Method, device, storage medium and electronic device for monitoring vegetation coverage in mining areas

Abstract

The present disclosure relates to a method, device, storage medium, and electronic device for monitoring vegetation coverage in a mining area, and relates to the field of coal mining technology. The method comprises: obtaining subsidence and deformation information of the ground surface; obtaining soil moisture content corresponding to the subsidence and deformation information based on a first interaction relationship, wherein the first interaction relationship is the relationship between deformation, subsidence, and the soil moisture content; and determining a target coverage rate corresponding to the soil moisture content based on a second interaction relationship, wherein the second interaction relationship is obtained by fitting the vegetation coverage rate with the soil moisture content. The present disclosure can more accurately obtain the vegetation coverage of the mining area by pre-fitting the first and second interaction relationships.

Description

Technical Field

[0001] The present disclosure relates to the technical field of coal mining, and in particular to a method, device, storage medium and electronic equipment for monitoring vegetation coverage in a mining area. Background Art

[0002] With the development of society, the economy, and the growth of industrial demand, mining pressure is gradually increasing, posing a serious threat to vegetation. In mining projects, vegetation is a decisive factor in ecological reconstruction and improving the ecological and environmental quality of mining areas. Vegetation not only improves the ecological environment of mining areas, but also enhances ecological services and promotes carbon sequestration and carbon sinks in ecosystems.

[0003] Specifically, vegetation plays an important role in ecological restoration and sustainable development in mining areas by improving soil chemistry, enhancing soil microbial activity, and regulating the abundance of genes involved in carbon cycling. Therefore, how to better monitor vegetation coverage in mining areas is a pressing technical challenge. Summary of the Invention

[0004] In order to overcome the problems existing in the related art, the present disclosure provides a method, device, storage medium and electronic device for monitoring vegetation coverage in a mining area.

[0005] According to a first aspect of an embodiment of the present disclosure, a method for monitoring vegetation coverage in a mining area is provided, the method comprising:

[0006] Obtaining subsidence and deformation information of the ground surface;

[0007] obtaining soil moisture content corresponding to the subsidence information and the deformation information based on a first action relationship, wherein the first action relationship is a relationship between deformation, subsidence, and the soil moisture content;

[0008] The target coverage rate corresponding to the soil moisture content is determined according to a second interaction relationship, where the second interaction relationship is obtained by fitting the vegetation coverage rate with the soil moisture content.

[0009] Optionally, the method further includes:

[0010] Obtaining a plurality of historical soil moisture contents, and obtaining a historical vegetation coverage rate corresponding to each of the historical soil moisture contents;

[0011] Each of the historical vegetation coverage rates is fitted with the corresponding historical soil moisture content to obtain the second interaction relationship.

[0012] Optionally, fitting each of the historical vegetation coverage rates with the corresponding historical soil moisture content to obtain the second interaction relationship includes:

[0013] collecting remote sensing images of the surface deformation area, and determining a trend slope of the Normalized Difference Vegetation Index (NDVI) based on the remote sensing images;

[0014] Obtaining the maximum vegetation coverage rate of the surface deformation area;

[0015] The second interaction relationship is obtained by fitting the maximum vegetation coverage, the trend slope, and the relationship between the historical soil moisture content and the historical vegetation coverage.

[0016] Optionally, obtaining multiple historical soil moisture contents includes:

[0017] Acquire multiple historical sinking information and historical deformation information corresponding to each of the historical sinking information;

[0018] The historical soil moisture content corresponding to each of the historical subsidence information and the historical deformation information is determined according to the first action relationship.

[0019] Optionally, the method further includes:

[0020] The relationship between each of the historical subsidence information, the historical deformation information and the corresponding historical soil moisture content is fitted to obtain the first interaction relationship, wherein the historical subsidence information includes the subsidence speed of the surface, and the historical deformation information includes the curvature and deformation value of the surface. The soil moisture content in the first interaction relationship is comprehensively determined based on the subsidence speed, the curvature and the deformation value.

[0021] Optionally, the subsidence information includes a subsidence amount and a subsidence speed, the deformation information includes a deformation value, and obtaining the subsidence information and deformation information of the ground surface includes:

[0022] determining a subsidence coefficient of the ground surface, the subsidence coefficient being determined based on a maximum subsidence value, an average mining height, an average inclination angle of the coal seam, and a coefficient of sufficient mining degree along the dip and strike;

[0023] Obtaining the subsidence amount according to the subsidence coefficient, and determining the subsidence speed of the ground surface based on the subsidence amount;

[0024] Obtaining a main influence radius, where the main influence radius is determined based on an average mining depth and a main influence angle of the working face;

[0025] The deformation value is obtained based on the main influence radius and the sinking amount.

[0026] According to a second aspect of an embodiment of the present disclosure, a device for monitoring vegetation coverage in a mining area is provided, the device comprising:

[0027] A first acquisition module is configured to acquire subsidence information and deformation information of the ground surface;

[0028] a second acquisition module configured to acquire soil moisture content corresponding to the subsidence information and the deformation information based on a first action relationship, wherein the first action relationship is a relationship between deformation, subsidence, and the soil moisture content;

[0029] The determination module is configured to determine the target coverage rate corresponding to the soil moisture content according to a second functional relationship, where the second functional relationship is obtained by fitting the vegetation coverage rate with the soil moisture content.

[0030] According to a third aspect of an embodiment of the present disclosure, a computer-readable storage medium is provided, on which computer program instructions are stored. When the program instructions are executed by a processor, the steps of the method for monitoring vegetation coverage in mining areas provided by the first aspect of the present disclosure are implemented.

[0031] According to a fourth aspect of the embodiments of the present disclosure, there is provided an electronic device, including:

[0032] a memory having a computer program stored thereon;

[0033] A processor is used to execute the computer program in the memory to implement the steps of the method for monitoring vegetation coverage in a mining area provided in the first aspect of the present disclosure.

[0034] According to a fifth aspect of an embodiment of the present disclosure, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the steps of the method for monitoring vegetation coverage in mining areas provided in the first aspect of the present disclosure.

[0035] The present disclosure can obtain more accurate vegetation coverage through the pre-acquired second action relationship. Specifically, the subsidence information and deformation information of the surface are obtained, and the soil moisture content corresponding to the subsidence information and deformation information is obtained based on the first action relationship. The first action relationship is the relationship between deformation, subsidence and soil moisture content. On this basis, the target coverage rate corresponding to the soil moisture content is determined according to the second action relationship. The second action relationship is obtained by fitting the vegetation coverage rate with the soil moisture content. Based on the pre-acquired second action relationship, the changes in vegetation coverage rates in different areas of the mining area can be accurately predicted.

[0036] Other features and advantages of the present disclosure will be described in detail in the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The accompanying drawings are used to provide a further understanding of the present disclosure and constitute a part of the specification. Together with the following detailed description, they are used to explain the present disclosure but do not constitute a limitation of the present disclosure. In the accompanying drawings:

[0038] Figure 1 The present invention is a flowchart of a method for monitoring vegetation coverage in a mining area according to an exemplary embodiment.

[0039] Figure 2 The figure is a flow chart of another method for monitoring vegetation coverage in a mining area according to an exemplary embodiment.

[0040] Figure 3 It is an example flow chart of obtaining a first action relationship and a second action relationship in another method for monitoring vegetation coverage in a mining area according to an exemplary embodiment.

[0041] Figure 4 The figure is a block diagram of a monitoring device for vegetation coverage in a mining area according to an exemplary embodiment.

[0042] Figure 5 It is a block diagram of an electronic device according to an exemplary embodiment.

[0043] Figure 6 is a block diagram of a chip system according to an exemplary embodiment. DETAILED DESCRIPTION

[0044] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all possible embodiments consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.

[0045] In the description of the present disclosure, terms such as "first" and "second" are used to distinguish similar objects and are not necessarily to be understood as implying a specific order or precedence. In addition, in the description with reference to the accompanying drawings, the same reference numerals in different drawings represent the same elements unless otherwise indicated.

[0046] Although operations or steps are described in a particular order in the drawings in the embodiments of the present disclosure, this should not be understood as requiring that these operations or steps be performed in the particular order shown or in a serial order, or that all of the operations or steps shown be performed to obtain a desired result. In the embodiments of the present disclosure, these operations or steps may be performed serially; these operations or steps may also be performed in parallel; or some of these operations or steps may be performed.

[0047] The development and application of remote sensing, wireless sensor technology, big data, and artificial intelligence have greatly improved vegetation monitoring efficiency. However, vegetation restoration remains difficult and inefficient. Related technologies for vegetation monitoring in mining areas primarily rely on manual observation and simple instrument measurements. Consequently, they suffer from limitations such as low data accuracy, poor real-time performance, high labor intensity, limited monitoring range, and incomplete monitoring information. These limitations indicate that modern mining area vegetation monitoring cannot fully meet vegetation monitoring needs.

[0048] In order to solve the above problems, the embodiment of the present disclosure proposes a method for monitoring vegetation coverage in mining areas. The method obtains a vegetation response prediction model (second action relationship) and uses the vegetation response prediction model to perform real-time monitoring, data processing and analysis of vegetation, thereby realizing the prediction and evaluation of the vegetation status in the mining area, so as to improve the scientificity and effectiveness of vegetation protection in the mining area. Among them, the vegetation response prediction model can be a coal mining vegetation response prediction model that combines theory and remote sensing monitoring.

[0049] Figure 1 FIG. 1 is a flow chart showing a method for monitoring vegetation coverage in a mining area according to an exemplary embodiment. Figure 1 As shown, the method may include the following steps.

[0050] In step S110 , subsidence information and deformation information of the ground surface are obtained.

[0051] In some embodiments, the surface subsidence information may be a surface subsidence parameter, which may include a surface subsidence amount and a surface subsidence velocity. The surface subsidence amount may be obtained based on a surface subsidence coefficient, and the calculation formula for the surface subsidence coefficient may be:

[0052] ;

[0053] Where q is the surface subsidence coefficient, W m is the maximum subsidence value, the unit is mm; m is the average mining height; is the average dip angle of the coal seam; n1 is the coefficient of full mining along the dip, and n2 is the coefficient of full mining along the strike. For example, full mining is 1 and under-mining is 0.95.

[0054] As an optional method, after obtaining the surface subsidence coefficient, the embodiment of the present disclosure can obtain the surface subsidence amount based on the surface subsidence coefficient. The calculation formula of the surface subsidence amount is as follows:

[0055] ;

[0056] Wherein, q is the surface subsidence coefficient; m is the average mining height; is the average inclination of the coal seam; n1 is the full mining degree coefficient along the dip, n2 is the full mining degree coefficient along the strike; ε1 is the first correction coefficient obtained through actual measurement.

[0057] After obtaining the amount of ground subsidence, the embodiment of the present disclosure can obtain the ground subsidence velocity based on the ground subsidence. Before this, the ground subsidence velocity coefficient can be determined based on the maximum subsidence value. On this basis, the ground subsidence velocity is calculated by combining the ground subsidence velocity coefficient and the amount of ground subsidence. The calculation formula of the ground subsidence velocity coefficient is as follows:

[0058] ;

[0059] Where K is the sinking velocity coefficient; c is the working face advancement velocity, in m / d; H0 is the average mining depth of the working face, in m; W m is the maximum surface subsidence value, its unit is mm; V m It is the maximum surface subsidence velocity, and its unit is mm / d.

[0060] After calculating the sinking velocity coefficient, the embodiment of the present disclosure can obtain the sinking velocity calculation formula shown below through field monitoring of the mining area:

[0061] ;

[0062] Among them, V is the surface subsidence velocity; K is the subsidence velocity coefficient; c is the working face advancement speed; H0 is the average mining depth of the working face; W is the surface subsidence value (subsidence amount); ε2 is the second correction parameter obtained through actual measurement.

[0063] Combining the above-mentioned calculation formulas for surface subsidence and subsidence velocity, the final formula for subsidence velocity can be obtained, which is:

[0064] ;

[0065] The amount of ground subsidence directly affects the soil quality of the mining area. Therefore, the ground subsidence rate can be an important parameter for obtaining the target coverage rate. In other words, the embodiment of the present disclosure can obtain the water content of the soil based on the ground subsidence rate and the deformation value of the surface.

[0066] Since the scope of surface deformation caused by mining is uncertain, the parameters affecting the scope of surface deformation are substituted into the existing formula based on the actual data obtained from monitoring, and the calculation formula of the scope of surface deformation can be obtained, so that the scope of surface deformation can be effectively predicted.

[0067] In other embodiments, deformation information may be used to characterize the deformation range of the ground surface. The deformation information may include the curvature of the ground surface and the ground deformation value. Here, the curvature of the ground surface may be calculated based on the slope of the ground surface. The slope may be calculated using the following formula:

[0068] ;

[0069] in, is the slope, x refers to the distance from the center of surface deformation, W m is the maximum surface subsidence value; r is the main impact radius, which can be calculated according to the following formula:

[0070] ;

[0071] Among them, H0 is the average mining depth of the working face, and β is the main influencing angle.

[0072] On this basis, the embodiment of the present disclosure can perform a curvature calculation operation based on the main influence radius r. The calculation formula of the curvature is as follows:

[0073] ;

[0074] The parameters involved in calculating the curvature are similar to those involved in calculating the inclination, and will not be described in detail here.

[0075] Alternatively, the ground deformation value can be calculated according to the following formula:

[0076] ;

[0077] Where λ is the correction coefficient, W is the subsidence value, r is the main impact radius, and B is the surface horizontal movement coefficient. The surface horizontal movement coefficient B can be calculated according to the following formula:

[0078] ;

[0079] Among them, U m is the maximum value of horizontal surface movement obtained through monitoring, W m is the maximum surface subsidence value.

[0080] After obtaining the surface horizontal movement coefficient, the embodiment of the present disclosure can calculate and obtain the surface deformation value based on the horizontal movement coefficient.

[0081] Optionally, the embodiment of the present disclosure may also combine the horizontal movement coefficient B with the actual monitoring result and add a correction coefficient , get the horizontal movement value U of the surface, where It can be a correction coefficient obtained through actual measurement. The specific formula is as follows:

[0082] ;

[0083] In summary, in the process of obtaining surface subsidence and deformation information, the disclosed embodiments can first determine the surface subsidence coefficient. This subsidence coefficient can be determined based on the maximum surface subsidence value, the average mining height, the average inclination of the coal seam, and the coefficient of full mining degree along the dip and along the strike. The surface subsidence amount can then be obtained based on this subsidence coefficient.

[0084] In addition, the embodiment of the present disclosure can obtain the main influence radius, which can be determined according to the average mining depth and main influence angle of the working face. On this basis, the deformation value of the surface can be obtained based on the main influence radius and the subsidence amount.

[0085] In step S120, soil moisture content corresponding to the subsidence information and the deformation information is acquired based on a first action relationship, where the first action relationship is the relationship between deformation, subsidence, and soil moisture content.

[0086] As an optional method, after obtaining the subsidence information and deformation information of the ground surface, the embodiment of the present disclosure can obtain the soil moisture content corresponding to the subsidence information and deformation information based on the first action relationship.

[0087] Among them, the first action relationship can be the relationship between deformation, subsidence and soil moisture content. Here, deformation can be deformation information, and subsidence can be sinking information. That is, the embodiment of the present disclosure can input deformation information and sinking information into the first action relationship to output soil moisture content corresponding to the sinking information and deformation information through the first action relationship.

[0088] Specifically, the disclosed embodiments can utilize remote sensing technology and the deployment of monitoring points for real-time sampling to monitor and analyze soil moisture content within the deformation range. The first interaction relationship can be the response of soil moisture changes to surface deformation and subsidence, which can be the interaction between multiple independent and dependent variables.

[0089] In other words, soil moisture content can be affected by a combination of factors, including surface subsidence, tilt, and horizontal deformation. In this regard, embodiments of the present disclosure can combine surface subsidence, tilt, and horizontal deformation to establish a multivariate linear regression model. This multivariate linear regression model can be a first action relationship, whose input parameters can be subsidence information, deformation information, etc., and whose output parameter can be soil moisture content.

[0090] The optimal solution can be obtained through numerical simulation and calculation of actual monitoring results. The significance test of the first action relationship shows that the fitting effect is good, and the soil moisture content and surface subsidence, inclination and horizontal deformation satisfy the ternary quadratic function relationship.

[0091] In step S130, the target coverage rate corresponding to the soil moisture content is determined according to the second interaction relationship, where the second interaction relationship is obtained by fitting the vegetation coverage rate with the soil moisture content.

[0092] As an optional method, after obtaining the soil moisture content, the disclosed embodiments can determine a target coverage rate corresponding to the soil moisture content based on a second interaction relationship, where the second interaction relationship can be obtained by fitting the vegetation coverage rate to the soil moisture content. Here, the target coverage rate can be the vegetation coverage rate of the mining area predicted using the second interaction relationship.

[0093] By employing D-InSAR interferometric radar and remote sensing testing technology, the disclosed embodiments can monitor surface subsidence and movement. By fusing these two data sets, the surface deformation conditions in the mining area can be determined, allowing for analysis of surface deformation patterns. Based on this, observation lines are set up along the strike and dip of the mining area, and observation stations are arranged along these lines based on actual conditions. During the station placement process, changes in geological characteristics can be fully considered to better monitor the overall status of rock formation movement.

[0094] The embodiment of the present disclosure can obtain more accurate vegetation coverage through the pre-acquired second action relationship. Specifically, the subsidence information and deformation information of the surface are obtained, and the soil moisture content corresponding to the subsidence information and deformation information is obtained based on the first action relationship. The first action relationship is the relationship between deformation, subsidence and soil moisture content. On this basis, the target coverage rate corresponding to the soil moisture content is determined according to the second action relationship. The second action relationship is obtained by fitting the vegetation coverage rate with the soil moisture content. Based on the pre-acquired second action relationship, the changes in vegetation coverage rates in different areas of the mining area can be accurately predicted.

[0095] Figure 2 is a flow chart of another method for monitoring vegetation coverage in a mining area according to an exemplary embodiment. Figure 2 As shown, the method may include the following steps.

[0096] In step S210, a plurality of historical soil moisture contents are obtained, and a historical vegetation coverage rate corresponding to each historical soil moisture content is obtained.

[0097] From the above introduction, we know that the second interaction relationship can be a coal mining vegetation response prediction model. In order to obtain the coal mining vegetation response prediction model, the embodiment of the present disclosure can first obtain multiple historical soil moisture contents, and obtain the historical vegetation coverage corresponding to each historical soil moisture content.

[0098] Here, the historical soil moisture content may be obtained through actual measurement, or after obtaining the historical subsidence information and the historical deformation information, the historical subsidence information and the historical deformation information are input into the first interaction relationship to obtain the historical soil moisture content through the first interaction relationship.

[0099] That is, in the process of obtaining multiple historical soil moisture contents, the disclosed embodiment can obtain multiple historical subsidence information and historical deformation information corresponding to each historical subsidence information. Based on this, the historical soil moisture content corresponding to each historical subsidence information and historical deformation information is determined according to the first working relationship.

[0100] Prior to this, embodiments of the present disclosure may fit the relationship between each piece of historical subsidence information, historical deformation information, and the corresponding historical soil moisture content to obtain a first interaction relationship. The historical subsidence information may include the subsidence velocity of the ground surface, and the historical deformation information may include the curvature and deformation value of the ground surface. The soil moisture content in the first interaction relationship may be determined based on a comprehensive combination of the ground surface subsidence velocity, curvature, and deformation value.

[0101] Here, the first action relationship can be shown as follows:

[0102] ;

[0103] Where Y is the soil moisture content; a, b, c, ..., j are constants and coefficients of their respective variables; V is the ground's subsidence velocity; K(x) is the ground's curvature; and δ is the ground's deformation. As can be seen, the disclosed embodiments can derive the coefficients (a, b, c, ..., j) in the above formula by fitting the ground's subsidence velocity, curvature, and ground's deformation to the soil moisture content, thereby deriving the first interaction relationship.

[0104] That is to say, by combining the surface subsidence, tilt and horizontal deformation, a multiple linear regression model can be established according to the above formula, and the multiple linear regression model can be used as the first action relationship.

[0105] In addition, the historical vegetation coverage can be a coverage obtained through actual measurement. Here, the historical soil moisture content and the historical vegetation coverage are mainly used to obtain the second interaction relationship.

[0106] In step S220, each historical vegetation coverage is fitted with the corresponding historical soil moisture content to obtain a second interaction relationship.

[0107] As an optional approach, embodiments of the present disclosure can utilize remote sensing technology and Landsat OLI imagery to monitor and analyze vegetation in areas of surface deformation. By monitoring changes in the vegetation index and combining it with soil moisture content, the changing trends of vegetation in response to three factors: surface subsidence, tilt, and horizontal deformation can be observed.

[0108] Specifically, embodiments of the present disclosure can collect remote sensing images of areas with surface deformation and determine the trend slope of the Normalized Difference Vegetation Index (NDVI) based on these images. Furthermore, the maximum vegetation coverage of the area with surface deformation is obtained. Based on this, the relationship between the maximum vegetation coverage, the trend slope, and the historical soil moisture content and historical vegetation coverage is fitted to obtain a second interaction relationship.

[0109] The second role relationship can be shown as follows:

[0110] ;

[0111] in, is the maximum vegetation coverage; Y is the current soil moisture content; Y0 is the midpoint of the soil moisture content, which can also be called the turning point or semi-saturation point. Y0 can be obtained through actual measurement or simulation, that is, the embodiment of the present disclosure can obtain Y0 through fitting; S is the trend slope of the Normalized Difference Vegetation Index (NDVI). It can be seen that the second interaction relationship can be obtained by fitting the hyperbolic tangent function.

[0112] The above maximum vegetation coverage The vegetation coverage can be obtained by comparing multiple vegetation coverages, which can be calculated using the following formula:

[0113] ;

[0114] Among them, X i is the NDVI value of the corresponding pixel; X is is the NDVI value of non-vegetation pixels; X iv is the NDVI value of the pure vegetation pixel, i is the time, such as i can be years.

[0115] The trend slope S of the NDVI can be obtained based on the following formula:

[0116] ;

[0117] Among them, X im is the maximum NDVI value in the corresponding pixel, and i is the time.

[0118] By obtaining this second interaction relationship, the disclosed embodiments can accurately predict changes in vegetation coverage across different areas of a mining site, particularly in areas experiencing significant surface subsidence, tilt, and deformation. By quantifying the impact of soil moisture on vegetation growth, the disclosed embodiments can accurately assess the potential and rate of vegetation recovery, providing a scientific basis for ecological restoration in mining areas.

[0119] In addition, by leveraging advanced remote sensing technology and ground monitoring networks, the disclosed embodiments can monitor environmental changes in mining areas in real time and promptly warn of the risk of declining vegetation coverage, which is of great significance for preventing environmental deterioration in mining areas and guiding vegetation restoration projects.

[0120] In step S230, subsidence information and deformation information of the ground surface are obtained.

[0121] In step S240, soil moisture content corresponding to the subsidence information and the deformation information is acquired based on a first action relationship, where the first action relationship is a relationship between deformation, subsidence, and soil moisture content.

[0122] In step S250, the target coverage rate corresponding to the soil moisture content is determined according to the second interaction relationship, where the second interaction relationship is obtained by fitting the vegetation coverage rate with the soil moisture content.

[0123] The specific implementation of steps S230 to S250 has been described in detail in the above embodiment and will not be repeated here.

[0124] After obtaining the first and second functional relationships, the disclosed embodiment can determine the vegetation coverage based on the currently acquired subsidence information and deformation information. Specifically, the disclosed embodiment can first obtain the subsidence velocity, deformation value, and curvature of the ground surface, and then input these three parameters into the pre-fitted first functional relationship to obtain the soil moisture content. On this basis, the acquired soil moisture content, NDVI trend slope, and maximum vegetation coverage are input into the second functional relationship to obtain the vegetation coverage of the mining area at the current moment.

[0125] In addition, based on an in-depth understanding of the relationship between vegetation coverage and environmental factors, the embodiment of the present disclosure can provide customized strategic recommendations for vegetation restoration through the second action relationship.

[0126] It should be noted that after obtaining the target coverage corresponding to the soil moisture content using the second action relationship, the embodiment of the present disclosure can also obtain the coefficient of variation of the vegetation. The formula of the coefficient of variation is as follows:

[0127] ;

[0128] Where C is the coefficient of variation; n is the time of change; Y is the average soil moisture content; Xi is the NDVI value of the corresponding pixel; Y i is the soil moisture content of the corresponding pixel. The coefficient of variation C can be used to characterize the stability of vegetation changes. The larger the coefficient of variation, the weaker the vegetation stability, that is, the greater the change in vegetation cover.

[0129] By combining the coefficient of variation and target coverage, the disclosed embodiments can provide more precise, customized strategies and recommendations for vegetation restoration. For example, a larger coefficient of variation and a vegetation coverage greater than a first preset value indicate healthy vegetation growth in the mining area. Conversely, a smaller coefficient of variation and a vegetation coverage less than a second preset value indicate poor vegetation growth in the mining area, requiring human intervention to assist vegetation growth.

[0130] In summary, the embodiment of the present disclosure can determine the period and monitoring points for rock strata movement measurement based on the mining parameters of the working face in the mining project, as well as collect specific data related to rock strata movement, and monitor the surface deformation parameters and the surface subsidence within a certain range. On this basis, the working face parameters, surface deformation parameters and subsidence are fitted through relevant formulas to obtain the calculation formula for the surface deformation range and subsidence. Since the vegetation coverage rate is usually highly correlated with the water content of the soil, the embodiment of the present disclosure can establish a calculation formula for the soil water content in the mining area under the joint changes of surface deformation and subsidence through multi-factor regression analysis of soil water content and surface deformation. Finally, by combining the changes in vegetation coverage rate monitored by remote sensing with the soil water content in the mining area, a prediction model for vegetation coverage rate in the mining area can be obtained. Based on this model, the current lack of quantitative monitoring and prediction in the field of mining area ecological monitoring can be filled to a certain extent.

[0131] As a specific implementation method, Figure 3 The embodiment of the present disclosure shown can determine the monitoring range based on the working face parameters, obtain the actual values of the surface deformation range and the amount of subsidence, and according to the existing formula combined with the actual monitoring parameters, can obtain the calculation formula of the surface deformation parameters. In addition, the embodiment of the present disclosure can monitor the soil moisture content according to a certain period and range, and fit this data with the surface deformation parameters to obtain the calculation formula of the soil moisture content (first interaction relationship). On this basis, the soil vegetation coverage rate is monitored, and according to the change of vegetation coverage rate with soil moisture content, fitting is performed to obtain a mining area vegetation coverage rate prediction model (second interaction relationship). Subsequently, this prediction model can be used to quickly and accurately predict the coverage rate of vegetation in the mining area.

[0132] The embodiment of the present disclosure can obtain more accurate vegetation coverage through the pre-acquired second action relationship. Specifically, the subsidence information and deformation information of the surface are obtained, and the soil moisture content corresponding to the subsidence information and deformation information is obtained based on the first action relationship. The first action relationship is the relationship between deformation, subsidence and soil moisture content. On this basis, the target coverage rate corresponding to the soil moisture content is determined according to the second action relationship. The second action relationship is obtained by fitting the vegetation coverage rate with the soil moisture content. Based on the pre-acquired second action relationship, the changes in vegetation coverage rates in different areas of the mining area can be accurately predicted.

[0133] Figure 4 This is a block diagram of a device for monitoring vegetation coverage in a mining area according to an exemplary embodiment. Figure 4 The mining area vegetation coverage monitoring device 300 includes a first acquisition module 310 , a second acquisition module 320 and a determination module 330 .

[0134] The first acquisition module 310 is configured to acquire subsidence information and deformation information of the ground surface;

[0135] The second acquisition module 320 is configured to acquire the soil water content corresponding to the subsidence information and the deformation information based on a first action relationship, wherein the first action relationship is a relationship between deformation, subsidence and the soil water content;

[0136] The determination module 330 is configured to determine the target coverage rate corresponding to the soil moisture content according to a second functional relationship, where the second functional relationship is obtained by fitting the vegetation coverage rate with the soil moisture content.

[0137] In some embodiments, the mining area vegetation coverage monitoring device 300 may further include:

[0138] A historical information acquisition module is configured to acquire a plurality of historical soil moisture contents and a historical vegetation coverage rate corresponding to each of the historical soil moisture contents;

[0139] The second action relationship fitting module is configured to fit each of the historical vegetation coverage rates with the corresponding historical soil moisture content to obtain the second action relationship.

[0140] In some embodiments, the second action relationship fitting module may include:

[0141] an acquisition submodule configured to acquire remote sensing images of a surface deformation area and determine a trend slope of a normalized difference vegetation index (NDVI) based on the remote sensing images;

[0142] a coverage acquisition submodule, configured to acquire the maximum vegetation coverage of the surface deformation area;

[0143] The fitting submodule is configured to fit the maximum vegetation coverage, the trend slope, and the relationship between the historical soil moisture content and the historical vegetation coverage to obtain the second interaction relationship.

[0144] In some implementations, the historical information acquisition module may include:

[0145] a deformation information acquisition submodule, configured to acquire a plurality of historical sinking information and historical deformation information corresponding to each of the historical sinking information;

[0146] The water content determination submodule is configured to determine the historical soil water content corresponding to each of the historical subsidence information and the historical deformation information according to the first action relationship.

[0147] In some embodiments, the mining area vegetation coverage monitoring device 300 may further include:

[0148] The first interaction relationship fitting module is configured to fit the relationship between each of the historical subsidence information, the historical deformation information and the corresponding historical soil moisture content to obtain the first interaction relationship, the historical subsidence information includes the subsidence speed of the surface, the historical deformation information includes the curvature and deformation value of the surface, and the soil moisture content in the first interaction relationship is determined comprehensively based on the subsidence speed, the curvature and the deformation value.

[0149] In some embodiments, the subsidence information includes a subsidence amount and a subsidence speed, and the deformation information includes a deformation value. To obtain the subsidence information and deformation information of the ground surface, the first obtaining module 310 may include:

[0150] a subsidence coefficient determination submodule, configured to determine a subsidence coefficient of the ground surface, wherein the subsidence coefficient is determined based on a maximum subsidence value, an average mining height, an average inclination angle of the coal seam, and a sufficient mining degree coefficient along the dip and strike;

[0151] a subsidence information acquisition submodule, configured to acquire the subsidence amount according to the subsidence coefficient, and determine the subsidence speed of the ground surface based on the subsidence amount;

[0152] a radius acquisition submodule configured to acquire a main influence radius, wherein the main influence radius is determined according to an average mining depth and a main influence angle of the working face;

[0153] The deformation value acquisition submodule is configured to acquire the deformation value based on the main influence radius and the sinking amount.

[0154] The embodiment of the present disclosure can obtain more accurate vegetation coverage through the pre-acquired second action relationship. Specifically, the subsidence information and deformation information of the surface are obtained, and the soil moisture content corresponding to the subsidence information and deformation information is obtained based on the first action relationship. The first action relationship is the relationship between deformation, subsidence and soil moisture content. On this basis, the target coverage rate corresponding to the soil moisture content is determined according to the second action relationship. The second action relationship is obtained by fitting the vegetation coverage rate with the soil moisture content. Based on the pre-acquired second action relationship, the changes in vegetation coverage rates in different areas of the mining area can be accurately predicted.

[0155] Regarding the device for monitoring vegetation coverage in mining areas in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method for monitoring vegetation coverage in mining areas, and will not be elaborated on here.

[0156] Figure 5 FIG. 7 is a block diagram of an electronic device 700 according to an exemplary embodiment. Figure 5 As shown, the electronic device 700 may include: a first processor 701 , a memory 702 , and may further include one or more of a multimedia component 703 , an input / output (I / O) interface 704 , and a communication component 705 .

[0157] The first processor 701 is used to control the overall operation of the electronic device 700 to complete all or part of the steps in the above-mentioned method for monitoring vegetation coverage in mining areas. The memory 702 is used to store various types of data to support the operation of the electronic device 700. This data may include, for example, instructions for any application or method operating on the electronic device 700, as well as application-related data, such as contact information, sent and received messages, images, audio, video, etc. The memory 702 can be implemented by any type of volatile or non-volatile storage device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The multimedia component 703 may include a screen and an audio component. The screen may be, for example, a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signals may be further stored in the memory 702 or transmitted via the communication component 705. The audio component also includes at least one speaker for outputting audio signals. The I / O interface 704 provides an interface between the first processor 701 and other interface modules. These other interface modules may include a keyboard, a mouse, buttons, etc. These buttons may be virtual or physical buttons. The communication component 705 is used for wired or wireless communication between the electronic device 700 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, 4G, NB-IOT, eMTC, or other 5G networks, or a combination thereof, is not limited here. Accordingly, the communication component 705 may include a Wi-Fi module, a Bluetooth module, an NFC module, etc.

[0158] In an exemplary embodiment, the electronic device 700 can be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to execute the above-mentioned method for monitoring vegetation coverage in mining areas.

[0159] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided. When executed by a processor, the program instructions implement the steps of the above-described method for monitoring vegetation coverage in a mining area. For example, the computer-readable storage medium may be the aforementioned memory 702 including the program instructions. The above-described program instructions may be executed by the first processor 701 of the electronic device 700 to implement the above-described method for monitoring vegetation coverage in a mining area.

[0160] In another exemplary embodiment, a computer program product is also provided, which includes a computer program that can be executed by a programmable device, and the computer program has a code portion for executing the above-mentioned mining area vegetation coverage monitoring method when executed by the programmable device.

[0161] Some embodiments of the present disclosure also provide a chip system, such as Figure 6 As shown, the chip system includes at least one second processor 1301 and at least one interface circuit 1302. The second processor 1301 and the interface circuit 1302 can be interconnected via a line. For example, the interface circuit 1302 can be used to receive signals from other devices (such as the memory of an electronic device). For another example, the interface circuit 1302 can be used to send signals to other devices (such as the second processor 1301). Exemplarily, the interface circuit 1302 can read instructions stored in the memory and send the instructions to the second processor 1301. When the instructions are executed by the second processor 1301, the device for monitoring vegetation coverage in a mining area can execute the various steps in the above-mentioned embodiments. Of course, the chip system can also include other discrete components, and some embodiments of the present disclosure are not specifically limited to this.

[0162] In some embodiments of the present disclosure, the interface circuit 1302 can obtain data, program instructions and / or information from the internal storage area of the chip system; it can also obtain data, program instructions and / or information from outside the chip system.

[0163] Optionally, the chip system may further include a memory for storing necessary computer programs and data.

[0164] Those skilled in the art will also understand that the various illustrative logical blocks and steps listed in the embodiments of this application can be implemented through electronic hardware, computer software, or a combination of both. Whether such functions are implemented through hardware or software depends on the specific application and the design requirements of the entire system. Those skilled in the art may use various methods to implement the described functions for each specific application, but such implementation should not be construed as exceeding the scope of protection of the embodiments of this application.

[0165] Furthermore, the word "exemplary" is used herein to mean serving as an example, instance, or illustration. Any aspect or design described herein as "exemplary" is not necessarily to be construed as advantageous over other aspects or designs. Rather, the use of the word exemplary is intended to present concepts in a concrete manner. As used herein, the term "or" is intended to mean an inclusive "or" rather than an exclusive "or." That is, unless otherwise specified or clear from the context, "X applies to A or B" is intended to mean any of the natural inclusive permutations. That is, if X applies to A; X applies to B; or X applies to both A and B, then "X applies to A or B" satisfies any of the aforementioned instances. Furthermore, the articles "a" and "an," as used in this application and the appended claims, are generally understood to mean "one or more," unless otherwise specified or clear from the context to refer to the singular form.

[0166] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, with the true scope and spirit of the present disclosure being indicated by the appended claims.

[0167] It should be understood that, unless otherwise specifically noted, the features of the various embodiments of the present disclosure described herein may be combined with each other. As used herein, the term "and / or" includes any one of the relevant listed items and any combination of any two or more thereof; similarly, "at least one of" includes any one of the relevant listed items and any combination of any two or more thereof.

[0168] Although terms such as "first", "second" and "third" may be used herein to describe various components, parts, regions, layers or sections, these components, parts, regions, layers or sections are not limited to these terms. On the contrary, these terms are only used to distinguish one component, part, region, layer or section from another component, part, region, layer or section. Therefore, without departing from the teachings of each example, the first component, part, region, layer or section mentioned in the examples described herein may also be referred to as the second component, part, region, layer or section. In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, the features defined as "first" and "second" can explicitly or implicitly include at least one such feature. In the description herein, the meaning of "multiple" is at least two, for example, two, three, etc., unless otherwise clearly and specifically defined.

[0169] The preferred embodiments of the present disclosure are described in detail above in conjunction with the accompanying drawings. However, the present disclosure is not limited to the specific details of the above embodiments. Within the technical concept of the present disclosure, various simple modifications can be made to the technical solutions of the present disclosure, and these simple modifications all fall within the scope of protection of the present disclosure.

[0170] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any appropriate manner without contradiction. In order to avoid unnecessary repetition, the present disclosure will not further describe various possible combinations.

[0171] In addition, the various embodiments of the present disclosure may be arbitrarily combined, and as long as they do not violate the concept of the present disclosure, they should also be regarded as the contents disclosed by the present disclosure.

Claims

1. A method for monitoring vegetation coverage in mining areas, characterized in that: The method comprises: Acquiring subsidence information and deformation information of the ground surface, wherein the subsidence information includes subsidence amount and subsidence speed, and the deformation information includes deformation value and curvature; The obtaining of the subsidence information and deformation information of the ground surface includes: determining a subsidence coefficient of the ground surface, the subsidence coefficient being determined based on a maximum subsidence value, an average mining height, an average inclination angle of the coal seam, and a coefficient of sufficient mining degree along the dip and strike; Obtaining the subsidence amount according to the subsidence coefficient, and determining the subsidence speed of the ground surface based on the subsidence amount; Obtaining a main influence radius, where the main influence radius is determined based on an average mining depth and a main influence angle of the working face; Obtaining the deformation value based on the main influence radius and the sinking amount; The soil moisture content corresponding to the sinking velocity, the deformation value, and the curvature of the ground surface is obtained based on a first action relationship, wherein the first action relationship is a relationship between deformation, subsidence, and the soil moisture content established by a multivariate quadratic function model, and the multivariate quadratic function is: ； Wherein, Y is the soil moisture content; a to j are fitting coefficients; V is the sinking velocity; K(x) is the curvature of the ground surface; δ is the deformation value of the ground surface; The target coverage rate corresponding to the soil moisture content is determined according to a second action relationship, wherein the second action relationship is the relationship between the vegetation coverage rate fitted by a hyperbolic tangent function and the soil moisture content, and the hyperbolic tangent function is: ； in, is the maximum vegetation coverage; Y is the current soil moisture content; Y0 is the midpoint of soil moisture content; S is the trend slope of the normalized difference vegetation index NDVI; Obtaining a coefficient of variation of vegetation, where the coefficient of variation of vegetation is used to characterize a stability of vegetation changes; A corresponding vegetation restoration strategy is obtained according to the coefficient of variation and the target coverage rate.

2. The method for monitoring vegetation coverage in mining areas according to claim 1, characterized in that: The method further comprises: Obtaining a plurality of historical soil moisture contents, and obtaining a historical vegetation coverage rate corresponding to each of the historical soil moisture contents; Each of the historical vegetation coverage rates is fitted with the corresponding historical soil moisture content to obtain the second interaction relationship.

3. The method for monitoring vegetation coverage in mining areas according to claim 2, characterized in that: The fitting of each of the historical vegetation coverage rates with the corresponding historical soil moisture content to obtain the second interaction relationship includes: collecting remote sensing images of the surface deformation area, and determining a trend slope of the Normalized Difference Vegetation Index (NDVI) based on the remote sensing images; Obtaining the maximum vegetation coverage rate of the surface deformation area; The second interaction relationship is obtained by fitting the maximum vegetation coverage, the trend slope, and the relationship between the historical soil moisture content and the historical vegetation coverage.

4. The method for monitoring vegetation coverage in mining areas according to claim 2, characterized in that: The obtaining of multiple historical soil moisture contents includes: Acquire multiple historical sinking information and historical deformation information corresponding to each of the historical sinking information; The historical soil moisture content corresponding to each of the historical subsidence information and the historical deformation information is determined according to the first action relationship.

5. The method for monitoring vegetation coverage in mining areas according to claim 4, characterized in that: The method further comprises: The relationship between each of the historical subsidence information, the historical deformation information and the corresponding historical soil moisture content is fitted to obtain the first interaction relationship, wherein the historical subsidence information includes the subsidence speed of the ground surface, and the historical deformation information includes the curvature and deformation value of the ground surface. The soil moisture content in the first interaction relationship is comprehensively determined based on the subsidence speed, the curvature and the deformation value.

6. A monitoring device for vegetation coverage in mining areas, characterized in that: The device comprises: a first acquisition module configured to acquire subsidence information and deformation information of the ground surface, wherein the subsidence information includes a subsidence amount and a subsidence speed, and the deformation information includes a deformation value and a curvature; acquiring the subsidence information and deformation information of the ground surface includes: determining a subsidence coefficient of the ground surface, wherein the subsidence coefficient is determined based on a maximum subsidence value, an average mining height, an average inclination angle of the coal seam, and a coefficient of a sufficient mining degree along a dip and a strike; acquiring the subsidence amount according to the subsidence coefficient, and determining the subsidence speed of the ground surface based on the subsidence amount; acquiring a main influence radius, wherein the main influence radius is determined based on an average mining depth and a main influence angle of a working face; and acquiring the deformation value based on the main influence radius and the subsidence amount; The second acquisition module is configured to acquire the soil moisture content corresponding to the sinking speed, the deformation value, and the curvature of the ground surface based on a first action relationship, wherein the first action relationship is a relationship between deformation, subsidence, and the soil moisture content established by a multivariate quadratic function model, and the multivariate quadratic function is: ; Wherein, Y is the soil moisture content; a to j are fitting coefficients; V is the sinking velocity; K(x) is the curvature of the ground surface; δ is the deformation value of the ground surface; The determination module is configured to determine the target coverage corresponding to the soil moisture content according to a second action relationship, wherein the second action relationship is a relationship between the vegetation coverage rate and the soil moisture content fitted by a hyperbolic tangent function, and the hyperbolic tangent function is: ;in, is the maximum vegetation coverage; Y is the current soil moisture content; Y0 is the midpoint of the soil moisture content, and S is the trend slope of the normalized difference vegetation index (NDVI); the coefficient of variation of the vegetation is obtained, which is used to characterize the stability of vegetation changes; and the corresponding vegetation restoration strategy is obtained based on the coefficient of variation and the target coverage.

7. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

8. An electronic device, characterized in that: include: a memory having a computer program stored thereon; A processor, configured to execute the computer program in the memory to implement the steps of the method according to any one of claims 1 to 5.

9. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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