the first estimated pollution diffusion area is determined, and then the total number of equipment resources required for the soil monitoring area is determined according to the first number of equipment resources and the initial number of equipment resources corresponding to the first soil monitoring area (this may be the number of equipment resources actually used when the first soil monitoring area is first tested and monitored). That is to say, for step S301, it can be specifically as follows: using the initial number of equipment resources corresponding to the first soil monitoring area and the first number of equipment resources corresponding to the area of ​​the first estimated pollution diffusion area, the total number of equipment resources that should be configured and arranged for the first soil monitoring area when the detection and monitoring is performed again is determined, and according to the total number of equipment resources corresponding to each first soil monitoring area, resources are allocated for the first soil monitoring areas with the same first importance level. That is to say, when there are at least two first soil monitoring areas with the same first importance level, resources are allocated according to the total number of equipment resources corresponding to the first soil monitoring areas.

[0066] like Figure 2 As shown, V1 represents the first soil monitoring area, and V2 represents the estimated pollution diffusion area determined based on the relevant data corresponding to the first monitoring area combined with the model. In this way, the number of equipment resources required for its area can be obtained according to the area of ​​V2. In this way, according to the actual number of equipment resources used corresponding to V1 (i.e., the initial number of equipment resources) and the first number of equipment resources corresponding to the area of ​​V2, the total number of equipment resources required for the soil area to be tested and monitored again can be estimated. When the detection and monitoring are carried out again, the pollution changes in the current soil area can be timely understood according to the analysis and processing structure of these detection and monitoring data, so as to determine whether it is necessary to adjust the governance strategy or end the corresponding remediation operation.

[0067] In some embodiments, there is a monitoring time interval between the detection and monitoring time point of the first soil monitoring area and the time point of the next detection and monitoring, and during this interval, the estimated pollution diffusion area will be affected by some environmental factors. Therefore, when it is necessary to perform the detection and monitoring work again, it is necessary to obtain these influencing factors and determine the corresponding adjustment coefficients based on them, so as to adjust the initial pollution diffusion estimated area, so that the accuracy of the result of the total number of equipment resources determined subsequently will be higher. Therefore, for step S301, it specifically includes the following steps.

[0068] S3011, in response to the monitoring trigger instruction, obtaining the initial pollution diffusion estimated area corresponding to the first soil monitoring area. When the monitoring trigger instruction is received, it means that the detection and monitoring work needs to be performed again, and the monitoring time interval can be determined based on this time point and the initial detection and monitoring time point of the first soil monitoring area.

[0069] S3012: After obtaining the characteristic value of the influencing factor, determine a first adjustment coefficient according to the characteristic value of the influencing factor.

[0070] In some embodiments, step S3012 specifically includes the following steps.

[0071] S30121. After obtaining a plurality of influencing factor eigenvalues, the plurality of influencing factor eigenvalues ​​are used to form a first characteristic data input matrix.

[0072] S30122. After inputting the first feature data input matrix into the first machine learning model for processing, output the first adjustment coefficient.

[0073] Specifically, for the first machine learning model, it needs to be trained using training input data and training output data to obtain a trained first machine learning model. In this embodiment, the characteristic value of the historical influencing factor constitutes the second training input data, and the historical adjustment coefficient is used as the second training output data, wherein the historical adjustment coefficient is determined based on the ratio between the area of ​​the historical initial pollution diffusion estimate (i.e., the area of ​​the historical initial pollution diffusion estimate region) and the historical actual pollution diffusion estimate area obtained by the actual detection and monitoring when the detection and monitoring are performed again. Further, the historical adjustment coefficient can be directly the ratio, or the ratio can be slightly adjusted to obtain the final historical adjustment coefficient, which can be selected according to the actual situation and is not specifically limited here. It can be seen that when the actual application is run, the first machine learning model that has been trained is used to process the characteristic value of the input actual influencing factor to obtain the corresponding first adjustment coefficient, which can improve the processing efficiency of the actual operation and the accuracy of the output adjustment coefficient.

[0074] S3013. Adjust the initial pollution diffusion estimated area according to the first adjustment coefficient to obtain a first pollution diffusion estimated area.

[0075] S3014. Use the first estimated pollution diffusion area to allocate resources to the first soil monitoring area with the same first importance level.

[0076] In some embodiments, water is the main physical carrier of pollutants in the soil, so the moisture content of the soil will have a significant impact on the movement and diffusion area of ​​pollutants, and the moisture content of the soil will be affected by precipitation and soil moisture evaporation. Therefore, in this embodiment, the characteristic value of the influencing factor mainly includes the first precipitation and the first moisture evaporation. Among them, the first precipitation refers to the total precipitation corresponding to the first soil monitoring area within the monitoring time interval, that is, the total precipitation experienced by the first soil monitoring area within the monitoring time interval is taken as the first precipitation; the first moisture evaporation refers to the total moisture evaporation corresponding to the first soil monitoring area within the monitoring time interval. For the above-mentioned total precipitation and total moisture evaporation, the specific calculation and determination method can be carried out by using the existing model for corresponding calculation and confirmation, which will not be elaborated here.

[0077] In some embodiments, within the monitoring time interval, there may be newly grown vegetation and / or larger vegetation growth in the first pollution diffusion estimation area, which will lead to a higher coverage of vegetation in the area. When the coverage increases, it will increase the water absorption and retention capacity, thus resulting in reduced runoff and shorter movement distance. In other words, vegetation can slow down the diffusion area of ​​pollutants. Therefore, when the vegetation addition rate in the first pollution diffusion estimation area is greater than 0, it means that the more vegetation there is, the greater the degree to which it slows down the diffusion area of ​​pollutants. In other words, the parameter of the vegetation addition rate will inevitably affect the area of ​​the pollution diffusion estimation area. Therefore, in order to further improve the accuracy of determining the first adjustment coefficient, the vegetation addition rate is introduced as an influencing factor in the first characteristic data input matrix.

[0078] From the above, it can be obtained that the influencing factor characteristic value also includes the first vegetation addition rate, and the first vegetation addition rate is obtained through the following steps.

[0079] C1. Acquire a first soil area image and a second soil area image, wherein the first soil area image refers to an initial captured image of the first soil monitoring area, and the second soil area image is a captured image obtained after the first capturing device is triggered to capture the first soil monitoring area in response to a monitoring trigger instruction.

[0080] Specifically, since the first pollution diffusion estimation area is an area extending 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. Therefore, the vegetation addition rate of the first soil monitoring area is used as the vegetation addition rate corresponding to the first pollution diffusion estimation area. As for the vegetation changes in the first soil monitoring area, it can be imaged at the initial detection and monitoring time point of the first soil monitoring area to obtain an initial captured image, and when receiving the monitoring trigger instruction, it means that the detection and monitoring work needs to be performed again, and at this time, the first shooting device is triggered to shoot the first soil monitoring area to obtain a second soil area image. Among them, for the two captured images, the shooting device used, the configured shooting parameters, the shooting angle, and the height of the shooting device should be the same, so as to ensure that the first soil monitoring area can be captured in the picture during the first and second shootings, and the parameters such as pixel degree 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 recognition accuracy is guaranteed.

[0081] C2. Identify the first vegetation target object in the first soil region image and the second vegetation target object in the second soil region image respectively by using image recognition technology.

[0082] C3. Determine a first vegetation addition rate according to the first vegetation target object and the second vegetation target object.

[0083] Specifically, the first vegetation addition rate is mainly determined by the vegetation addition amount, and the vegetation addition amount can be a number addition amount or a addition amount of other units, depending on the specific required settings.

[0084] In some embodiments, since the existing vegetation will grow larger when the vegetation is newly added, and the increase in vegetation will also slow down the diffusion area of ​​pollutants, in order to reflect that the increase in vegetation has taken into account the two dimensional factors of the increase in number and the increase in volume, the change in the coverage area of ​​the vegetation in the first soil monitoring area is used to determine the first vegetation increase rate. Therefore, the step C3 of determining the first vegetation increase rate based on the first vegetation target object and the second vegetation target object specifically includes:

[0085] C301. Determine a current vegetation coverage area according to a pixel ratio of a second vegetation target object in a second soil region image.

[0086] C302, determining the initial vegetation coverage area according to the pixel ratio of the first vegetation target object in the first soil region image. Specifically, since the actual area of ​​the first soil monitoring region is known, the actual vegetation coverage area can be determined by the pixel ratio of the vegetation target object and the first soil monitoring region.

[0087] C303. Determine a first vegetation addition rate according to the current vegetation coverage area a and the initial vegetation coverage area b.

[0088] Specifically, for the first vegetation addition rate, the specific determination steps 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 addition rate according to the ratio between the first difference and the initial vegetation coverage area b. Further, for the first vegetation addition rate r, the calculation formula used can be specifically: r = ((ab) ÷ b) × 100%. It can be seen that this method can improve the calculation accuracy of the vegetation addition rate.

[0089] In some embodiments, step S3014 specifically includes the following steps.

[0090] S30141. When the first vegetation addition rate is less than a preset threshold, the total number of equipment resources is determined according to 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.

[0091] Specifically, because vegetation will have an impact on the spread of pollution, the vegetation on the soil will not be removed during soil pollution detection and monitoring. Therefore, for the first soil monitoring area, if the first vegetation addition rate is very small, that is, there is no new vegetation. At this time, the number of equipment resources required for the first soil monitoring area remains unchanged, and is still the number of equipment resources actually used when the detection and monitoring work is initially performed, that is, the initial number of equipment resources. On this basis, when the detection and monitoring work needs to be performed again, the total number of equipment resources includes the initial number of equipment resources and the first number of equipment resources corresponding to the first estimated pollution diffusion area.

[0092] S30142. When the first vegetation addition rate is greater than or equal to a preset threshold, the initial device resource quantity is adjusted to obtain a second device resource quantity, and the total device resource quantity is determined based on the second device resource quantity and the first device resource quantity.

[0093] Specifically, when the first vegetation addition rate is greater than or equal to the preset threshold, it means that the newly added vegetation in the first soil monitoring area is relatively obvious and covers the soil. At this time, the initial number of equipment resources can be adjusted according to the first vegetation addition rate. Among them, if the vegetation addition rate is larger, the initial number of equipment resources will be reduced. Therefore, historical data can be used to obtain the mapping relationship between different vegetation addition rates and different second adjustment coefficients, and then the corresponding historical second adjustment coefficient is obtained from the above mapping relationship according to the first vegetation addition rate, and then the initial number of equipment resources is adjusted according to the second adjustment coefficient to obtain the second number of equipment resources.

[0094] Alternatively, the step of obtaining the second device resource quantity after adjusting the initial device resource quantity may specifically include:

[0095] D1. Determine 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.

[0096] D2. Determine the amount of equipment resource reduction based on the coverage area of ​​the newly added vegetation and the location of the newly added vegetation in the first soil monitoring area.

[0097] D3. After adjusting the initial device resource quantity according to the device resource reduction amount, a second device resource quantity is obtained.

[0098] Specifically, according to 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 into the position in the actual soil area by 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 comparative identification. According to the coverage area and position of the newly added vegetation, it can be queried from the historical data of the initial detection and monitoring execution operation to obtain whether the coverage area of ​​the newly added vegetation at this position overlaps with the detection and monitoring sampling point at that time. If it overlaps, the detection and monitoring sampling points corresponding to the overlapping part need to be cleared, and the number of detection and monitoring sampling points cleared corresponds to the number of equipment resources reduced. Therefore, in this embodiment, the reduction in equipment resources 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 equipment resource quantity can be adjusted according to the equipment resource reduction to obtain the second equipment resource quantity. It can be seen that the equipment resource quantity determined in this way is more accurate and more in line with the actual situation.

[0099] S30143. Allocate resources for the first soil monitoring areas with the same first importance level according to the total number of equipment resources.

[0100] In some embodiments, step S30143 specifically includes the following steps:

[0101] S301431. After summing up the total number of equipment resources corresponding to the first soil monitoring areas with the same first importance level, a first summation result is obtained.

[0102] S301432: when the first summation result is less than or equal to the number of idle equipment resources, allocate resources according to the total number of equipment resources corresponding to the first soil monitoring areas with the same first importance level. If resources are insufficient, resources can be allocated to the soil monitoring areas with the same importance level at the same time.

[0103] S301433. When the first summation result is greater than the number of idle equipment resources, resources are allocated to the first soil monitoring areas with the same first importance level in order from large to small according to the total number of equipment resources corresponding to the first soil monitoring areas. In this way, the waiting time for resource allocation in the areas with large areas to be inspected and monitored (i.e., areas that require a large number of inspection and monitoring equipment resources) can be minimized, thereby avoiding the situation where the inspection and monitoring work in these areas exceeds the specified time node or even exceeds the deadline by too much.

[0104] In some embodiments, the characteristic value of the influencing factor may also include the success rate of the treatment measures. If the success rate of the treatment measures is adopted after the first soil monitoring area is tested and monitored, it will have a certain effect on slowing down the spread of pollutants, and there is an inevitable connection between the success rate and the success rate. The higher the success rate, the better the effect of slowing down the spread. It can be seen that by introducing the influencing factors of this dimension, the accuracy will be further improved.

[0105] Reference Figure 3 The embodiment of the present application also provides a soil environment environmental protection detection data management and processing system, the system comprising:

[0106] The first soil detection and monitoring equipment is used to detect and monitor the soil monitoring area and obtain soil detection and monitoring data;

[0107] A background processing system, comprising at least one processor, for executing the method steps described in the above method embodiment after loading a program;

[0108] The first soil detection and monitoring device is communicatively connected to the background processing system.

[0109] Since the background processing system in the system embodiment includes at least one processor, and it is used to load the program to execute the method steps described in the above method embodiment, the description and beneficial effects of the system embodiment are the same as those of the method embodiment, so they will not be repeated here.

[0110] In addition, an embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the steps of the above method embodiment.

[0111] For the processors mentioned in the above storage medium embodiment and the system embodiment, the number can be at least 1, and at least any step in the above method embodiment can be executed. When the number is at least two, at least two processors can be connected to each other in a communication manner, not limited to wired or wireless communication connection, and the at least one processor can be connected to various intelligent terminal devices in a communication manner. In addition, the processor can be a central processing unit (CPU), or 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. A general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc.

[0112] Finally, it should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0113] Note that the above are only preferred embodiments of the present application and the technical principles used. Those skilled in the art will understand that the present application is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present application. Therefore, although the present application is described in more detail through the above embodiments, the present application is not limited to the above embodiments, and may 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 soil environment environmental protection detection data management and processing method, characterized in that: The method comprises the following steps: S1. Acquire first soil region attribute data corresponding to a first soil monitoring region, wherein the first soil region attribute data at least includes pollution attributes, geographical location, and land use pattern; S2. determining a first importance level corresponding to the first soil monitoring area according to the first soil area attribute data; S3. Allocate resources according to the first importance level corresponding to the first soil monitoring area.

2. The method according to claim 1, characterized in that The step S3 specifically comprises the following steps: S301. Allocate resources for first soil monitoring areas with the same first importance level by using a first estimated pollution diffusion area corresponding to the first soil monitoring area.

3. The method according to claim 2, characterized in that The step S301 specifically includes the following steps: S3011. In response to a monitoring trigger instruction, obtaining an initial pollution diffusion estimated area corresponding to a first soil monitoring area; S3012, after obtaining the characteristic value of the influencing factor, determine a first adjustment coefficient according to the characteristic value of the influencing factor; S3013, adjusting the initial pollution diffusion estimated area according to the first adjustment coefficient to obtain a first pollution diffusion estimated area; S3014. Use the first estimated pollution diffusion area to allocate resources to the first soil monitoring area with the same first importance level.

4. The method according to claim 3, characterized in that The influencing factor characteristic value includes a first precipitation and a first water evaporation, wherein the first precipitation refers to the total precipitation amount corresponding to the first soil monitoring area within the monitoring time interval, and the first water evaporation amount refers to the total water evaporation amount corresponding to the first soil monitoring area within the monitoring time interval.

5. The method according to claim 4, characterized in that The influencing factor characteristic value further includes a first vegetation addition rate, and the first vegetation addition rate is obtained by the following steps: Acquire a first soil region image and a second soil region image, wherein the first soil region image refers to an initial captured image of the first soil monitoring region, and the second soil region image is a captured image obtained after the first capturing device is triggered to capture the first soil monitoring region in response to a monitoring trigger instruction; Respectively identifying a first vegetation target object in the first soil region image and a second vegetation target object in the second soil region image by using an image recognition technology; A first vegetation addition rate is determined according to the first vegetation target object and the second vegetation target object.

6. The method according to claim 5, characterized in that The step of determining the first vegetation addition rate according to the first vegetation target object and the second vegetation target object specifically includes: Determine the current vegetation coverage area according to the pixel ratio of the second vegetation target object in the second soil region image; Determine an initial vegetation coverage area according to a pixel ratio of the first vegetation target object in the first soil region image; The first vegetation addition rate is determined according to the current vegetation coverage area and the initial vegetation coverage area.

7. The method according to claim 6, characterized in that The step S3014 specifically includes the following steps: S30141. When the first vegetation addition rate is less than a preset threshold, the corresponding total number of equipment resources is determined according to 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 addition rate is greater than or equal to a preset threshold, the initial device resource quantity is adjusted to obtain a second device resource quantity, and the total device resource quantity is determined based on the second device resource quantity and the first device resource quantity; S30143. Allocate resources for the first soil monitoring areas with the same first importance level according to the total number of equipment resources.

8. The method according to claim 7, characterized in that The step S30143 specifically includes the following steps: S301431. Summing the total number of equipment resources corresponding to the first soil monitoring areas with the same first importance level to obtain a first summation result; S301432. When the first summation result is less than or equal to the number of idle equipment resources, allocate resources 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, resources are allocated to the first soil monitoring areas with the same first importance level in order from largest to smallest according to the total number of equipment resources corresponding to the first soil monitoring areas.

9. The method according to any one of claims 3 to 8, characterized in that: The step S3012 specifically includes the following steps: S30121. After obtaining a plurality of influencing factor eigenvalues, the plurality of influencing factor eigenvalues ​​are used to form a first eigendata input matrix; S30122. After inputting the first feature data input matrix into the first machine learning model for processing, output the first adjustment coefficient.

10. A soil environment environmental protection detection data management and processing system, characterized in that: The system includes: The first soil detection and monitoring equipment is used to detect and monitor the soil monitoring area and obtain soil detection and monitoring data; A background processing system, comprising at least one processor, configured to load a program to execute the method according to any one of claims 1 to 9; The first soil detection and monitoring device is communicatively connected to the background processing system.

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