A method and system for evaluating farmland quality

Abstract

The present invention discloses a method and system for evaluating the quality grade of cultivated land, which is applied to the field of intelligent evaluation technology. The method includes: obtaining the cultivated land distribution status and multiple sampling points in the target area; obtaining the basic information and soil information of the sampling points; fitting the missing soil information of the missing sampling points by matching the soil information of the sampling points; and evaluating the quality grade of cultivated land in the process of cultivated land improvement through the basic information and soil information of all sampling points. The present invention effectively supplements the missing soil information caused by soil sensor failure or power failure, thereby making the monitoring of the changes in the quality grade of cultivated land at different time points more accurate, which is conducive to the evaluation of the changes in the quality grade of cultivated land in the process of cultivated land improvement, forming a high-standard farmland quality grade evaluation procedure and technical method suitable for the actual regional situation, and accumulating experience and laying a foundation for the comprehensive evaluation of the quality grade of high-standard farmland.

Description

Technical Field

[0001] The present invention relates to intelligent evaluation technology, and in particular to a method and system for evaluating the quality level of cultivated land. Background Art

[0002] As a basic element of food production and supply, cultivated land is not only a basic resource and condition for human survival, but also a necessary cornerstone for agricultural production and sustainable economic and social development. Changes in its quantity and quality will directly affect food security, agricultural product quality safety and ecological security. In recent years, with the acceleration of industrialization and urbanization, construction land, ecological land withdrawal and agricultural structural adjustment, in addition to the decrease in cultivated land area year by year and the increasing pollution of farmland environment, there are also many problems such as the overall decline in cultivated land quality, uneven spatial distribution of cultivated land resources, increased difficulty in development, consolidation and reclamation, uncoordinated matching of water and soil resources, and increasing scarcity of cultivated land reserve resources. Therefore, it is urgent to optimize the allocation of cultivated land resources, carry out high-standard farmland construction, strengthen cultivated land quality construction and management, and protect and improve cultivated land quality.

[0003] In order to accurately evaluate the quality of cultivated land, it is necessary to obtain relevant data on the cultivated land. In order to reduce labor costs, existing data collection often uses soil sensors to obtain parameters such as pH value, inorganic content, heavy metal content, etc.; however, soil sensors may run out of power or malfunction during use, resulting in the loss of relevant monitoring data for a period of time, affecting the evaluation of cultivated land quality during the process of cultivated land improvement. Summary of the invention

[0004] In order to at least overcome the above-mentioned deficiencies in the prior art, the purpose of the present application is to provide a method and system for evaluating the quality level of cultivated land.

[0005] In a first aspect, an embodiment of the present application provides a method for evaluating the quality level of cultivated land, comprising:

[0006] Acquire the cultivated land distribution status of the target area, and arrange multiple sampling points according to the cultivated land distribution status;

[0007] Obtaining basic information of the sampling points, and deploying sensors at the sampling points to obtain soil information of the sampling points during the process of farmland improvement; the basic information includes at least one of topographic location, farmland forest network, altitude, effective soil layer thickness, texture configuration, plough layer texture and obstacle factors; the soil information includes at least one of pH, available potassium, available phosphorus and alkaline nitrogen;

[0008] When the soil information of any sampling point is missing, the sampling point is regarded as a missing sampling point;

[0009] Find at least two sampling points that best match the missing sampling points as matching sampling points through the basic information and the soil information, and fit the missing soil information of the missing sampling points through the soil information of the matching sampling points;

[0010] The quality grade of cultivated land during the process of cultivated land improvement is evaluated through the basic information and soil information of all the sampling points.

[0011] When implementing the embodiments of the present application, it is necessary to select multiple sampling points based on the distribution status of the cultivated land. The selection needs to follow the following principles: First, the principle of representativeness. Combined with the soil sampling and testing points that have been set up in the cultivated land quality protection and improvement project, full consideration is given to the representativeness of administrative divisions, point distribution, point density, as well as terrain location, soil type, cultivated land utilization method, management level, planting system and other factors, and the sampling points are reasonably and comprehensively arranged in the target area. Second, the principle of uniformity. The sampling points basically and evenly cover the main soil types of cultivated land and all agricultural towns in the target area, and cannot be too concentrated in certain areas or soil types. Third, the principle of fixity. After the field is determined by investigation and sampling, GPS positioning is used in a timely manner to carry out long-term fixed-point investigation and monitoring work. For example, in Figure 2 There are three township areas: Area A, Area B and Area C. The administrative boundaries between each township area are Figure 2 In the figure, the black curve represents each township area, and each township area represents the regional scope of a township. Through the analysis of terrain, soil and other information, the relevant factors of area A and area C are relatively close, so area A and area C are merged into a specific target area, that is, area A and area C within the red line range; and the sampling points are Figure 2 The brown dots in the Figure 2 The horizontal and vertical straight lines in the figure are the latitude and longitude lines, and finally 233 sampling points are obtained.

[0012] In the embodiment of the present application, it is necessary to obtain the basic information and soil information of the sampling point, wherein the basic information is the inherent status information of the sampling point, and the soil information is the information that needs to be continuously monitored by the soil sensor. In actual use, the soil sensor may be limited by factors such as power outages and failures, and data may be missing for a period of time. This data loss will not end until the staff arrives at the soil sensor and performs troubleshooting. This part of the missing data may affect the evaluation of the quality grade of the cultivated land at the sampling point during the process of cultivated land improvement. Therefore, in the embodiment of the present application, a method of fitting the missing soil information of the missing sampling point through similar sampling points is adopted to complete the data.

[0013] In the embodiment of the present application, it is necessary to find at least two matching sampling points to improve the accuracy of the fitted data. Based on the at least two matching sampling points, the corresponding soil information data can be supplemented during the period when the missing sampling point data is missing, so as to facilitate the subsequent evaluation of the quality grade of cultivated land. After the soil information data is completed, the change of the corresponding cultivated land quality grade can be generated according to the change of soil information and basic information in the process of cultivated land improvement, thereby realizing the evaluation of the cultivated land improvement process. Through the above-mentioned technical means, the present application effectively realizes the supplement of the missing soil information caused by soil sensor failure or power failure, so that the monitoring of the change of cultivated land quality grade at different time points is more accurate, which is conducive to the evaluation of the change of cultivated land quality grade in the process of cultivated land improvement, and forms a high-standard farmland cultivated land quality grade evaluation procedure and technical method suitable for the actual region, so as to accumulate experience and lay a foundation for the comprehensive development of high-standard farmland cultivated land quality grade evaluation.

[0014] In a possible implementation, searching for at least two sampling points that best match the missing sampling points as matching sampling points through the basic information and the soil information includes:

[0015] The basic information and the soil information are digitized to form farmland quality index data, and the weight value of each data in the farmland quality index data is obtained as the index weight value;

[0016] The weighted cosine similarity between the cultivated land quality index data when the soil information of the missing sampling point is not missing and the cultivated land quality index data of all the sampling points at the same time is calculated according to the index weight value, and at least two sampling points with the largest weighted cosine similarity are selected as the matching sampling points.

[0017] In a possible implementation manner, fitting the missing soil information of the missing sampling point through the soil information of the matching sampling point includes:

[0018] Marking time nodes in the time sequence to form a marked time sequence; the time nodes include sunrise time, sunset time, rainfall start time and rainfall end time;

[0019] Obtaining the time period in the marked time series corresponding to the missing soil information of the missing sampling point as the time period to be fitted;

[0020] Constructing a soil information curve in the time period to be fitted according to the soil information of the matching sampling points;

[0021] Acquire a fitting function between two adjacent time nodes according to the soil information curve; the independent variable of the fitting function is time, and the dependent variable of the fitting function is the soil information;

[0022] The fitting functions of all the matching sampling points in the same time period are weighted according to the weighted cosine similarity to form a weighted fitting function;

[0023] The soil information of the missing sampling point in the time period to be fitted is fitted by the weighted fitting function along the marked time sequence.

[0024] In a possible implementation manner, weighting the fitting functions of all the matching sampling points in the same time period according to the weighted cosine similarity to form a weighted fitting function includes:

[0025] The weighted cosine similarity is normalized to form a normalized similarity, and the fitting function is weighted by the following formula to form a weighted fitting function:

[0026]

[0027] In the formula, is the weighted fitting function of the j-th soil information, is the normalized similarity corresponding to the i-th matching sampling point, is the fitting function corresponding to the j-th soil information of the ith matching sampling point.

[0028] In a possible implementation, evaluating the quality level of cultivated land during cultivated land improvement using the basic information and the soil information of all the sampling points includes:

[0029] Obtaining the farmland quality index data and the index weight value at the current moment of the sampling point;

[0030] Performing weighted calculation on all the farmland quality index data according to the index weight value to form a comprehensive farmland quality index;

[0031] The sampling points are divided into corresponding cultivated land quality grades according to the positions of the comprehensive cultivated land quality indexes in a preset cultivated land quality grade classification table.

[0032] In the second aspect, the present application also provides a system for evaluating the quality of cultivated land, including:

[0033] A layout unit is configured to obtain the distribution status of cultivated land in the target area and layout a plurality of sampling points according to the distribution status of cultivated land;

[0034] An acquisition unit is configured to acquire basic information of the sampling point, and to arrange sensors at the sampling point to acquire soil information of the sampling point during the process of farmland improvement; the basic information includes at least one of topographic location, farmland forest network, altitude, effective soil layer thickness, texture configuration, plough layer texture and obstacle factors; the soil information includes at least one of pH, available potassium, available phosphorus and alkaline nitrogen;

[0035] A completion unit is configured to, when the soil information of any of the sampling points is missing, use the sampling point as a missing sampling point; search for at least two sampling points that best match the missing sampling point as matching sampling points through the basic information and the soil information, and fit the missing soil information of the missing sampling point through the soil information of the matching sampling points;

[0036] The evaluation unit is configured to evaluate the quality level of cultivated land during the process of cultivated land improvement through the basic information and soil information of all the sampling points.

[0037] In a possible implementation, the completion unit is further configured to:

[0038] The basic information and the soil information are digitized to form farmland quality index data, and the weight value of each data in the farmland quality index data is obtained as the index weight value;

[0039] The weighted cosine similarity between the cultivated land quality index data when the soil information of the missing sampling point is not missing and the cultivated land quality index data of all the sampling points at the same time is calculated according to the index weight value, and at least two sampling points with the largest weighted cosine similarity are selected as the matching sampling points.

[0040] In a possible implementation, the completion unit is further configured to:

[0041] Marking time nodes in the time sequence to form a marked time sequence; the time nodes include sunrise time, sunset time, rainfall start time and rainfall end time;

[0042] Obtaining the time period in the marked time series corresponding to the missing soil information of the missing sampling point as the time period to be fitted;

[0043] Constructing a soil information curve in the time period to be fitted according to the soil information of the matching sampling points;

[0044] Acquire a fitting function between two adjacent time nodes according to the soil information curve; the independent variable of the fitting function is time, and the dependent variable of the fitting function is the soil information;

[0045] The fitting functions of all the matching sampling points in the same time period are weighted according to the weighted cosine similarity to form a weighted fitting function;

[0046] The soil information of the missing sampling point in the time period to be fitted is fitted by the weighted fitting function along the marked time sequence.

[0047] In a possible implementation, the completion unit is further configured to:

[0048] The weighted cosine similarity is normalized to form a normalized similarity, and the fitting function is weighted by the following formula to form a weighted fitting function:

[0049]

[0050] In the formula, is the weighted fitting function of the j-th soil information, is the normalized similarity corresponding to the i-th matching sampling point, is the fitting function corresponding to the j-th soil information of the ith matching sampling point.

[0051] In a possible implementation, the evaluation unit is further configured to:

[0052] Obtaining the farmland quality index data and the index weight value at the current moment of the sampling point;

[0053] Performing weighted calculation on all the farmland quality index data according to the index weight value to form a comprehensive farmland quality index;

[0054] The sampling points are divided into corresponding cultivated land quality grades according to the positions of the comprehensive cultivated land quality indexes in a preset cultivated land quality grade classification table.

[0055] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0056] The present invention effectively supplements the missing soil information caused by soil sensor failure or power outage, thereby making the monitoring of changes in arable land quality grade at different time points more accurate, which is conducive to the evaluation of changes in arable land quality grade during arable land improvement, and forming a high-standard farmland quality grade evaluation procedure and technical method suitable for regional realities, accumulating experience and laying a foundation for comprehensively carrying out high-standard farmland quality grade evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of this application, and do not constitute a limitation of the embodiments of the present invention. In the drawings:

[0058] Figure 1 This is a schematic diagram of the steps of the method of the embodiment of the present application;

[0059] Figure 2 Schematic diagram of the target area and sampling points of the embodiment of the present application. DETAILED DESCRIPTION

[0060] To make the purpose, technical scheme and advantages of the embodiment of the present application clearer, the technical scheme in the embodiment of the present application will be clearly and completely described below in conjunction with the drawings in the embodiment of the present application. It should be understood that the drawings in the present application only serve the purpose of explanation and description and are not used to limit the scope of protection of the present application. In addition, it should be understood that the schematic drawings are not drawn in real proportion. The flowchart used in this application shows the operations implemented according to some embodiments of the embodiment of the present application. It should be understood that the operations of the flowchart can be implemented out of sequence, and the steps without logical context can be reversed in order or implemented simultaneously. In addition, those skilled in the art can add one or more other operations to the flowchart under the guidance of the content of the present application, or remove one or more operations from the flowchart.

[0061] In addition, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0062] Please refer to Figure 1 , which is a flow chart of a method for evaluating the quality grade of cultivated land provided in an embodiment of the present invention. Furthermore, the method for evaluating the quality grade of cultivated land may specifically include the contents described in the following steps S1 to S5.

[0063] S1: Obtain the cultivated land distribution status of the target area, and arrange multiple sampling points according to the cultivated land distribution status;

[0064] S2: obtaining basic information of the sampling points, and placing sensors at the sampling points to obtain soil information of the sampling points during the process of farmland improvement; the basic information includes at least one of topographic location, farmland forest network, altitude, effective soil layer thickness, texture configuration, plough layer texture and obstacle factors; the soil information includes at least one of pH, available potassium, available phosphorus and alkaline nitrogen;

[0065] S3: when the soil information of any sampling point is missing, the sampling point is regarded as a missing sampling point;

[0066] S4: searching for at least two sampling points that best match the missing sampling point as matching sampling points through the basic information and the soil information, and fitting the missing soil information of the missing sampling point through the soil information of the matching sampling points;

[0067] S5: Evaluate the quality level of cultivated land during the process of cultivated land improvement through the basic information and soil information of all the sampling points.

[0068] When implementing the embodiments of the present application, it is necessary to select multiple sampling points based on the distribution status of the cultivated land. The selection needs to follow the following principles: First, the principle of representativeness. Combined with the soil sampling and testing points that have been set up in the cultivated land quality protection and improvement project, full consideration is given to the representativeness of administrative divisions, point distribution, point density, as well as terrain location, soil type, cultivated land utilization method, management level, planting system and other factors, and the sampling points are reasonably and comprehensively arranged in the target area. Second, the principle of uniformity. The sampling points basically and evenly cover the main soil types of cultivated land and all agricultural towns in the target area, and cannot be too concentrated in certain areas or soil types. Third, the principle of fixity. After the field is determined by investigation and sampling, GPS positioning is used in a timely manner to carry out long-term fixed-point investigation and monitoring work. For example, in Figure 2 There are three township areas: Area A, Area B and Area C. The administrative boundaries between each township area are Figure 2 In the figure, the black curve represents each township area, and each township area represents the regional scope of a township. Through the analysis of terrain, soil and other information, the relevant factors of area A and area C are relatively close, so area A and area C are merged into a specific target area, that is, area A and area C within the red line range; and the sampling points are Figure 2 The brown dots in the Figure 2 The horizontal and vertical straight lines in the figure are the latitude and longitude lines, and finally 233 sampling points are obtained.

[0069] In the embodiment of the present application, it is necessary to obtain the basic information and soil information of the sampling point, wherein the basic information is the inherent status information of the sampling point, and the soil information is the information that needs to be continuously monitored by the soil sensor. In actual use, the soil sensor may be limited by factors such as power outages and failures, and data may be missing for a period of time. This data loss will not end until the staff arrives at the soil sensor and performs troubleshooting. This part of the missing data may affect the evaluation of the quality grade of the cultivated land at the sampling point during the process of cultivated land improvement. Therefore, in the embodiment of the present application, a method of fitting the missing soil information of the missing sampling point through similar sampling points is adopted to complete the data.

[0070] In the embodiment of the present application, it is necessary to find at least two matching sampling points to improve the accuracy of the fitted data. Based on the at least two matching sampling points, the corresponding soil information data can be supplemented during the period when the missing sampling point data is missing, so as to facilitate the subsequent evaluation of the quality grade of cultivated land. After the soil information data is completed, the change of the corresponding cultivated land quality grade can be generated according to the change of soil information and basic information in the process of cultivated land improvement, thereby realizing the evaluation of the cultivated land improvement process. Through the above-mentioned technical means, the present application effectively realizes the supplement of the missing soil information caused by soil sensor failure or power failure, so that the monitoring of the change of cultivated land quality grade at different time points is more accurate, which is conducive to the evaluation of the change of cultivated land quality grade in the process of cultivated land improvement, and forms a high-standard farmland cultivated land quality grade evaluation procedure and technical method suitable for the actual region, so as to accumulate experience and lay a foundation for the comprehensive development of high-standard farmland cultivated land quality grade evaluation.

[0071] In a possible implementation, searching for at least two sampling points that best match the missing sampling points as matching sampling points through the basic information and the soil information includes:

[0072] The basic information and the soil information are digitized to form farmland quality index data, and the weight value of each data in the farmland quality index data is obtained as the index weight value;

[0073] The weighted cosine similarity between the cultivated land quality index data when the soil information of the missing sampling point is not missing and the cultivated land quality index data of all the sampling points at the same time is calculated according to the index weight value, and at least two sampling points with the largest weighted cosine similarity are selected as the matching sampling points.

[0074] When implementing the embodiment of the present application, the data process of basic information and soil information is in accordance with GB / T 33469. The Delphi method and the membership function method are combined to determine the membership function of the numerical evaluation index, and the Delphi method is used to directly give the membership degree for the qualitative conceptual evaluation index. The weight acquisition process can be determined by combining the Delphi method with the hierarchical analysis method in accordance with GB / T33469; for example, the corresponding weights of the determined arable land quality index data are shown in Table 1:

[0075] Table 1 Cultivated land quality index data and weight table

[0076]

[0077] Among them, B1, B2, B3, B5 and B6 in the criterion layer are basic information, and B4 is soil information.

[0078] At this time, matching sampling points can be screened based on the indicator weight value. During the screening process, it is necessary to first obtain the arable land quality indicator data at the missing sampling point when the soil information is not missing, and calculate the arable land quality indicator data of other sampling points at the same time. The weighted cosine similarity of the arable land quality indicator data of different sampling points and the arable land quality indicator data at the missing sampling point is calculated through the above-mentioned indicator weight value. At least two most similar sampling points can be obtained as matching sampling points to facilitate subsequent data fitting.

[0079] In a possible implementation manner, fitting the missing soil information of the missing sampling point through the soil information of the matching sampling point includes:

[0080] Marking time nodes in the time sequence to form a marked time sequence; the time nodes include sunrise time, sunset time, rainfall start time and rainfall end time;

[0081] Obtaining the time period in the marked time series corresponding to the missing soil information of the missing sampling point as the time period to be fitted;

[0082] Constructing a soil information curve in the time period to be fitted according to the soil information of the matching sampling points;

[0083] Acquire a fitting function between two adjacent time nodes according to the soil information curve; the independent variable of the fitting function is time, and the dependent variable of the fitting function is the soil information;

[0084] The fitting functions of all the matching sampling points in the same time period are weighted according to the weighted cosine similarity to form a weighted fitting function;

[0085] The soil information of the missing sampling point in the time period to be fitted is fitted by the weighted fitting function along the marked time sequence.

[0086] When implementing the embodiments of the present application, the inventors found in scientific practice that for the monitoring data of the soil sensor, the corresponding attribute changes will be different for different time periods, so it is necessary to perform segmented fitting on the time series; the basic segmented nodes need to include sunrise time, sunset time, rainfall start time and rainfall end time, which can also include fixed watering nodes, fertilization nodes, etc., which will not be repeated in the embodiments of the present application. It should be understood that the selection of matching sampling points generally needs to be near the missing sampling points to meet the requirements of the rainfall nodes. At the same time, if watering nodes and fertilization nodes are added, the synchronization of watering and fertilizing of the two sampling points needs to be met. For mountainous areas, the matching sampling points selected by the above technical solution are generally closer to the missing sampling points. The reason is that the terrain environment in the mountainous areas is more complex, so only the basic information of the matching sampling points that are closer to the missing sampling points will be similar to the basic information of the missing sampling points.

[0087] In the embodiment of the present application, the time period to be fitted that needs to be fitted can be selected from the marked time series by the time period in which the soil information is missing. The main fitting method in the embodiment of the present application is to segment the time period to be fitted according to the time node, and obtain the fitting function of each segment, and the fitting function can be implemented by polynomial fitting, which is not limited in the embodiment of the present application. After obtaining the fitting functions of different matching sampling points in different time periods, all fitting functions in the same time period can be weighted by the weighted cosine similarity obtained by the previous calculation to form a weighted fitting function suitable for the missing sampling point to fit the data in the time period. In the embodiment of the present application, it is necessary to perform data fitting for each subsequent time period in turn from the time when the missing sampling point has data missing to supplement the missing data. The fitting in turn here can refer to the fitting calculation of a time period and then the fitting of the next time period, or it can be the fitting calculation of each time period at the same time, which is not limited in the embodiment of the present application. After the fitting is completed, the missing data part of the missing sampling point will also form a complete data curve, which is convenient for data sampling during subsequent evaluation. Since this part of the real data can also form a complete curve, it is conducive to the evaluation of soil information changes in the process of farmland improvement.

[0088] In a possible implementation manner, weighting the fitting functions of all the matching sampling points in the same time period according to the weighted cosine similarity to form a weighted fitting function includes:

[0089] The weighted cosine similarity is normalized to form a normalized similarity, and the fitting function is weighted by the following formula to form a weighted fitting function:

[0090]

[0091] In the formula, is the weighted fitting function of the j-th soil information, is the normalized similarity corresponding to the i-th matching sampling point, is the fitting function corresponding to the j-th soil information of the ith matching sampling point.

[0092] In a possible implementation, evaluating the quality level of cultivated land during cultivated land improvement using the basic information and the soil information of all the sampling points includes:

[0093] Obtaining the farmland quality index data and the index weight value at the current moment of the sampling point;

[0094] Performing weighted calculation on all the farmland quality index data according to the index weight value to form a comprehensive farmland quality index;

[0095] The sampling points are divided into corresponding cultivated land quality grades according to the positions of the comprehensive cultivated land quality indexes in a preset cultivated land quality grade classification table.

[0096] When implementing the embodiment of the present application, it is necessary to obtain the farmland quality index data and the corresponding index weight value of the sampling point at the current moment. For sampling points without data missing, the farmland quality index data can be generated with the data sampled at the current moment. For sampling points with data missing, the soil information at the current moment can be calculated with the fitted curve, and then the farmland quality index data is generated. The weighted calculated comprehensive farmland quality index can obtain the corresponding farmland quality grade by looking up the table. For example, please refer to Table 2, which gives a specific farmland quality grade classification table:

[0097] Table 2 Classification of cultivated land quality

[0098]

[0099] Based on the same inventive concept, the present application also provides a farmland quality grade evaluation system, including:

[0100] A layout unit is configured to obtain the distribution status of cultivated land in the target area and layout a plurality of sampling points according to the distribution status of cultivated land;

[0101] An acquisition unit is configured to acquire basic information of the sampling point, and to arrange sensors at the sampling point to acquire soil information of the sampling point during the process of farmland improvement; the basic information includes at least one of topographic location, farmland forest network, altitude, effective soil layer thickness, texture configuration, plough layer texture and obstacle factors; the soil information includes at least one of pH, available potassium, available phosphorus and alkaline nitrogen;

[0102] A completion unit is configured to, when the soil information of any of the sampling points is missing, use the sampling point as a missing sampling point; search for at least two sampling points that best match the missing sampling point as matching sampling points through the basic information and the soil information, and fit the missing soil information of the missing sampling point through the soil information of the matching sampling points;

[0103] The evaluation unit is configured to evaluate the quality level of cultivated land during the process of cultivated land improvement through the basic information and soil information of all the sampling points.

[0104] In a possible implementation, the completion unit is further configured to:

[0105] The basic information and the soil information are digitized to form farmland quality index data, and the weight value of each data in the farmland quality index data is obtained as the index weight value;

[0106] The weighted cosine similarity between the cultivated land quality index data when the soil information of the missing sampling point is not missing and the cultivated land quality index data of all the sampling points at the same time is calculated according to the index weight value, and at least two sampling points with the largest weighted cosine similarity are selected as the matching sampling points.

[0107] In a possible implementation, the completion unit is further configured to:

[0108] Marking time nodes in the time sequence to form a marked time sequence; the time nodes include sunrise time, sunset time, rainfall start time and rainfall end time;

[0109] Obtaining the time period in the marked time series corresponding to the missing soil information of the missing sampling point as the time period to be fitted;

[0110] Constructing a soil information curve in the time period to be fitted according to the soil information of the matching sampling points;

[0111] Acquire a fitting function between two adjacent time nodes according to the soil information curve; the independent variable of the fitting function is time, and the dependent variable of the fitting function is the soil information;

[0112] The fitting functions of all the matching sampling points in the same time period are weighted according to the weighted cosine similarity to form a weighted fitting function;

[0113] The soil information of the missing sampling point in the time period to be fitted is fitted by the weighted fitting function along the marked time sequence.

[0114] In a possible implementation, the completion unit is further configured to:

[0115] The weighted cosine similarity is normalized to form a normalized similarity, and the fitting function is weighted by the following formula to form a weighted fitting function:

[0116]

[0117] In the formula, is the weighted fitting function of the j-th soil information, is the normalized similarity corresponding to the i-th matching sampling point, is the fitting function corresponding to the j-th soil information of the ith matching sampling point.

[0118] In a possible implementation, the evaluation unit is further configured to:

[0119] Obtaining the farmland quality index data and the index weight value at the current moment of the sampling point;

[0120] Performing weighted calculation on all the farmland quality index data according to the index weight value to form a comprehensive farmland quality index;

[0121] The sampling points are divided into corresponding cultivated land quality grades according to the positions of the comprehensive cultivated land quality indexes in a preset cultivated land quality grade classification table.

[0122] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0123] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, or it can be an electrical, mechanical or other form of connection.

[0124] The units described as separate components may or may not be physically separated. As units, it is obvious that a person of ordinary skill in the art can realize that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0125] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0126] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a grid device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0127] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for evaluating the quality level of cultivated land, characterized in that: include: Acquire the cultivated land distribution status of the target area, and arrange multiple sampling points according to the cultivated land distribution status; Obtaining basic information of the sampling points, and deploying sensors at the sampling points to obtain soil information of the sampling points during the process of farmland improvement; the basic information includes at least one of topographic location, farmland forest network, altitude, effective soil layer thickness, texture configuration, plough layer texture and obstacle factors; the soil information includes at least one of pH, available potassium, available phosphorus and alkaline nitrogen; When the soil information of any sampling point is missing, the sampling point is regarded as a missing sampling point; Find at least two sampling points that best match the missing sampling points as matching sampling points through the basic information and the soil information, and fit the missing soil information of the missing sampling points through the soil information of the matching sampling points; Evaluating the quality grade of cultivated land during cultivated land improvement by using the basic information and soil information of all the sampling points; Finding at least two sampling points that best match the missing sampling points as matching sampling points through the basic information and the soil information includes: The basic information and the soil information are digitized to form farmland quality index data, and the weight value of each data in the farmland quality index data is obtained as the index weight value; Calculating the weighted cosine similarity between the cultivated land quality index data when the soil information of the missing sampling point is not missing and the cultivated land quality index data of all the sampling points at the same time according to the index weight value, and selecting at least two sampling points with the largest weighted cosine similarity as the matching sampling points; Fitting the missing soil information of the missing sampling point through the soil information of the matching sampling point includes: Marking time nodes in the time sequence to form a marked time sequence; the time nodes include sunrise time, sunset time, rainfall start time and rainfall end time; Obtaining the time period in the marked time series corresponding to the missing soil information of the missing sampling point as the time period to be fitted; Constructing a soil information curve in the time period to be fitted according to the soil information of the matching sampling points; Acquire a fitting function between two adjacent time nodes according to the soil information curve; the independent variable of the fitting function is time, and the dependent variable of the fitting function is the soil information; The fitting functions of all the matching sampling points in the same time period are weighted according to the weighted cosine similarity to form a weighted fitting function; The soil information of the missing sampling points in the time period to be fitted is fitted by using the weighted fitting function along the marked time sequence.

2. A method for evaluating the quality of cultivated land according to claim 1, characterized in that: The step of weighting the fitting functions of all the matching sampling points in the same time period according to the weighted cosine similarity to form a weighted fitting function comprises: The weighted cosine similarity is normalized to form a normalized similarity, and the fitting function is weighted by the following formula to form a weighted fitting function: In the formula, is the weighted fitting function of the j-th soil information, is the normalized similarity corresponding to the i-th matching sampling point, is the fitting function corresponding to the j-th soil information of the ith matching sampling point.

3. A method for evaluating farmland quality according to claim 1, characterized in that: The evaluation of the quality level of cultivated land in the process of cultivated land improvement by using the basic information and soil information of all the sampling points includes: Obtaining the farmland quality index data and the index weight value at the current moment of the sampling point; Performing weighted calculation on all the farmland quality index data according to the index weight value to form a comprehensive farmland quality index; The sampling points are divided into corresponding cultivated land quality grades according to the positions of the comprehensive cultivated land quality indexes in a preset cultivated land quality grade classification table.

4. A system for evaluating the quality of cultivated land, characterized in that: include: A layout unit is configured to obtain the distribution status of cultivated land in the target area and layout a plurality of sampling points according to the distribution status of cultivated land; An acquisition unit is configured to acquire basic information of the sampling point, and to deploy sensors at the sampling point to acquire soil information of the sampling point during the process of farmland improvement; The basic information includes at least one of topographic location, farmland forest network, altitude, effective soil layer thickness, texture configuration, plough layer texture and obstacle factors; the soil information includes at least one of pH, available potassium, available phosphorus and alkaline nitrogen; A completion unit, configured to treat any sampling point as a missing sampling point when the soil information of the sampling point is missing; Find at least two sampling points that best match the missing sampling points as matching sampling points through the basic information and the soil information, and fit the missing soil information of the missing sampling points through the soil information of the matching sampling points; An evaluation unit, configured to evaluate the quality level of cultivated land during the process of cultivated land improvement through the basic information and the soil information of all the sampling points; The completion unit is further configured to: The basic information and the soil information are digitized to form farmland quality index data, and the weight value of each data in the farmland quality index data is obtained as the index weight value; Calculating the weighted cosine similarity between the cultivated land quality index data when the soil information of the missing sampling point is not missing and the cultivated land quality index data of all the sampling points at the same time according to the index weight value, and selecting at least two sampling points with the largest weighted cosine similarity as the matching sampling points; The completion unit is further configured to: Marking time nodes in the time sequence to form a marked time sequence; the time nodes include sunrise time, sunset time, rainfall start time and rainfall end time; Obtaining the time period in the marked time series corresponding to the missing soil information of the missing sampling point as the time period to be fitted; Constructing a soil information curve in the time period to be fitted according to the soil information of the matching sampling points; Acquire a fitting function between two adjacent time nodes according to the soil information curve; the independent variable of the fitting function is time, and the dependent variable of the fitting function is the soil information; The fitting functions of all the matching sampling points in the same time period are weighted according to the weighted cosine similarity to form a weighted fitting function; The soil information of the missing sampling point in the time period to be fitted is fitted by the weighted fitting function along the marked time sequence.

5. A system for evaluating farmland quality according to claim 4, characterized in that: The completion unit is further configured to: The weighted cosine similarity is normalized to form a normalized similarity, and the fitting function is weighted by the following formula to form a weighted fitting function: In the formula, is the weighted fitting function of the j-th soil information, is the normalized similarity corresponding to the i-th matching sampling point, is the fitting function corresponding to the j-th soil information of the ith matching sampling point.

6. A system for evaluating farmland quality according to claim 4, characterized in that: The evaluation unit is further configured to: Obtaining the farmland quality index data and the index weight value at the current moment of the sampling point; Performing weighted calculation on all the farmland quality index data according to the index weight value to form a comprehensive farmland quality index; The sampling points are divided into corresponding cultivated land quality grades according to the positions of the comprehensive cultivated land quality indexes in a preset cultivated land quality grade classification table.

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