Data evaluation method, electronic equipment, storage medium and program product

Abstract

The invention relates to the technical field of data evaluation processing, in particular to a data evaluation method, electronic equipment, a storage medium and a program product, and the method comprises the steps: obtaining a field remote sensing image corresponding to a current moment, and recognizing a region remote sensing image corresponding to a to-be-improved region from the field remote sensing image; spectral data in the area remote sensing image are recognized, improvement parameters corresponding to the area to be improved are determined based on the spectral data, and the improvement parameters comprise the soil salt content, the soil alkalization degree and the soil nitrogen content; determining a corresponding improvement period standard parameter based on the current moment and preset improvement measure information, and evaluating the improvement parameters based on the improvement period standard parameter to obtain a parameter evaluation value of each improvement parameter; and determining a total evaluation value corresponding to the current moment according to each parameter evaluation value, and when the total evaluation value is lower than a preset evaluation standard value, generating abnormal warning information based on each parameter evaluation value. The method is convenient for improving the accuracy of the data evaluation result.

Description

Technical Field

[0001] The present application relates to the technical field of data evaluation and processing, and in particular to a data evaluation method, electronic equipment, storage medium and program product. Background Art

[0002] There are many reasons for the formation of saline-alkali land, mainly including climate factors, topography and geomorphology factors, parent material factors, groundwater level and water quality factors. The soil surface of saline-alkali land is generally covered with a layer of white salt crystals, and the soil has a high pH value. Saline-alkali land has a great inhibitory effect on plant growth. Excessive salt and pH value will cause plant cells to lose water, affect the plant's absorption and utilization of nutrients, and even cause plant death.

[0003] Improvement of saline-alkali land is one of the important ways to achieve sustainable utilization of land resources. Through scientific and reasonable improvement measures, saline-alkali land can be turned into valuable agricultural resources, providing strong support for future agricultural development. Since improvement of saline-alkali land requires a lot of resources, including funds, manpower and time, once inappropriate improvement measures appear in the improvement process, it will not only waste improvement resources, but also may lead to deterioration of soil structure. Therefore, data evaluation of the improvement process is particularly critical. Summary of the invention

[0004] In order to improve the accuracy of data evaluation results, thereby improving the adaptability between saline-alkali land improvement measures and the actual conditions to be improved, the present application provides a data evaluation method, electronic equipment, storage medium and program product.

[0005] In a first aspect, the present application provides a data evaluation method, which adopts the following technical solution: A data evaluation method, comprising: Acquire the on-site remote sensing image corresponding to the current moment, and identify the regional remote sensing image corresponding to the area to be improved from the on-site remote sensing image; Identify spectral data in the remote sensing image of the region, and determine improvement parameters corresponding to the area to be improved based on the spectral data, wherein the improvement parameters include soil salt content, soil alkalinity, and soil nitrogen content; Determine the corresponding improvement period standard parameter based on the current moment and the preset improvement measure information, and evaluate the improvement parameter based on the improvement period standard parameter to obtain a parameter evaluation value of each improvement parameter; The total evaluation value corresponding to the current moment is determined according to each parameter evaluation value, and when the total evaluation value is lower than a preset evaluation standard value, abnormal warning information is generated based on each parameter evaluation value.

[0006] By adopting the above technical solution, the improvement parameters of the corresponding area are located and identified through remote sensing data, which is convenient for reducing the difficulty of field surveys and thus improving the efficiency of survey work. In addition, since remote sensing images can monitor surface changes in real time, remote sensing data is convenient for realizing real-time supervision of the improved area. Since the improvement measures corresponding to different improvement cycles may be different, the improvement effects brought about by the improvement measures in the same cycle may also be different. By accurately locating the corresponding improvement cycle standard parameters at the current moment, and evaluating the improvement parameters corresponding to the current moment based on the improvement cycle standard parameters, instead of using any standard value to evaluate the improvement parameters obtained in different improvement periods, it is convenient to improve the accuracy of the evaluation results. By quantifying the evaluation results to obtain parameter evaluation values, it is convenient to intuitively view and analyze the evaluation effects. Finally, by timely generating abnormal warning information when the total evaluation value is lower than the preset evaluation standard value, it is convenient to timely discover and correct inappropriate improvement measures. By improving the adaptability between the saline-alkali land improvement measures and the actual situation to be improved, the improvement work is ensured to proceed smoothly and achieve the expected results.

[0007] In one possible implementation, the method further includes: Obtain improved parameters and regional remote sensing images corresponding to each evaluation moment within a preset time period; Based on the preset layer, each improved parameter and the regional remote sensing image corresponding to each improved parameter, a remote sensing layer corresponding to each improved parameter is obtained; All remote sensing layers are superimposed according to the evaluation time to determine the salinity change trend diagram of the area to be improved, and the salinity change trend diagram is fed back. The salinity change trend diagram contains the change rate of each improvement parameter.

[0008] By adopting the above technical scheme, by combining the improvement parameters and regional remote sensing images, it is convenient to provide spatial display effects for relevant inspection personnel, so that relevant inspection personnel can view the improvement effects of the areas to be improved in an immersive way. In addition, by converting the improvement parameters corresponding to different evaluation times into remote sensing layers, it is convenient to intuitively view and analyze the salinity change trends corresponding to different evaluation times by overlaying layers, and it is also possible to intuitively view the improvement effects corresponding to any evaluation time by extracting remote sensing layers. By feeding back the generated salinity change trend chart, it is convenient to provide data basis for relevant inspection personnel to optimize or adjust the improvement measures.

[0009] In a possible implementation, when a stage detection instruction is received, the method further includes: Identifying a stage detection date and a stage detection parameter value included in the stage detection instruction; Identify each improved parameter and the change rate corresponding to each improved parameter in the saline-alkali change trend diagram; Based on the stage detection date, the stage detection parameter value and the change rate corresponding to each improved parameter, determine whether each improved parameter in the salinity change trend graph can reach the corresponding stage detection parameter value on the stage detection date; If not, a governance enhancement route is determined based on the salinity change trend diagram, and improvement measures corresponding to the governance enhancement route are adjusted based on the stage detection parameter value to obtain enhanced improvement measures; The governance enhancement route is improved based on the enhancement improvement measures.

[0010] By adopting the above technical solution, by setting the stage detection date, it is convenient to conduct a staged evaluation of the improvement effect, so as to facilitate the summary and staged adjustment of the improvement measures. By analyzing the change rate of each improvement parameter, it is predicted whether each improvement parameter can meet the standard on the stage detection date, so as to facilitate real-time grasp and understanding of the improvement progress. When the improvement progress is lagging behind, the improvement measures corresponding to the governance strengthening route are strengthened to improve the overall improvement progress, thereby improving the convenience of improving the entire area to be improved.

[0011] In a possible implementation, the determining of the governance strengthening route based on the salinity change trend diagram includes: Determine at least one parameter abnormal area from the saline-alkali change trend diagram, wherein the change rate mean of the improved parameter corresponding to each parameter abnormal area is in a different rate mean range, and the change rate mean of the improved parameter corresponding to the parameter abnormal area is lower than the preset rate standard mean; Identify regional edge point information corresponding to each parameter abnormality region from the on-site remote sensing image, determine the cross-region peripheral edge point of each parameter abnormality region based on each regional edge point information, and determine the cross-region width corresponding to each parameter abnormality region based on the cross-region peripheral edge point of each parameter abnormality region; Determine the width adjustment value of the rate mean range corresponding to each parameter abnormal area based on the rate mean range and the width adjustment mapping relationship corresponding to each parameter abnormal area, wherein the width adjustment mapping relationship is the corresponding relationship between the rate mean range and the width adjustment value; Determine a final cross-region width corresponding to each parameter abnormal region based on the cross-region width and the width adjustment value corresponding to each parameter abnormal region; Based on the cross-regional peripheral edge points corresponding to each final cross-regional width adjustment, determine the final cross-regional peripheral edge points corresponding to each parameter abnormality area, connect each final cross-regional peripheral edge point, and determine the governance strengthening route.

[0012] By adopting the above technical solution, the salinity change trend diagram is subdivided by improving the change rate, so as to improve the management accuracy in the improvement process. By comparing the change rate mean corresponding to each parameter abnormal area with the preset rate standard mean, it is convenient to quickly determine the key focus areas, so as to provide data support for subsequent resource allocation. In addition, according to the rate mean range of the parameter abnormal area, the corresponding final cross-regional peripheral edge point is determined, so as to improve the adaptability between the governance enhancement route and the actual improvement situation, so as to improve the accuracy of the instruction enhancement route.

[0013] In one possible implementation, the method further includes: Identifying the impact area of ​​the governance enhancement route from the on-site remote sensing image, and identifying the directly affected crops corresponding to the governance enhancement route and the indirectly affected crops corresponding to the impact area; Acquire soil parameters and environmental parameters of the enhanced governance route and the affected area, wherein the environmental parameters include temperature, humidity and light intensity; Determine a saline-alkali land simulation model based on the soil parameters and the environmental parameters, and drive the saline-alkali land simulation model to perform simulation based on the enhanced improvement measures to obtain the directly affected growth characteristics corresponding to the directly affected crops and the indirectly affected growth characteristics corresponding to the indirectly affected crops; When the directly affecting growth characteristics and the indirectly affecting growth characteristics do not include the preset abnormal growth characteristics, the governance enhancement route is improved based on the enhanced improvement measures.

[0014] By adopting the above technical scheme, after the enhanced improvement measures are determined, the enhanced management route is not directly improved according to the enhanced improvement measures, but the directly affected crops corresponding to the enhanced management route and the indirectly affected crops corresponding to the affected area are determined, and then the impact on crops when the enhanced management route is improved based on the enhanced improvement measures is determined through model simulation. By identifying the growth characteristics of directly affected crops and indirectly affected crops, the feasibility of the enhanced improvement measures is evaluated, so as to reduce the impact of inappropriate improvement measures on crop growth.

[0015] In a possible implementation manner, the step of identifying the impact area of ​​the governance enhancement route from the on-site remote sensing image includes: Identify the change rate of each improved parameter in the salinity change trend diagram, and determine the mean change rate corresponding to the enhanced governance route based on the change rates of all improved parameters; Based on the mapping relationship between the mean change rate and the impact width, determining the impact width value of the impact area corresponding to the enhanced governance route, wherein the impact width mapping relationship is the corresponding relationship between the mean change rate and the impact width value; The impact length value of the governance reinforcement route is identified, and a first impact area and a second impact area are determined on both sides of the governance reinforcement route based on the impact length value and the impact width value. The first impact area and the second impact area constitute the impact area.

[0016] By adopting the above technical solution, the impact width value of the impact area is determined by improving the rate of change of the parameters, rather than using a fixed width value to determine the corresponding impact area, which facilitates improving the adaptability between the impact area and the actual impact situation, thereby facilitating improving the accuracy of determining the impact area corresponding to the governance enhancement route.

[0017] In a second aspect, the present application provides an electronic device, which adopts the following technical solution: An electronic device, comprising: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the above data evaluation method.

[0018] In a third aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium includes: a computer program that can be loaded by a processor and execute the above data evaluation method.

[0019] In a fourth aspect, the present application provides a computer program product, which adopts the following technical solution: A computer program product comprises a computer program, wherein when the computer program is executed by a processor, the data evaluation method is implemented.

[0020] In summary, the present application includes at least one of the following beneficial technical effects: By locating and identifying the improvement parameters of the corresponding area through remote sensing data, it is convenient to reduce the difficulty of field surveys and thus improve the efficiency of survey work. In addition, since remote sensing images can monitor surface changes in real time, remote sensing data can be used to realize real-time supervision of the improved area. Since the improvement measures corresponding to different improvement cycles may be different, the improvement effects brought about by the improvement measures in the same cycle may also be different. By accurately locating the corresponding improvement cycle standard parameters at the current moment, and evaluating the improvement parameters corresponding to the current moment based on the improvement cycle standard parameters, instead of using any standard value to evaluate the improvement parameters obtained in different improvement periods, it is convenient to improve the accuracy of the evaluation results. By quantifying the evaluation results to obtain parameter evaluation values, it is convenient to intuitively view and analyze the evaluation effects. Finally, by timely generating abnormal warning information when the total evaluation value is lower than the preset evaluation standard value, it is convenient to timely discover and correct inappropriate improvement measures. By improving the adaptability between the saline-alkali land improvement measures and the actual situation to be improved, the improvement work can be carried out smoothly and the expected effect can be achieved.

[0021] By subdividing the salinity change trend chart according to the improved change rate, it is convenient to improve the management accuracy during the improvement process. By comparing the change rate mean corresponding to each parameter abnormal area with the preset rate standard mean, it is convenient to quickly determine the key focus areas, thereby providing data support for subsequent resource allocation. In addition, according to the rate mean range of the parameter abnormal area, the corresponding final cross-regional peripheral edge point is determined, which is convenient to improve the adaptability between the governance enhancement route and the actual improvement situation, thereby improving the accuracy of the instruction enhancement route. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 It is a flow chart of a data evaluation method in an embodiment of the present application; Figure 2 It is a schematic diagram of a process for determining a governance enhancement route in an embodiment of the present application; Figure 3 This is a schematic diagram of an enhanced improvement measure evaluation process in an embodiment of the present application; Figure 4 It is a structural schematic diagram of an electronic device in an embodiment of the present application. DETAILED DESCRIPTION

[0023] The following is combined with Figure 1-4 This application is described in further detail.

[0024] After reading this specification, those skilled in the art may make non-creative modifications to this embodiment as needed, but such modifications are protected by patent law as long as they are within the scope of the claims of this application.

[0025] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with 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 this application.

[0026] It should be noted that in the optional embodiments of the present application, the object information and other related data involved, when the embodiments in the present application are applied to specific products or technologies, need to obtain the permission or consent of the object, and the collection, use and processing of the relevant data need to comply with the relevant laws, regulations and standards of the relevant countries and regions. In other words, if the embodiments of the present application involve data related to the object, it needs to be obtained with the authorization and consent of the object, the authorization and consent of the relevant departments, and in compliance with the relevant laws, regulations and standards of the country and region. If personal information is involved in the embodiments, the acquisition of all personal information needs to obtain the consent of the individual. If sensitive information is involved, the separate consent of the information subject needs to be obtained. The embodiments also need to be implemented with the authorization and consent of the object.

[0027] Specifically, the embodiment of the present application provides a data evaluation method, which is executed by an electronic device, which can be a server or a terminal device, wherein the server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides cloud computing services. The terminal device can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc., but is not limited thereto. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, which is not limited in the embodiment of the present application.

[0028] refer to Figure 1 , Figure 1 is a flow chart of a data evaluation method in an embodiment of the present application, the method comprising steps S110 to S140, wherein: Step S110: Acquire the on-site remote sensing image corresponding to the current moment, and identify the regional remote sensing image corresponding to the area to be improved from the on-site remote sensing image.

[0029] Specifically, the on-site remote sensing image can be obtained by drone equipment, ground remote sensing equipment or satellite remote sensing with access rights. The specific acquisition method is not specifically limited in the embodiment of the present application. When the drone equipment is used for acquisition, the corresponding drone equipment can be controlled in advance to collect images according to the preset flight trajectory and then uploaded to the electronic device. The on-site remote sensing image corresponding to the current moment can be determined from the collected remote sensing image by frame extraction technology. In order to facilitate management and detection, the site to be improved is generally divided into multiple areas to be improved. Any area to be improved can be identified from the on-site remote sensing image by edge detection or feature recognition. Since different areas to be improved have different regional features or regional identifiers, the regional features may include texture, shape, etc. The specific regional features are not specifically limited in the embodiment of the present application. The regional features extracted from the on-site remote sensing image are matched with the target regional features corresponding to each pre-defined area to be improved, so as to realize the recognition of the regional remote sensing image corresponding to the area to be improved from the on-site remote sensing image. The specific identification method is not specifically limited in the embodiment of the present application, as long as it can be ensured that the area to be improved is included in the regional remote sensing image.

[0030] Step S120: Identify spectral data in the regional remote sensing image, and determine improvement parameters corresponding to the area to be improved based on the spectral data, the improvement parameters including soil salt content, soil alkalinity, and soil nitrogen content.

[0031] Specifically, a hyperspectral imager can be used to capture regional remote sensing images to obtain spectral band information. By performing band analysis on the obtained spectral band information, the spectral characteristics of different objects can be identified in detail. Multispectral data generally contains multiple spectral band information. Multispectral data refers to combining the spectral band information of an object or scene with spatial information. By measuring and analyzing multiple different spectral band information, the characteristics and properties of the object or scene are obtained. Multispectral data usually contains dozens to hundreds of bands, each of which corresponds to a different spectral range.

[0032] Different improvement parameters correspond to different spectral reflectances. Therefore, by analyzing the spectral reflectances corresponding to different spectral band information, the soil salinity, soil alkalinity and soil nitrogen content contained in the area to be improved can be identified. In order to improve the accuracy of determining the improvement parameters, before performing spectral data recognition on the regional remote sensing image, the remote sensing image can also be preprocessed, for example, radiation calibration, atmospheric correction and other operations, to reduce the interference that external factors may cause to the recognition results. The specific implementation method of determining the improvement parameters corresponding to the area to be improved based on the regional remote sensing image is not specifically limited in the embodiments of the present application. In addition, the improvement parameters include but are not limited to soil salt content, soil alkalinity, and soil nitrogen content. The specific content can be adjusted or set by relevant technical personnel according to actual needs.

[0033] Step S130: determining corresponding improvement cycle standard parameters based on the current time and preset improvement measure information, and evaluating the improvement parameters based on the improvement cycle standard parameters to obtain parameter evaluation values ​​of each improvement parameter.

[0034] Specifically, the improvement parameters corresponding to the area to be improved can reflect the improvement effect of the area to be improved, that is, the improvement process of the area to be improved can be evaluated based on the improvement parameters. As the improvement work progresses, the soil conditions in the area to be improved may be improved, for example, the soil salt content may be reduced. Therefore, the improvement measures corresponding to different periods may be different, and the standard parameters of the improvement period may also be different. The preset improvement measure information contains the improvement measure information corresponding to each improvement period. The specific content of the preset improvement measure information is not specifically limited in the embodiment of this application, and can be determined by relevant staff based on experimental data or historical experience and uploaded to the electronic device. For example, the preset improvement measure information may include three improvement cycles, namely 1-3 months, 3-12 months and 1-3 years. Among them, 1-3 months are short-term improvement measures, which can mainly reduce the rise of salinity by digging deep drainage ditches and lowering the groundwater level. At the same time, fresh water flushing can help quickly reduce the salt content in the soil; 3-12 months are medium-term improvement measures, which can mainly cover the surface of the saline-alkali land with a layer of organic materials, such as straw, stalks, etc., which can not only reduce water evaporation and inhibit the rise of salt, but also gradually improve the soil structure. In addition, in the improvement process, you can also choose to plant some salt-alkali tolerant crops, such as Suaeda salsa, Puccinellia littoralis, etc., to improve soil conditions by planting crops; 1-3 years are long-term improvement measures, which can be achieved by using special soil conditioners, such as gypsum, phosphogypsum, etc., to reduce the salinity of the soil by allowing the soil conditioner to react with the sodium ions in the soil. You can also choose to plant salt-alkali tolerant vegetation, such as Salix babylonica and Elaeagnus angustifolia, to improve the soil environment while reducing the risk of soil erosion.

[0035] Therefore, when evaluating the collected improvement parameters, no single standard is used for evaluation. Instead, it is necessary to first determine the corresponding improvement cycle based on the current moment, and then evaluate the collected improvement parameters based on the improvement cycle standard parameters corresponding to the improvement cycle. After evaluation, the parameter evaluation value corresponding to each improvement parameter can be determined. The higher the parameter evaluation value, the more the corresponding improvement parameter fits the corresponding standard.

[0036] Step S140: Determine the total evaluation value corresponding to the current moment according to each parameter evaluation value, and when the total evaluation value is lower than a preset evaluation standard value, generate abnormal warning information based on each parameter evaluation value.

[0037] Specifically, after determining the parameter evaluation value corresponding to each improved parameter collected at the current moment, the total evaluation value corresponding to all parameter evaluation values ​​at the current moment is calculated, and the total evaluation value is compared with the preset evaluation standard value. If the total evaluation value corresponding to the current moment is not lower than the preset evaluation standard value, it indicates that the corresponding evaluation measures at the current moment are compatible with the actual saline-alkali land situation, and there is no need to adjust or optimize the improvement measures; if the total evaluation value corresponding to the current moment is lower than the preset evaluation standard value, it indicates that the corresponding evaluation measures at the current moment are not compatible with the actual saline-alkali land situation, and the improvement measures may need to be adjusted or optimized. Among them, the specific value of the preset evaluation standard value is not specifically limited in the embodiment of the present application, and can be set by relevant technical personnel. By feeding back the generated abnormal warning information, it is convenient to prompt relevant staff.

[0038] For the embodiments of the present application, by locating and identifying the improvement parameters of the corresponding area through remote sensing data, it is convenient to reduce the difficulty of field surveys and thus improve the efficiency of survey work. In addition, since remote sensing images can monitor surface changes in real time, remote sensing data is convenient for realizing real-time supervision of the improved area. Since the improvement measures corresponding to different improvement cycles may be different, the improvement effects brought about by the improvement measures in the same cycle may also be different. By accurately locating the corresponding improvement cycle standard parameters at the current moment, and evaluating the improvement parameters corresponding to the current moment based on the improvement cycle standard parameters, instead of using any standard value to evaluate the improvement parameters obtained in different improvement periods, it is convenient to improve the accuracy of the evaluation results. By quantifying the evaluation results to obtain parameter evaluation values, it is convenient to intuitively view and analyze the evaluation effects. Finally, by timely generating abnormal warning information when the total evaluation value is lower than the preset evaluation standard value, it is convenient to timely discover and correct inappropriate improvement measures. By improving the adaptability between the saline-alkali land improvement measures and the actual situation to be improved, the improvement work can be carried out smoothly and the expected effect can be achieved.

[0039] Furthermore, the method provided in the embodiment of the present application also includes: obtaining the improvement parameters and regional remote sensing images corresponding to each evaluation moment within a preset time period; obtaining the remote sensing layer corresponding to each improved parameter based on the preset layer, each improved parameter and the regional remote sensing image corresponding to each improved parameter; superimposing all remote sensing layers according to the evaluation time, determining the salinity change trend diagram of the area to be improved, and feeding back the salinity change trend diagram, which includes the change rate of each improved parameter.

[0040] Specifically, the duration corresponding to the preset time period can be 5 days, 7 days, or 10 days. The specific duration is not specifically limited in the embodiments of the present application. The evaluation moment corresponds to the evaluation frequency. Under different evaluation frequencies, the number of evaluation moments generated in the same preset time period is different. The corresponding regional remote sensing image can be collected at each evaluation moment, and the improved parameters corresponding to each evaluation moment can also be obtained based on the regional remote sensing image.

[0041] For any evaluation moment, the improvement parameters corresponding to the evaluation moment and the regional remote sensing image are superimposed to obtain a superimposed remote sensing image. Based on the superimposed remote sensing image, the soil conditions and specific improvement parameters of the corresponding area to be improved can be determined. Since different soil conditions are displayed differently in regional remote sensing images, the regional remote sensing images corresponding to different evaluation moments may be different. Based on the above method, a superimposed remote sensing image corresponding to each evaluation moment can be obtained. In order to facilitate the comparison of superimposed remote sensing images at different evaluation moments, the superimposed remote sensing images corresponding to different evaluation moments can be integrated into different preset layers to obtain remote sensing layers. By changing the layer display mode, it is convenient to arbitrarily combine the evaluation moments, and then compare the corresponding remote sensing layers under any combination. Among them, when fusing the superimposed remote sensing image with the corresponding preset layer, it is necessary to ensure that the superimposed remote sensing image and the corresponding preset layer are in the same coordinate system to facilitate improving the fusion accuracy, wherein the preset layer is the basic map data such as terrain and road grid corresponding to the area to be improved. The method of fusing the superimposed remote sensing image with the corresponding preset layer is not specifically limited in the embodiment of the present application, as long as the remote sensing layer corresponding to each improvement parameter can be obtained after the layer fusion.

[0042] For the convenience of management, the transparency of each remote sensing layer can be adjusted, and then sorted according to the evaluation time. It can be sorted from early to late in the evaluation time to superimpose all remote sensing layers. By superimposing the remote sensing layers after adjusting the transparency, the remote sensing images at the lower layer can also be displayed, so as to facilitate the comprehensive evaluation of the improvement conditions corresponding to multiple evaluation times. Since different remote sensing layers correspond to the same preset layers, the change rate of each improvement parameter at the same location can be determined by superimposing all remote sensing layers. After determining the change rate of each improvement parameter, data can be superimposed in the superimposed remote sensing layers to form a salinity change trend map of the area to be improved.

[0043] By converting the improvement parameters corresponding to different evaluation times into remote sensing layers, it is convenient to intuitively view and analyze the salinity change trends corresponding to different evaluation times by overlaying layers. In addition, the improvement effect corresponding to any evaluation time can be intuitively viewed by extracting remote sensing layers. By feeding back the generated salinity change trend chart, it is convenient to provide data basis for relevant testing personnel to optimize or adjust improvement measures.

[0044] Furthermore, in order to improve the convenience of improving the entire area to be improved, when a stage detection instruction is received, the method provided in the embodiment of the present application further includes: Identify the stage detection date and stage detection parameter value contained in the stage detection instruction; identify each improved parameter and the change rate corresponding to each improved parameter in the saline-alkali change trend diagram; based on the stage detection date, the stage detection parameter value and the change rate corresponding to each improved parameter, determine whether each improved parameter in the saline-alkali change trend diagram can reach the corresponding stage detection parameter value on the stage detection date; if not, determine the governance enhancement route based on the saline-alkali change trend diagram, and adjust the improvement measures corresponding to the governance enhancement route based on the stage detection parameter value to obtain enhanced improvement measures; improve the governance enhancement route based on the enhanced improvement measures.

[0045] Specifically, the phase detection instruction can be issued by the relevant detection personnel through the terminal device. The phase detection instruction is used to conduct phased acceptance of the improvement results in the area to be improved. The detection phase span of the phase detection instruction corresponding to different areas to be improved is different. For example, area a to be improved needs to be tested once every 30 days, and area b to be improved may need to be tested once every 60 days. The date of issuing the phase detection instruction may not be the phase detection date, that is, it may be sent some time before the phase detection date. For example, if the phase detection date is July 3, the date of receiving the phase detection instruction may be June 25. The phase detection parameter value in the phase detection instruction is the node detection parameter value corresponding to each improvement parameter, that is, on the phase detection date, when all the improvement parameters contained in the area to be improved reach the corresponding node detection parameter value, it indicates that the phase detection has met the standard.

[0046] Since the date of receiving the stage detection instruction is generally earlier than the stage detection date, it is necessary to predict all the improvement parameters in the area to be improved based on the salinity-alkali change trend chart, whether they will reach the corresponding stage detection parameter values ​​on the stage detection date. The specific prediction method can be to calculate according to each improvement parameter and the corresponding change rate of each improvement parameter in the salinity-alkali change trend chart. If, on the basis of the improvement parameters, the changes are made according to the corresponding change rates and cannot reach the corresponding stage detection parameter values ​​on the stage detection date, then it is necessary to strengthen the management of the area to be improved, that is, it is necessary to strengthen the control of the corresponding improvement measures in the area to be improved, so that each improvement parameter in the area to be improved can reach the corresponding stage detection parameter value on the stage detection date.

[0047] When it is necessary to strengthen the improvement measures corresponding to the area to be improved, comprehensive adjustments can be made on the basis of the original improvement measures, or the route for strengthening governance can be determined based on the salinity change trend map, that is, for areas that need to be strengthened, only the strengthening governance route will be strengthened. The strengthening governance route is an area with a slow rate of change of improvement parameters or high improvement parameters. Since the salinity change map is obtained by superimposing the improvement conditions corresponding to each evaluation moment, the corresponding strengthening governance route can be directly determined through the salinity change trend map, and finally the strengthening governance route is improved based on the strengthening improvement measures. When the improvement progress corresponding to the strengthening governance route in the area to be improved is lagging behind, the improvement measures corresponding to the strengthening governance route are strengthened to improve the overall improvement progress, thereby improving the convenience of improving the entire area to be improved.

[0048] Furthermore, in order to improve the adaptability between the governance enhancement route and the actual improvement situation, the governance enhancement route is determined based on the salinity change trend diagram, which may specifically include steps S1 to S5, such as Figure 2 As shown, where: Step S1: Determine at least one parameter abnormality area from the salinity change trend diagram, the change rate mean of the improved parameter corresponding to each parameter abnormality area is in a different rate mean range, and the change rate mean of the improved parameter corresponding to the parameter abnormality area is lower than the preset rate standard mean.

[0049] Specifically, the salinity change trend map may include multiple improvement pilot sites. The pilot improvement parameters corresponding to each improvement pilot site can be further identified through regional remote sensing images. The pilot change rate corresponding to each pilot improvement parameter can be determined according to the salinity change trend. The mean change rates of all pilot sites are calculated to obtain the mean change rate of the pilot area corresponding to each improvement pilot site. Different improvement pilot areas have different corresponding change rate means. The change rate mean corresponding to each improvement pilot area is compared with the preset rate standard mean. If the change rate mean corresponding to the improvement pilot area is lower than the preset rate standard mean, the improvement pilot area is determined to be a parameter abnormality area. The number of parameter abnormality areas is not specifically limited in the embodiment of the present application, and can be 0, 1 or more.

[0050] Since different parameter abnormality areas correspond to different mean values ​​of the change rates, the mean rate ranges of the mean change rates corresponding to different parameter abnormality areas may also be different. The mean rate range can be determined by relevant staff based on experimental data and uploaded to the electronic device. The specific content is not specifically limited in the embodiments of the present application.

[0051] Step S2: Identify the regional edge point information corresponding to each parameter abnormality area from the on-site remote sensing image, determine the cross-regional peripheral edge points of each parameter abnormality area based on each regional edge point information, and determine the cross-regional width corresponding to each parameter abnormality area based on the cross-regional peripheral edge points of each parameter abnormality area.

[0052] Specifically, the regional edge point information of each parameter abnormality region can be determined from the on-site remote sensing image by feature recognition. For the convenience of description, each parameter abnormality region in the embodiment of the present application can be circular. Then, the cross-region peripheral edge point of each parameter abnormality region is the endpoint of any diameter in the corresponding parameter abnormality region, and the length corresponding to any diameter is the cross-region width of the corresponding parameter abnormality region. When the shape corresponding to the parameter abnormality region is an irregular shape, the maximum cross-region width of the parameter abnormality region can be determined first, and then the endpoint of the line segment corresponding to the maximum cross-region width can be determined as the cross-region peripheral edge point.

[0053] Step S3: Based on the rate mean range and width adjustment mapping relationship corresponding to each parameter abnormal area, determine the width adjustment value of the rate mean range corresponding to each parameter abnormal area, and the width adjustment mapping relationship is the corresponding relationship between the rate mean range and the width adjustment value.

[0054] Specifically, since different parameter abnormality areas correspond to different rate mean ranges, the corresponding width adjustment value can be determined based on the rate mean ranges corresponding to different parameter abnormality areas and the width adjustment mapping relationship, where the width adjustment mapping relationship includes width adjustment values ​​for different rate mean ranges. The mapping relationship can be determined by relevant staff based on historical operating experience and then uploaded to the electronic device. The specific content is not specifically limited in the embodiments of the present application.

[0055] Step S4: Based on the cross-region width and the width adjustment value corresponding to each parameter abnormal region, determine the final cross-region width corresponding to each parameter abnormal region.

[0056] Specifically, after determining the width adjustment value corresponding to each parameter abnormal area, the corresponding cross-region width can be adjusted based on the width adjustment value, and the cross-region peripheral edge points can be adjusted by adjusting the cross-region width. For example, in the salinity change trend diagram, the cross-region width is 10 cm, and the corresponding cross-region peripheral edge points are (2, 0) and (12, 0). The width adjustment value is 2 cm. After adjusting the cross-region width according to the width adjustment value, the final cross-region width is 12 cm, and the final cross-region peripheral edge points after adjustment are (1, 0) and (13, 0).

[0057] Step S5: Based on the cross-regional peripheral edge points corresponding to each final cross-regional width adjustment, determine the final cross-regional peripheral edge points corresponding to each parameter abnormality area, connect each final cross-regional peripheral edge point, and determine the governance enhancement route.

[0058] Specifically, after determining the final cross-regional peripheral edge point corresponding to each parameter abnormal area, connecting each final cross-regional peripheral edge point, the corresponding governance enhancement route of all parameter abnormal areas can be obtained, and the area corresponding to the governance enhancement route is a part of all parameter abnormal areas. By comparing the mean change rate corresponding to each parameter abnormal area with the preset rate standard mean, it is convenient to quickly determine the key focus area, so as to provide data support for subsequent resource allocation.

[0059] In order to further reduce the impact of inappropriate improvement measures on crop growth, the method provided in the embodiment of the present application further includes steps Sa1 to Sa4, such as Figure 3 As shown, where: Step Sa1: Identify the impact area of ​​the governance enhancement route from the on-site remote sensing image, and identify the directly affected crops corresponding to the governance enhancement route and the indirectly affected crops corresponding to the impact area.

[0060] Specifically, the impact area of ​​the enhanced governance route is located on both sides of the enhanced governance route. When the enhanced improvement measures are used to improve the enhanced governance route, it may affect the soil conditions in the surrounding areas, which may affect the health of the corresponding crops planted in the surrounding areas. Therefore, when using enhanced improvement measures to enhance the improvement of the enhanced governance route, it is necessary to analyze whether the health status of the directly affected crops corresponding to the enhanced governance route and the indirectly affected crops corresponding to the affected areas will be affected.

[0061] Furthermore, in order to improve the accuracy of determining the impact area corresponding to the governance enhancement route, the impact area of ​​the governance enhancement route is identified from the on-site remote sensing image, including: Identify the change rate of each improvement parameter in the salinity change trend diagram, and determine the mean change rate corresponding to the enhanced governance route based on the change rate of all improvement parameters; determine the influence width value of the impact area corresponding to the enhanced governance route based on the mapping relationship between the mean change rate and the influence width, and the influence width mapping relationship is the correspondence between the mean change rate and the influence width value; identify the influence length value of the enhanced governance route, and determine the first influence area and the second influence area on both sides of the enhanced governance route based on the influence length value and the influence width value. The first influence area and the second influence area constitute the influence area.

[0062] Specifically, the mean change rate corresponding to each improved pilot in the governance enhancement route is identified, and the mean change rate of multiple improved pilots is averaged to obtain the mean change rate corresponding to the governance enhancement route. Different mean change rates correspond to different impact width values. The impact width value corresponding to each mean change rate can be determined according to the impact width mapping relationship. The specific content of the impact width mapping relationship is not specifically limited in the embodiments of this application. The impact length value of the governance enhancement route can be identified by an edge detection algorithm. The impact length value is the side length of the governance enhancement route. The length of the first impact area and the second impact area is the impact length value, and the width is the determined impact width value. The first impact area and the second impact area are aligned with the governance enhancement route.

[0063] By improving the rate of change of parameters to determine the impact width value of the impact area, rather than using a fixed width value to determine the corresponding impact area, it is convenient to improve the adaptability between the impact area and the actual impact situation, thereby facilitating the improvement of the accuracy of determining the impact area corresponding to the governance enhancement route.

[0064] Step Sa2: Obtain soil parameters and environmental parameters of the governance enhancement route and the affected area. The environmental parameters include temperature, humidity and light intensity.

[0065] Step Sa3: Determine the saline-alkali land simulation model based on soil parameters and environmental parameters, and drive the saline-alkali land simulation model to simulate based on enhanced improvement measures to obtain direct growth characteristics corresponding to direct impact on crops and indirect growth characteristics corresponding to indirect impact on crops.

[0066] Specifically, by obtaining the soil parameters and environmental parameters of the governance enhancement routes and the affected areas, it is convenient to drive the simulation of the governance enhancement routes and the affected areas. Since the temperature, humidity and light intensity included in the environmental parameters may affect the improvement effect, when constructing the corresponding saline-alkali land simulation model, it is necessary to refer to the soil parameters and environmental parameters. The environmental parameters include but are not limited to temperature, humidity and light intensity. The specific content can be set according to the actual needs of relevant technical personnel.

[0067] The determined saline-alkali land simulation model can simulate and predict the growth status of crops planted in the enhanced management route and the affected area when the enhanced improvement measures are applied for improvement operations. It can be specifically reflected by observing the direct growth characteristics of direct impact on crops and the indirect growth characteristics of indirect impact on crops.

[0068] Step Sa4: When the directly affecting growth characteristics and the indirectly affecting growth characteristics do not contain the preset abnormal growth characteristics, the governance enhancement route is improved based on the enhanced improvement measures.

[0069] Specifically, the preset abnormal growth characteristics may be dead leaves, deformed fruits, spots on the stem, swollen stems, etc. When any of the preset abnormal growth characteristics appears in the growth characteristics corresponding to the direct impact on crops or the indirect impact on crops, it can be characterized that the enhanced improvement measures may have an impact on the growth of the planted crops, that is, the enhanced improvement measures may need to be optimized or adjusted. Therefore, after the enhanced improvement measures are determined, the governance enhancement route is not directly improved according to the enhanced improvement measures, but by identifying the growth characteristics that directly affect crops and indirectly affect crops, the feasibility of the enhanced improvement measures is evaluated, so as to reduce the impact of inappropriate improvement measures on crop growth.

[0070] An electronic device is provided in an embodiment of the present application, such as Figure 4 As shown, Figure 4 The electronic device 400 shown includes: a processor 401 and a memory 403. The processor 401 and the memory 403 are connected, such as through a bus 402. Optionally, the electronic device 400 may also include a transceiver 404. It should be noted that in actual applications, the transceiver 404 is not limited to one, and the structure of the electronic device 400 does not constitute a limitation on the embodiments of the present application.

[0071] Processor 401 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of this application. Processor 401 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0072] The bus 402 may include a path to transmit information between the above components. The bus 402 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 402 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 4 The fact that only one line is used in the diagram does not mean that there is only one bus or only one type of bus.

[0073] The memory 403 may be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0074] The memory 403 is used to store the application code for executing the solution of the present application, and the execution is controlled by the processor 401. The processor 401 is used to execute the application code stored in the memory 403 to implement the contents shown in the above method embodiment.

[0075] The electronic devices include, but are not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), and fixed terminals such as digital TVs, desktop computers, etc. It can also be a server, etc. Figure 4 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0076] An embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer-readable storage medium is run on a computer, the computer can execute the corresponding content in the aforementioned method embodiment.

[0077] An embodiment of the present application provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the method in any of the above embodiments is implemented.

[0078] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0079] The above is only a partial implementation method of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A data evaluation method, It is characterized in that include: Acquire the on-site remote sensing image corresponding to the current moment, and identify the regional remote sensing image corresponding to the area to be improved from the on-site remote sensing image; Identify spectral data in the remote sensing image of the region, and determine improvement parameters corresponding to the area to be improved based on the spectral data, wherein the improvement parameters include soil salt content, soil alkalinity, and soil nitrogen content; Determine the corresponding improvement period standard parameter based on the current moment and the preset improvement measure information, and evaluate the improvement parameter based on the improvement period standard parameter to obtain a parameter evaluation value of each improvement parameter; The total evaluation value corresponding to the current moment is determined according to each parameter evaluation value, and when the total evaluation value is lower than a preset evaluation standard value, abnormal warning information is generated based on each parameter evaluation value.

2. A data evaluation method according to claim 1, It is characterized in that Also includes: Obtain improved parameters and regional remote sensing images corresponding to each evaluation moment within a preset time period; Based on the preset layer, each improved parameter and the regional remote sensing image corresponding to each improved parameter, a remote sensing layer corresponding to each improved parameter is obtained; All remote sensing layers are superimposed according to the evaluation time to determine the salinity change trend diagram of the area to be improved, and the salinity change trend diagram is fed back. The salinity change trend diagram contains the change rate of each improvement parameter.

3. A data evaluation method according to claim 2, It is characterized in that When a stage detection instruction is received, it also includes: Identifying a stage detection date and a stage detection parameter value included in the stage detection instruction; Identify each improved parameter and the change rate corresponding to each improved parameter in the saline-alkali change trend diagram; Based on the stage detection date, the stage detection parameter value and the change rate corresponding to each improved parameter, determine whether each improved parameter in the salinity change trend graph can reach the corresponding stage detection parameter value on the stage detection date; If not, a governance enhancement route is determined based on the salinity change trend diagram, and improvement measures corresponding to the governance enhancement route are adjusted based on the stage detection parameter value to obtain enhanced improvement measures; The governance enhancement route is improved based on the enhancement improvement measures.

4. A data evaluation method according to claim 3, It is characterized in that The method of determining a governance strengthening route based on the salinity change trend diagram includes: Determine at least one parameter abnormality region from the saline-alkali change trend diagram, wherein the change rate mean of the improved parameter corresponding to each parameter abnormality region is in a different rate mean range, and the change rate mean of the improved parameter corresponding to the parameter abnormality region is lower than the preset rate standard mean; Identify regional edge point information corresponding to each parameter abnormality region from the on-site remote sensing image, determine the cross-region peripheral edge point of each parameter abnormality region based on each regional edge point information, and determine the cross-region width corresponding to each parameter abnormality region based on the cross-region peripheral edge point of each parameter abnormality region; Determine the width adjustment value of the rate mean range corresponding to each parameter abnormal area based on the rate mean range and the width adjustment mapping relationship corresponding to each parameter abnormal area, wherein the width adjustment mapping relationship is the corresponding relationship between the rate mean range and the width adjustment value; Determine a final cross-region width corresponding to each parameter abnormal region based on the cross-region width and the width adjustment value corresponding to each parameter abnormal region; Based on the cross-regional peripheral edge points corresponding to each final cross-regional width adjustment, determine the final cross-regional peripheral edge points corresponding to each parameter abnormality area, connect each final cross-regional peripheral edge point, and determine the governance strengthening route.

5. A data evaluation method according to claim 3, It is characterized in that Also includes: Identifying the impact area of ​​the governance enhancement route from the on-site remote sensing image, and identifying the directly affected crops corresponding to the governance enhancement route and the indirectly affected crops corresponding to the impact area; Acquire soil parameters and environmental parameters of the enhanced governance route and the affected area, wherein the environmental parameters include temperature, humidity and light intensity; Determine a saline-alkali land simulation model based on the soil parameters and the environmental parameters, and drive the saline-alkali land simulation model to perform simulation based on the enhanced improvement measures to obtain the directly affected growth characteristics corresponding to the directly affected crops and the indirectly affected growth characteristics corresponding to the indirectly affected crops; When the directly affecting growth characteristics and the indirectly affecting growth characteristics do not include the preset abnormal growth characteristics, the governance enhancement route is improved based on the enhanced improvement measures.

6. A data evaluation method according to claim 5, It is characterized in that The step of identifying the impact area of ​​the governance enhancement route from the on-site remote sensing image comprises: Identify the change rate of each improved parameter in the salinity change trend diagram, and determine the mean change rate corresponding to the enhanced governance route based on the change rates of all improved parameters; Based on the mapping relationship between the mean change rate and the impact width, determining the impact width value of the impact area corresponding to the enhanced governance route, wherein the impact width mapping relationship is the corresponding relationship between the mean change rate and the impact width value; The impact length value of the governance reinforcement route is identified, and a first impact area and a second impact area are determined on both sides of the governance reinforcement route based on the impact length value and the impact width value. The first impact area and the second impact area constitute the impact area.

7. An electronic device, It is characterized in that The electronic device includes: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute a data evaluation method according to any one of claims 1-6.

8. A computer-readable storage medium, It is characterized in that include: A computer program is stored which can be loaded by a processor and execute a data evaluation method according to any one of claims 1 to 6.

9. A computer program product, It is characterized in that The invention comprises a computer program, which, when executed by a processor, implements the steps of a data evaluation method according to any one of claims 1 to 6.

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