Intelligent plot sketching method, device and equipment and storage medium

Abstract

The invention belongs to the field of artificial intelligence, and relates to an intelligent plot sketching method, which comprises the following steps: acquiring a plurality of control points selected by a user on preset map software; simplifying the plurality of control points to obtain a target control point set; according to adjacent target control points in the target control point set, adopting a Bezier curve algorithm to generate a plurality of plot boundary curves; generating a closed polygon according to the plurality of plot boundary curves, obtaining boundary information of the to-be-measured plot, and calculating the plot area of the boundary information by using an area calculation tool; and associating the boundary information with the land parcel area to obtain a sketching result of the to-be-measured land parcel. In addition, the invention also relates to a block chain technology, and the sketching result of the to-be-measured plot and the like can be stored in a block chain. According to the invention, the accuracy of calculating the plot sketching information can be improved.

Description

Technical Field

[0001] This application relates to the field of artificial intelligence, and particularly to an intelligent drawing method for plots of land. Background Art

[0002] Agricultural insurance plays a crucial role in protecting the interests of farmers and promoting the development of modern agriculture. However, in actual operation, the accuracy and efficiency of plot identification and data management have become the key factors restricting the development of agricultural insurance.

[0003] Currently, the traditional plot drawing method has the problem of insufficient accuracy in plot drawing, and there are large errors in the existing tools for plot boundary recognition and area calculation.

[0004] However, the errors in plot boundary and area calculation will cause a deviation between the insured data and the actual situation, which will in turn affect the judgment of the insurance company during compensation and increase the risk of claims disputes. Summary of the Invention

[0005] The purpose of the embodiments of this application is to propose an intelligent drawing method, device, equipment, and storage medium for plots of land, and its main purpose is to improve the accuracy of calculating plot drawing information.

[0006] To solve the above technical problems, the embodiments of this application provide an intelligent drawing method for plots of land, and adopt the following technical solutions:

[0007] Obtain multiple control points selected by the user on a preset map software;

[0008] Simplify the multiple control points to obtain a set of target control points;

[0009] According to adjacent target control points in the set of target control points, use the Bezier curve algorithm to generate multiple plot boundary curves;

[0010] Generate a closed polygon according to the multiple plot boundary curves to obtain the boundary information of the plot to be measured;

[0011] Use an area calculation tool to calculate the plot area of the boundary information;

[0012] Associate the boundary information and the plot area to obtain the drawing result of the plot to be measured.

[0013] Further, the simplifying the multiple control points to obtain a set of target control points includes:

[0014] Step S2021: Select two relatively positioned control points from the multiple control points as connection points, and connect the two connection points to obtain a control line;

[0015] Step S2022: Calculate the vertical distance from each non - connection point among the multiple control points to the control line, obtaining multiple such vertical distances;

[0016] Step S2023: Remove the control points corresponding to the vertical distances less than or equal to a preset simplification threshold, obtaining a new set of multiple control points;

[0017] Based on the new set of multiple control points, iterate from Step S2021 to Step S2023 until the vertical distances from all non - connection points to the control line are greater than the preset simplification threshold, obtaining the target control point set.

[0018] Further, generating multiple plot boundary curves using the Bezier curve algorithm according to adjacent target control points in the target control point set includes:

[0019] According to the curve type of the selected Bezier curve, determine the number of adjacent target control points from the target control point set, and the Bezier curve calculation formula corresponding to the curve type;

[0020] Generate a Bezier curve segment corresponding to the adjacent target control points through the Bezier curve calculation formula and the number of adjacent target control points;

[0021] Traverse all the adjacent target control points in the target control point set, and draw the Bezier curve segments through a preset drawing method to obtain multiple plot boundary curves.

[0022] Further, generating multiple plot boundary curves using the Bezier curve algorithm according to adjacent target control points in the target control point set includes:

[0023] Identify the number of adjacent target control points;

[0024] If the number of adjacent target control points is fixed at two, then according to the curve type of the Bezier curve, determine the number of intermediate points and the Bezier curve calculation formula corresponding to the curve type;

[0025] Generate the corresponding number of intermediate points using a preset intermediate point generation method according to the number of intermediate points;

[0026] Calculate the adjacent target control points and the corresponding number of intermediate points through the Bezier curve calculation formula to generate a Bezier curve segment corresponding to the adjacent target control points;

[0027] Traverse all the adjacent target control points in the target control point set, and draw the Bezier curve segments through a preset drawing method to obtain multiple plot boundary curves.

[0028] Furthermore, the curve type of the Bezier curve is a quadratic Bezier curve, wherein the calculation formula of the quadratic Bezier curve includes:

[0029] B(t)=(1-t) 2 P 0 +2(1-t)tP 1 +t 2 P 2

[0030] Wherein, t refers to the parameter of the quadratic Bezier curve, and t varies between [0,1]. B(t) refers to the position vector of a point on the Bezier curve, which changes with the change of t. 0 , P 1 , P 2 refers to the coordinates of the target control point, where P 0 As the starting point, the P 1 is the middle point, the P 2 For the end point.

[0031] Furthermore, after obtaining the delineation result of the plot to be measured, the method further includes:

[0032] Regularly obtain satellite remote sensing images of the area where the plot to be measured is located, and extract crop characteristics of the plot to be measured based on the satellite remote sensing images;

[0033] Regularly obtain meteorological data collected by meteorological sensors and soil data collected by soil sensors;

[0034] The crop characteristics, meteorological data and soil data are associated with the delineation results of the plot to be measured to obtain associated data of the plot to be measured.

[0035] Furthermore, after associating the crop characteristics, meteorological data and soil data with the delineation result of the plot to be measured to obtain the associated data of the plot to be measured, the method further includes:

[0036] Analyze the associated data of the plot to be measured by using a pre-trained risk assessment model to obtain an analysis result;

[0037] A risk assessment report is generated according to the analysis results.

[0038] In order to solve the above technical problems, the embodiment of the present application further provides an intelligent delineation device for plots of land, which adopts the following technical solution:

[0039] An acquisition module, used to acquire multiple control points selected by a user on a preset map software;

[0040] A simplification module, used for simplifying the multiple control points to obtain a target control point set;

[0041] A first calculation module, configured to generate a plurality of land parcel boundary curves by using a Bezier curve algorithm according to adjacent target control points in the target control point set;

[0042] A generation module, used to generate a closed polygon based on multiple plot boundary curves to obtain boundary information of the plot to be measured;

[0043] A second calculation module is used to calculate the area of ​​the land parcel of the boundary information using an area calculation tool;

[0044] The association module is used to associate the boundary information with the land area to obtain the delineation result of the land to be measured.

[0045] In order to solve the above technical problems, an embodiment of the present application also provides a computer device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the intelligent delineation method of the plot as described above.

[0046] In order to solve the above technical problems, an embodiment of the present application further provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the intelligent delineation method of a plot of land as described above.

[0047] Compared with the prior art, the embodiments of the present application have the following beneficial effects:

[0048] The multiple control points are acquired and simplified to obtain a target control point set, which reduces the computing resources for subsequent plot delineation and improves computing efficiency while ensuring accuracy; and prevents excessive control points from causing an increase in data noise, thereby improving the accuracy of the calculated plot delineation.

[0049] Through the Bezier curve algorithm, an accurate plot boundary curve is generated based on all control points of the target control point set, thereby improving the accuracy of plot boundary delineation; and through the Bezier curve algorithm, automation is achieved, reducing the workload of manual plot boundary drawing, improving work efficiency while reducing the risk of human error, making the generated plot boundary curve more reliable.

[0050] By integrating the plot boundary curve, constructing a closed polygon, and extracting the boundary information of the plot to be measured from the closed polygon, the accuracy of plot boundary calculation is improved. The process of constructing the closed polygon and extracting the boundary information can be automated, greatly improving the data processing efficiency. This reduces the workload of manually drawing the plot boundary, reduces the risk of human error, and makes the generation of the plot boundary faster and more accurate.

[0051] Through the area calculation tool, the area of the plot with boundary information can be calculated in real time, excluding the situation where the calculated area deviates too much from the actual area, improving the accuracy of the drawing of the plot to be measured, and thus reducing the risk of claims disputes.

[0052] By associating the boundary information and the plot area, the drawing result of the plot to be measured is obtained, which can clearly define the boundary and area of the plot to be measured, reduce the error in calculating the plot boundary and area, and improve the accuracy of drawing the plot to be measured. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the solutions in the present application, the following will briefly introduce the drawings required for the description of the embodiments of the present application. Obviously, the drawings below are some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0054] Figure 1 It is an exemplary system architecture diagram to which the present application can be applied;

[0055] Figure 2 It is a flowchart of an embodiment of the intelligent drawing method of the plot according to the present application;

[0056] Figure 3 It is a schematic structural diagram of an embodiment of the intelligent drawing device of the plot according to the present application;

[0057] Figure 4 It is a schematic structural diagram of an embodiment of the device according to the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0058] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs; the terms used in the specification of this application are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" and any variations thereof in the specification and claims of this application and the above drawings are intended to cover non-exclusive inclusion. The terms "first", "second", etc. in the specification and claims of this application or the above drawings are used to distinguish different objects and not to describe a specific order.

[0059] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments can be included in at least one embodiment of the application. The phrase appears in various places in the specification and is not necessarily referring to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive of other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0060] To enable those skilled in the art to better understand the solutions of this application, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0061] As Figure 1 shown, the system architecture 100 may include a terminal device 101, a network 102, and a server 103. The terminal device 101 may be a laptop computer 1011, a tablet computer 1012, or a mobile phone 1013. The network 102 is a medium for providing a communication link between the terminal device 101 and the server 103. The network 102 may include various connection types, such as wired, wireless communication links, or fiber optic cables, etc.

[0062] A user may use the terminal device 101 to interact with the server 103 via the network 102 to receive or send messages, etc. Various communication client applications may be installed on the terminal device 101, such as a web browser application, a shopping application, a search application, an instant messaging tool, an email client, a social platform software, etc.

[0063] The terminal device 101 can be any electronic device with a display screen and supporting web browsing. In addition to a laptop computer 1011, a tablet computer 1012 or a mobile phone 1013, the terminal device 101 can also be an e-book reader, an MP3 player (Moving Picture Experts Group Audio Layer III), an MP4 (Moving Picture Experts Group Audio Layer IV), a laptop computer, a desktop computer, etc.

[0064] The server 103 may be a server that provides various services, such as a background server that provides support for web pages displayed on the terminal device 101 .

[0065] It should be noted that the intelligent delineation method for a plot of land provided in the embodiment of the present application is generally executed by a server / terminal device, and accordingly, the intelligent delineation device for a plot of land is generally arranged in the server / terminal device.

[0066] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to the implementation requirements.

[0067] Continue to refer Figure 2 , shows a flow chart of an embodiment of the intelligent delineation method of a plot of land according to the present application. According to different requirements, the order of the steps in the flow chart can be changed, and some steps can be omitted. The intelligent delineation method of a plot of land provided in the embodiment of the present application can be applied to any scenario that requires intelligent delineation of a plot of land, and the intelligent delineation method of a plot of land can be applied to products in these scenarios. The intelligent delineation method of a plot of land comprises the following steps:

[0068] Step S201: Acquire multiple control points selected by a user on a preset map software.

[0069] In this embodiment, the intelligent delineation method of the above-mentioned land parcel is executed on the electronic device (for example Figure 1 The server / terminal device shown in the figure) can obtain multiple control points through a wired connection or a wireless connection. It should be noted that the above wireless connection method may include but is not limited to 3G / 4G / 5G connection, WiFi connection, Bluetooth connection, WiMAX connection, Zigbee connection, UWB (ultra wideband) connection, and other wireless connection methods currently known or to be developed in the future.

[0070] In this embodiment, the above-mentioned preset map software includes, but is not limited to, Minemap, etc., which has basic functions such as map display, zooming, panning, etc., and allows users to perform interactive operations; the above-mentioned multiple control points refer to the key points representing the plot boundaries.

[0071] Specifically, the user opens the above-mentioned preset map software on a terminal device (such as a mobile phone of a handheld device, an iPad, etc., a computer of a fixed device, etc.). In the preset map software interface, enter the plot drawing module. In the plot drawing module, improve the accuracy of subsequent plot drawing by manually clicking on the position on the map, inputting longitude and latitude coordinates, importing an information file containing control points, etc.

[0072] Step S202: Simplify the multiple control points to obtain a set of target control points;

[0073] In this embodiment, the D-P algorithm (Douglas-Peucker algorithm) is used to simplify the multiple control points, remove unnecessary redundant points from the multiple control points, and retain the key points, finally obtaining a set of target control points; the above-mentioned D-P algorithm (Douglas-Peucker algorithm) is a high-line algorithm for simplifying polygons or polylines. The core idea of this algorithm is to recursively divide the polyline into two segments, and then remove those points whose deviation from the straight line distance is less than the threshold according to the set threshold, so as to achieve the purpose of simplifying the polyline.

[0074] In one embodiment, the simplifying the multiple control points to obtain a set of target control points includes:

[0075] Step 2021: Select two relatively positioned control points from the multiple control points as connection points, and connect the two connection points to obtain a control line;

[0076] Step 2022: Calculate the perpendicular distance from each non-connection point among the multiple control points to the control line to obtain a plurality of the perpendicular distances;

[0077] Step 2023: Remove the control points corresponding to the perpendicular distances less than or equal to a preset simplification threshold to obtain a new set of multiple control points;

[0078] Based on the new set of multiple control points, iterate steps S2021 to S2023 until the perpendicular distances from all non-connection points to the control line are greater than the preset simplification threshold, to obtain the set of target control points.

[0079] In this embodiment, two control points with opposite positions are selected from multiple control points as connection points. Suppose the multiple control points form a circle, any two control points with opposite positions are selected as connection points, and the two connection points are connected by a straight line segment to obtain a control line. The control line is used as the basis for simplifying the D-P algorithm, and the perpendicular distances from the control points that are not connection points among the multiple control points to the control line are calculated to obtain multiple perpendicular distances;

[0080] A preset simplification threshold is set, and the setting of the preset simplification threshold can be determined according to the actual situation and accuracy requirements of the plot; by comparing each of the multiple perpendicular distances with the preset simplification threshold, when the perpendicular distance is less than or equal to the preset simplification threshold, the non-connection point (control point) corresponding to the perpendicular distance is regarded as a redundant point and the redundant point is removed. When the perpendicular distance is greater than the preset simplification threshold, the non-connection point (control point) corresponding to the perpendicular threshold is regarded as a key point. After all the perpendicular distances are compared with the preset simplification threshold, a new set of multiple control points is obtained;

[0081] An iterative operation is performed based on the new set of multiple control points. The iterative operation means selecting two connection points from the new set of multiple control points and connecting them to obtain a new control line, calculating the perpendicular distances from the non-connection points among the new set of multiple control points to the new control line to obtain multiple new perpendicular distances, and then comparing the multiple new perpendicular distances with the preset simplification threshold to screen out the latest set of multiple control points; repeating the above steps until no more redundant points can be removed, and finally obtaining a set of target control points.

[0082] In this embodiment, the D-P algorithm is used to simplify multiple control points, effectively reducing the number of control points, while retaining the key control points of the plot boundary. On the premise of ensuring accuracy, the calculation efficiency of subsequent plot drawing is improved, and the computing resources are reduced.

[0083] In this embodiment, the multiple control points are simplified to obtain a set of target control points. On the premise of ensuring accuracy, the computing resources for subsequent plot drawing are reduced, and the calculation efficiency is improved; and it prevents the increase of data noise caused by excessive control points, thereby improving the accuracy of calculating the plot drawing.

[0084] Step S203: Generate multiple plot boundary curves by using the Bezier curve algorithm according to the adjacent target control points in the set of target control points;

[0085] In this embodiment, based on the set of target control points, the Bezier curve algorithm is used to calculate every two adjacent target control points respectively. For the multiple curve points generated by the Bezier curve algorithm, they are drawn through a preset drawing method (such as Canvas API or SVG), and the multiple curve points are connected to generate a Bezier curve, thereby obtaining multiple plot boundary curves. The above-mentioned Bezier curve algorithm is a parametric curve widely used in graphic design and computer graphics, and the shape of the curve is defined by target control points. The above-mentioned preset drawing method (such as Canvas API or SVG) is a technology for drawing in HTML5 to generate the multiple plot boundary curves in this embodiment.

[0086] In one embodiment, generating multiple plot boundary curves by using the Bezier curve algorithm according to adjacent target control points in the set of target control points includes:

[0087] According to the curve type of the selected Bezier curve, determine the number of adjacent target control points from the set of target control points, and the Bezier curve calculation formula corresponding to the curve type;

[0088] Generate a Bezier curve segment corresponding to the adjacent target control points through the Bezier curve calculation formula and the number of adjacent target control points;

[0089] Traverse all the adjacent target control points in the set of target control points, and draw the Bezier curve segments through a preset drawing method to obtain multiple plot boundary curves.

[0090] In this embodiment, the curve type of the Bezier curve is selected according to specific requirements. The curve type includes but is not limited to quadratic Bezier curves and cubic Bezier curves, etc. According to the selected curve type, the number of adjacent target control points needs to be determined from the set of target control points. For example, when the curve type of the Bezier curve is a quadratic Bezier curve, three adjacent target control points need to be selected. When the curve type of the Bezier curve is a cubic Bezier curve, four adjacent target control points need to be selected. After determining the number of adjacent target control points and the Bezier curve calculation formula corresponding to the curve type according to the curve type of the Bezier curve, calculate the adjacent target control points through the Bezier curve calculation formula to generate a Bezier curve segment corresponding to the adjacent target control points; traverse all the target control points in the set of target control points, and draw all the calculated Bezier curve segments through a preset drawing method to finally obtain multiple plot boundary curves.

[0091] In this embodiment, by selecting different types of Bézier curves, the shape of the plot boundary can be flexibly adjusted according to specific requirements, improving the flexibility and generality of plot boundary calculation; through the Bézier curve calculation method, a curve very close to the actual plot boundary can be generated, thereby improving the accuracy of map or plot division.

[0092] In one embodiment, generating a plurality of plot boundary curves by using a Bézier curve algorithm according to adjacent target control points in the target control point set includes:

[0093] If the number of the adjacent target control points is fixed to two, determine the number of intermediate points according to the curve type of the Bézier curve, and determine the Bézier curve calculation formula corresponding to the curve type;

[0094] Generate the corresponding number of the intermediate points by using a preset intermediate point generation method according to the number of the intermediate points;

[0095] Calculate the adjacent target control points and the corresponding number of the intermediate points through the Bézier curve calculation formula to generate a Bézier curve segment corresponding to the adjacent target control points;

[0096] Traverse all the adjacent target control points in the target control point set, and draw the Bézier curve segments by using a preset drawing method to obtain a plurality of plot boundary curves.

[0097] In this embodiment, if the calculation is performed for two adjacent target control points, one of the target control points is used as the starting point and the other target control point is used as the ending point. Since the number of control points required for the curve type of the Bézier curve is different, at this time, it is necessary to determine the intermediate points to be added according to the curve type. For example, if the curve type is a quadratic Bézier curve and the number of control points it requires is three, then an intermediate point also needs to be added between the starting point and the ending point, and then calculate an intermediate point of the adjacent target control points according to the Bézier curve calculation formula corresponding to the curve type to generate a Bézier curve segment corresponding to the adjacent target control points; traverse all the adjacent target control points in the target control point set, and draw the Bézier curve segments by using a preset drawing method to obtain a plurality of plot boundary curves. Among them, the above-mentioned generation method of the intermediate points can be through manual specification, linear interpolation, etc. The above-mentioned manual specification means determining the position of the intermediate point manually; the above-mentioned linear interpolation means taking the midpoint of the starting point and the ending point as the intermediate point.

[0098] In this embodiment, when the number of adjacent target control points is fixed to two, the situation of lack of target control points is prevented, reducing the complexity of the operation. Through the generation of intermediate points, the position of the intermediate points can still be accurately controlled, thereby improving the accuracy of subsequent plot drawing.

[0099] In another embodiment, the Bezier curve algorithm is used to generate a plurality of plot boundary curves. The calculation formula of the quadratic Bezier curve includes:

[0100] B(t) = (1 - t) 2 P 0 + 2(1 - t)tP 1 + t 2 P 2

[0101] where t is the parameter of the quadratic Bezier curve, t varies between [0, 1], B(t) is the position vector of a point on the Bezier curve, which changes with the change of t, and P 0 , P 1 , P 2 are the coordinates of the target control points, where P 0 is the starting point, P 1 is the intermediate point, and P 2 is the ending point.

[0102] It should be noted that when t is 0, B(t) is P 0 , and when t is 1, B(t) is P 2 .

[0103] In this embodiment, by varying the above t between [0, 1], a plurality of B(t) are generated, that is, a plurality of coordinate points of the Bezier curve are generated. By connecting the coordinate points of the plurality of Bezier curves, a Bezier curve segment corresponding to adjacent target control points is generated. By drawing the Bezier curve segment in the above-mentioned drawing manner, a plurality of plot boundary curves are obtained.

[0104] In this embodiment, based on all the control points of the target control point set, the Bezier curve algorithm generates accurate plot boundary curves, improving the accuracy of plot boundary delineation; and by implementing automation through the Bezier curve algorithm, the workload of manually drawing plot boundaries is reduced, the work efficiency is improved, and the risk of human error is reduced, making the generated plot boundary curves more reliable.

[0105] Step S204: Generate a closed polygon according to the plurality of plot boundary curves to obtain the boundary information of the plot to be measured;

[0106] In this embodiment, the multiple plot boundary curves generated in the above step S203 are integrated. Since the above plot boundary curves are calculated based on adjacent target control points, the multiple plot boundary curves are continuous without gaps or overlaps, that is, the end point of each curve is the start point of the next curve. According to the integrated boundary curve, a closed polygon is constructed. The above closed polygon completely encloses the plot to be measured. The boundary information of the plot to be measured is extracted from the closed polygon to obtain the boundary information of the plot to be measured. Among them, the boundary information can be stored in the GeoJOSN format, and the boundary information includes the longitude and latitude of the control points and curve parameters.

[0107] Specifically, during the construction of the closed polygon, in the order of the curves (such as clockwise or counterclockwise), the start point of the plot boundary curve is used as the first vertex of the polygon in sequence, and then other points on the plot boundary curve are added in sequence until the end point of the last plot boundary curve is reached (i.e., the last vertex or the first vertex of the closed polygon).

[0108] When the closed polygon is constructed, the boundary information of the plot to be measured is extracted from the closed polygon.

[0109] In this embodiment, by integrating the plot boundary curves, constructing a closed polygon, and extracting the boundary information of the plot to be measured from the closed polygon, the accuracy of plot boundary calculation is improved. The process of constructing the closed polygon and extracting the boundary information can be automated, greatly improving the data processing efficiency. This reduces the workload of manually drawing the plot boundary, reduces the risk of human error, and makes the generation of the plot boundary faster and more accurate.

[0110] Step S205: Calculate the plot area of the boundary information by using an area calculation tool;

[0111] In this embodiment, the above area calculation tool refers to a tool that can calculate the area of a polygon, such as turf.js, etc. The plot area of the boundary information is calculated in real time through turf.area of turf.js; the above turf.js is a spatial analysis library based on the browser side, written in JavaScript and managed by npm for packages. This spatial analysis library provides rich functions for geospatial calculations, including but not limited to the creation of points, lines, and polygons, buffer calculations, distance calculations, area calculations, and region mergers. The above turf.area is a built-in method of turf.js for calculating the area of a polygon; the plot area of the boundary information can be automatically calculated by calling the turf.area function.

[0112] In this embodiment, the area calculation tool can calculate the area of the plot with boundary information in real time, eliminating the situation where the calculated area deviates too much from the actual area, improving the accuracy of the delineation of the plot to be measured, and thus reducing the risk of claims disputes.

[0113] Step S206: Associate the boundary information with the plot area to obtain the delineation result of the plot to be measured.

[0114] In this embodiment, the boundary information and the plot area are associated with a unique identifier and a name by using a Geographic Information System (GIS tool) or a front-end database (such as Leaflet.js, Mapbox, etc.) to obtain the delineation result of the plot to be measured. Finally, the delineation result is displayed on the map in a two-dimensional form, enabling the user to clearly and intuitively see the delineation result of the plot. The delineation result includes the shape, area size, and location.

[0115] In this embodiment, by associating the boundary information with the plot area, the delineation result of the plot to be measured is finally obtained and displayed, reducing the error of the plot boundary and area and reducing the risk of claims disputes.

[0116] In one embodiment, after obtaining the delineation result of the plot to be measured, the method further includes:

[0117] Regularly obtain the satellite remote sensing images of the area where the plot to be measured is located, and extract the crop characteristics of the plot to be measured according to the satellite remote sensing images;

[0118] Regularly obtain the meteorological data collected by meteorological sensors and the soil data collected by soil sensors;

[0119] Associate the crop characteristics, meteorological data, and soil data with the delineation result of the plot to be measured to obtain the associated data of the plot to be measured.

[0120] In this embodiment, after determining the geographical location information and boundary information of the plot to be measured, satellite remote sensing data of the area is obtained. The satellite remote sensing data includes multi-spectral remote sensing data and multi-temporal remote sensing data. Among them, the multi-spectral remote sensing data includes visible light, near-infrared, short-wave infrared, etc.; the multi-temporal remote sensing data refers to high-resolution satellite images obtained at different time points to capture the dynamic changes of crops in the plot to be measured.

[0121] Extract the characteristics of crops from the above-obtained multi-spectral remote sensing data and multi-temporal remote sensing data. Specifically, spectral feature analysis methods (such as principal component analysis, linear discriminant analysis, etc.) are used to extract the spectral features (health features) of the crops in the plot to be measured from the multi-spectral remote sensing data. The spectral features include chlorophyll content, vegetation coverage, etc.; the dynamic features of the crops in the plot to be measured are extracted through the multi-temporal remote sensing data. The dynamic features include growth rate, growth cycle, occurrence of pests and diseases, etc. Combine the spectral features and dynamic features to obtain the crop characteristics of the plot to be measured.

[0122] Install meteorological sensors and soil sensors in advance. Use meteorological sensors (such as temperature sensors, humidity sensors, wind speed sensors, etc.) to regularly collect meteorological data in the area where the plot to be measured is located; use soil sensors (such as soil moisture sensors, soil nutrient sensors, etc.) to obtain soil data, such as soil humidity, pH value, nutrient content, etc.

[0123] Associate the extracted crop characteristics, the collected meteorological data and soil data with the delineation result of the plot to be measured, so as to provide a basis for agricultural insurance when insuring.

[0124] In this embodiment, by associating the delineation result of the plot to be measured with the crop characteristics, meteorological data and soil data, a basis for insurance is provided for agricultural insurance when insuring, reducing claim disputes; and through the associated plot to be measured, a comprehensive detection of the plot to be measured can be carried out.

[0125] In one embodiment, after associating the crop characteristics, meteorological data and soil data with the delineation result of the plot to be measured to obtain the associated data of the plot to be measured, the method further includes:

[0126] Analyze the associated data of the plot to be measured through a pre-trained risk assessment model to obtain an analysis result;

[0127] Generate a risk assessment report according to the analysis result.

[0128] In this embodiment, the associated data of the plot to be measured is analyzed by a pre-trained risk assessment model. The pre-trained risk assessment model refers to a machine learning model (such as a decision tree, a random forest, a support vector machine, etc.) or a deep learning model (such as a convolutional neural network, etc.) constructed and trained. The specific training steps include obtaining a large amount of training data, and the training data includes crop growth training data, soil training data, and meteorological training data. Correlation analysis is performed with the soil training data, the meteorological training data, and the growth data. For example, when the soil training data is like, the corresponding result of generating the training data is like. The initial risk assessment model is trained with the above growth training data, soil training data, and meteorological training data, and then the performance of the model is evaluated (such as whether the loss value is less than a preset loss threshold) by model evaluation indicators (such as accuracy, etc.). When the loss value is less than the preset threshold, a trained risk assessment model is obtained, and the associated data of the plot to be measured is analyzed by the trained risk assessment model to obtain an analysis report, and then a risk assessment report for the plot to be measured is generated according to the analysis report.

[0129] In this embodiment, after obtaining the risk assessment report, the insurance staff can push the corresponding agricultural insurance based on the risk assessment report.

[0130] In this embodiment, based on the plot boundaries and area of ​​the plot to be measured, the associated data of the plot to be measured is analyzed through a risk assessment model to generate a corresponding risk assessment report, thereby improving the accuracy of agricultural insurance and reducing the risk of claims disputes.

[0131] In this embodiment, by associating the boundary information and the plot area, the delineation result of the plot to be measured is obtained, which can clearly define the boundary and area of ​​the plot to be measured, reduce the error in the calculation of the plot boundary and area, and improve the accuracy of delineating the plot to be measured.

[0132] It should be emphasized that in order to further ensure the privacy and security of the intelligent delineation results of the above-mentioned plots of land, the intelligent delineation results of the above-mentioned plots of land can also be stored in a node of a blockchain.

[0133] The blockchain referred to in this application is a new application model of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanism, encryption algorithm, etc. Blockchain is essentially a decentralized database, a string of data blocks generated by cryptographic methods. Each data block contains a batch of network transaction information, which is used to verify the validity of its information (anti-counterfeiting) and generate the next block. Blockchain can include the underlying blockchain platform, platform product service layer, and application service layer.

[0134] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Among them, Artificial Intelligence (AI) is a theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use knowledge to obtain the best results.

[0135] Artificial intelligence basic technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technology, operation / interaction systems, and mechatronics. Artificial intelligence software technologies mainly include several major directions such as computer vision technology, robotics, biometric technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0136] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through computer-readable instructions. These computer-readable instructions can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods. Among them, the aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, optical disk, Read-Only Memory (ROM), or a Random Access Memory (RAM), etc.

[0137] It should be understood that although the steps in the flowchart of the accompanying drawings are shown in sequence according to the arrows, these steps do not necessarily have to be executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps has no strict order limitation, 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. These sub-steps or stages do not necessarily have to be executed at the same time, but can be executed at different times, and their execution order does not necessarily have to be sequential, but can be executed alternately or alternately with at least a part of other steps or sub-steps or stages of other steps.

[0138] Further reference Figure 3 to Figure 2 As an implementation of the method shown above, the present application provides an embodiment of an intelligent plot delineation device. This device embodiment corresponds to the method embodiment shown in Figure 2 and can be specifically applied to various computer devices.

[0139] Such as Figure 3As shown in the figure, the intelligent delineation device 300 for plots in this embodiment includes: an acquisition module 301, a simplification module 302, a first calculation module 303, a generation module 304, a second calculation module 305, and an association module 306. Among them:

[0140] The acquisition module 304 is configured to acquire a plurality of control points selected by a user on a preset map software;

[0141] The simplification module 302 is configured to simplify the plurality of control points to obtain a set of target control points;

[0142] In one embodiment, the simplification module 302 includes:

[0143] A selection sub-module, configured to select two control points with opposite positions from the plurality of control points as connection points, and connect the two connection points to obtain a control line;

[0144] A first calculation sub-module, configured to calculate the vertical distance from each non-connection point among the plurality of control points to the control line to obtain a plurality of the vertical distances;

[0145] A removal sub-module, configured to remove the control points corresponding to the vertical distances less than or equal to a preset simplification threshold to obtain a new plurality of control points;

[0146] A first iteration sub-module, configured to iterate from step S2021 to step S2023 based on the new plurality of control points until the vertical distances from all non-connection points to the control line are greater than the preset simplification threshold, to obtain the set of target control points.

[0147] The first calculation module 303 is configured to generate a plurality of plot boundary curves by using a Bezier curve algorithm according to adjacent target control points in the set of target control points;

[0148] In one embodiment, the first calculation module 303 includes:

[0149] A first determination sub-module, configured to determine the number of adjacent target control points from the set of target control points according to the curve type of the selected Bezier curve, and the Bezier curve calculation formula corresponding to the curve type;

[0150] A first generation sub-module, configured to generate a Bezier curve segment corresponding to the adjacent target control points through the Bezier curve calculation formula and the number of adjacent target control points;

[0151] A first drawing sub-module, configured to traverse all the adjacent target control points in the set of target control points, and draw the Bezier curve segments by a preset drawing method to obtain a plurality of plot boundary curves.

[0152] In one embodiment, the first calculation module 303 includes:

[0153] An identification sub-module, configured to identify the number of adjacent target control points;

[0154] A second determination sub-module, configured to, if the number of adjacent target control points is fixed at two, determine the number of intermediate points according to the curve type of the Bezier curve, and determine the Bezier curve calculation formula corresponding to the curve type;

[0155] A second generation sub-module, configured to generate the corresponding number of intermediate points according to the number of intermediate points by using a preset intermediate point generation method;

[0156] A third generation sub-module, configured to calculate the adjacent target control points and the corresponding number of intermediate points through the Bezier curve calculation formula to generate a Bezier curve segment corresponding to the adjacent target control points;

[0157] A second drawing sub-module, configured to traverse all the adjacent target control points in the target control point set, and draw the Bezier curve segment by using a preset drawing method to obtain a plurality of plot boundary curves.

[0158] In one embodiment, in the first calculation module 303, the curve type of the Bezier curve is a quadratic Bezier curve, and the calculation formula of the quadratic Bezier curve includes:

[0159] B(t) = (1 - t) 2 P 0 + 2(1 - t)tP 1 + t 2 P 2

[0160] wherein, the t refers to the parameter of the quadratic Bezier curve, the t varies between [0, 1], the B(t) refers to the position vector of a point on the Bezier curve, and changes with the change of the t, and the P 0 、P 1 、P 2 refer to the coordinates of the target control points, wherein the P 0 is the starting point, the P 1 is the intermediate point, and the P 2 is the ending point.

[0161] A generation module 304, configured to generate a closed polygon according to a plurality of plot boundary curves to obtain the boundary information of the plot to be measured;

[0162] A second calculation module 305, configured to calculate the plot area of the boundary information by using an area calculation tool;

[0163] The association module 306 is used to associate the boundary information with the area of ​​the land parcel to obtain the delineation result of the land parcel to be measured.

[0164] In one embodiment, the apparatus further comprises:

[0165] A first periodic acquisition module is used to periodically acquire satellite remote sensing images of the area where the land to be measured is located, and extract crop characteristics of the land to be measured based on the satellite remote sensing images;

[0166] A second periodic acquisition module is used to periodically acquire meteorological data collected by a meteorological sensor and soil data collected by a soil sensor;

[0167] The data association module is used to associate the crop characteristics, meteorological data and soil data with the delineation results of the plot to be measured to obtain the associated data of the plot to be measured.

[0168] In one embodiment, the apparatus further comprises:

[0169] An analysis module is used to analyze the associated data of the plot to be measured by using a pre-trained risk assessment model to obtain an analysis result;

[0170] A report generation module is used to generate a risk assessment report based on the analysis results.

[0171] In this embodiment, the multiple control points are acquired and simplified to obtain a target control point set, which reduces the computing resources for subsequent plot delineation and improves computing efficiency while ensuring accuracy; and prevents excessive control points from causing an increase in data noise, thereby improving the accuracy of calculating plot delineation.

[0172] Through the Bezier curve algorithm, an accurate plot boundary curve is generated based on all control points of the target control point set, thereby improving the accuracy of plot boundary delineation; and through the Bezier curve algorithm, automation is achieved, reducing the workload of manual plot boundary drawing, improving work efficiency while reducing the risk of human error, making the generated plot boundary curve more reliable.

[0173] By integrating the plot boundary curves and constructing closed polygons, and extracting the boundary information of the plot to be measured from the closed polygons, the accuracy of the plot boundary calculation is improved. The process of constructing closed polygons and extracting boundary information can be automated, greatly improving data processing efficiency. This reduces the workload of manually drawing plot boundaries, reduces the risk of human error, and makes the generation of plot boundaries faster and more accurate.

[0174] The plot area can be calculated in real time through the area calculation tool, excluding the situation where the calculated area deviates too much from the actual area, improving the accuracy of the delineation of the plot to be measured, and thus reducing the risk of claims disputes.

[0175] By associating the boundary information and the plot area, the delineation result of the plot to be measured is obtained, which can clearly define the boundary and area of the plot to be measured, reduce the error in calculating the plot boundary and area, and improve the accuracy of delineating the plot to be measured.

[0176] To solve the above technical problems, the embodiments of the present application also provide a device (computer device). For details, please refer to Figure 4 , Figure 4 This is the basic structural block diagram of the computer device in this embodiment.

[0177] The computer device 4 includes a memory 41, a processor 42, and a network interface 43 that are communicatively connected to each other through a system bus. It should be noted that only the computer device 4 with a memory 41, a processor 42, and a network interface 43 is shown in the figure, but it should be understood that it is not required to implement all the shown components, and more or fewer components can be implemented alternatively. Among them, those skilled in the art of this technology can understand that the computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0178] The computer device can be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. The computer device can interact with the user through a keyboard, a mouse, a remote control, a touchpad, or a voice control device.

[0179] The memory 41 at least includes one type of readable storage medium, and the readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (such as SD or DX memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disc, etc. In some embodiments, the memory 41 may be an internal storage unit of the computer device 4, such as the hard disk or memory of the computer device 4. In other embodiments, the memory 41 may also be an external storage device of the computer device 4, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, FlashCard, etc. equipped on the computer device 4. Of course, the memory 41 may also include both the internal storage unit and the external storage device of the computer device 4. In this embodiment, the memory 41 is generally used to store the operating system and various application software installed on the computer device 4, such as computer-readable instructions for the intelligent delineation method of plots. In addition, the memory 41 may also be used to temporarily store various data that have been output or will be output.

[0180] In some embodiments, the processor 42 may be a central processing unit (CPU), controller, microcontroller, microprocessor, or other data processing chip. The processor 42 is generally used to control the overall operation of the computer device 4. In this embodiment, the processor 42 is used to run the computer-readable instructions stored in the memory 41 or process data, such as running the computer-readable instructions for the intelligent delineation method of plots.

[0181] The network interface 43 may include a wireless network interface or a wired network interface, and the network interface 43 is generally used to establish a communication connection between the computer device 4 and other electronic devices.

[0182] During the implementation of the electronic device of the present application, the multiple control points are acquired and simplified to obtain a set of target control points, which reduces the computing resources for subsequent plot delineation and improves the computing efficiency on the premise of ensuring accuracy; and prevents the increase of data noise caused by excessive control points, thereby improving the accuracy of computing plot delineation.

[0183] Based on all the control points of the target control point set through the Bezier curve algorithm, an accurate plot boundary curve is generated, improving the accuracy of plot boundary delineation; and through the Bezier curve algorithm, automation is achieved, reducing the workload of manually drawing plot boundaries, improving work efficiency while also reducing the risk of human errors, making the generated plot boundary curve more reliable.

[0184] By integrating the plot boundary curve and constructing a closed polygon, and extracting the boundary information of the plot to be measured from the closed polygon, the accuracy of plot boundary calculation is improved. The process of constructing a closed polygon and extracting boundary information can be automated, greatly improving data processing efficiency. This reduces the workload of manually drawing plot boundaries, reduces the risk of human errors, and makes the generation of plot boundaries faster and more accurate.

[0185] Through the area calculation tool, the area of the plot with boundary information can be calculated in real time, excluding the situation where the calculated area deviates too much from the actual area, improving the accuracy of the delineation of the plot to be measured, and thus reducing the risk of claims disputes.

[0186] By associating the boundary information and the plot area, the delineation result of the plot to be measured is obtained, which can clearly define the boundary and area of the plot to be measured, reduce the errors in calculating the plot boundary and area, and improve the accuracy of delineating the plot to be measured.

[0187] This application also provides another implementation manner, that is, to provide a storage medium (computer-readable storage medium), the computer-readable storage medium stores computer-readable instructions, and the computer-readable instructions can be executed by at least one processor, so that the at least one processor executes the steps of the intelligent delineation method of the plot as described above.

[0188] In the implementation process of the computer-readable storage medium of this application, the multiple control points are obtained and simplified to obtain a target control point set. On the premise of ensuring accuracy, the calculation resources for subsequent plot delineation are reduced, and the calculation efficiency is improved; and it prevents the increase of data noise caused by too many control points, thereby improving the accuracy of calculating plot delineation.

[0189] Based on all the control points of the target control point set through the Bezier curve algorithm, an accurate plot boundary curve is generated, improving the accuracy of plot boundary delineation; and through the Bezier curve algorithm, automation is achieved, reducing the workload of manually drawing plot boundaries, improving work efficiency while also reducing the risk of human errors, making the generated plot boundary curve more reliable.

[0190] By integrating the plot boundary curve, constructing a closed polygon, and extracting the boundary information of the plot to be measured, the accuracy of plot boundary calculation is improved. The process of constructing a closed polygon and extracting boundary information can be automated, greatly improving the data processing efficiency. This reduces the workload of manually drawing plot boundaries, reduces the risk of human errors, and makes the generation of plot boundaries faster and more accurate.

[0191] Through the area calculation tool, the area of the plot with boundary information can be calculated in real time, excluding the situation where the calculated area deviates too much from the actual area, improving the accuracy of the delineation of the plot to be measured, and thus reducing the risk of claims disputes.

[0192] By associating the boundary information with the plot area, the delineation result of the plot to be measured can be obtained, which can clearly define the boundary and area of the plot to be measured, reduce the errors in calculating the plot boundary and area, and improve the accuracy of delineating the plot to be measured.

[0193] The non-company software tools or components appearing in the embodiments of this application are only for illustrative introduction and do not represent actual use.

[0194] Through the description of the above embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus a necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of this application, in essence, or the part that makes a contribution to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disc), including several instructions to enable a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0195] Obviously, the above-described embodiments are only a part of the embodiments of this application, rather than all of the embodiments. The accompanying drawings show the preferred embodiments of this application, but do not limit the patent scope of this application. This application can be implemented in many different forms. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosed content of this application more thorough and comprehensive. Although this application has been described in detail with reference to the foregoing embodiments, for those skilled in the art, they can still modify the technical solutions described in the foregoing specific embodiments, or perform equivalent replacements for some of the technical features. Any equivalent structure made by using the specification and drawings of this application, directly or indirectly applied in other related technical fields, is equally within the scope of the patent protection of this application.

Claims

1. A method for intelligently delineating a land parcel, characterized in that: The steps include: Obtain multiple control points selected by the user on the preset map software; Simplifying the multiple control points to obtain a target control point set; Generate multiple plot boundary curves using a Bezier curve algorithm according to adjacent target control points in the target control point set; Generate closed polygons based on multiple plot boundary curves to obtain the boundary information of the plot to be measured Calculate the area of ​​the plot of land with the boundary information using an area calculation tool; The boundary information and the land area are associated to obtain a delineation result of the land to be measured.

2. The intelligent plot delineation method according to claim 1, characterized in that: The simplifying the multiple control points to obtain a target control point set includes: Step 2021: selecting two control points with opposite positions from the plurality of control points as connection points, and connecting the two connection points to obtain a control line; Step 2022: Calculate the vertical distance from each non-connected point in the plurality of control points to the control line to obtain a plurality of the vertical distances; Step 2023: removing the control points corresponding to the vertical distances being less than or equal to the preset simplification threshold, and obtaining multiple new control points; Based on the new multiple control points, iterate step S2021 to step S2023 until the vertical distances from all non-connected points to the control line are greater than the preset simplification threshold, thereby obtaining the target control point set.

3. The intelligent plot delineation method according to claim 1, characterized in that: The step of generating a plurality of land parcel boundary curves by using a Bezier curve algorithm according to adjacent target control points in the target control point set includes: According to the selected Bezier curve type, determining the number of adjacent target control points from the target control point set and the Bezier curve calculation formula corresponding to the curve type; Generate Bezier curve segments corresponding to the adjacent target control points according to the Bezier curve calculation formula and the number of the adjacent target control points; All the adjacent target control points in the target control point set are traversed, and the Bezier curve segments are drawn in a preset drawing manner to obtain a plurality of land parcel boundary curves.

4. The intelligent plot delineation method according to claim 1, characterized in that: The step of generating a plurality of land parcel boundary curves by using a Bezier curve algorithm according to adjacent target control points in the target control point set includes: identifying the number of the adjacent target control points; If the number of the adjacent target control points is fixed to two, then according to the curve type of the Bezier curve, the number of intermediate points is determined, and a Bezier curve calculation formula corresponding to the curve type is determined; According to the number of the intermediate points, a corresponding number of the intermediate points are generated by using a preset intermediate point generation method; Calculate the adjacent target control points and a corresponding number of the intermediate points using the Bezier curve calculation formula to generate Bezier curve segments corresponding to the adjacent target control points; All the adjacent target control points in the target control point set are traversed, and the Bezier curve segments are drawn in a preset drawing manner to obtain a plurality of land parcel boundary curves.

5. The intelligent plot delineation method of claim 4, characterized in that: The curve type of the Bezier curve is a quadratic Bezier curve, wherein the calculation formula of the quadratic Bezier curve includes: B(t)=(1-t) 2 P0+2(1-t)tP1+t 2 P2 Wherein, t refers to a parameter of a quadratic Bezier curve, and t varies between [0,1]. B(t) refers to a position vector of a point on the Bezier curve, and changes with the change of t. P0, P1, and P2 refer to the coordinates of the target control point, where P0 is the starting point, P1 is the middle point, and P2 is the end point.

6. The intelligent plot delineation method according to claim 1, characterized in that: After obtaining the delineation result of the plot to be measured, the method further includes: Regularly obtain satellite remote sensing images of the area where the plot to be measured is located, and extract crop characteristics of the plot to be measured based on the satellite remote sensing images; Regularly obtain meteorological data collected by meteorological sensors and soil data collected by soil sensors; The crop characteristics, meteorological data and soil data are associated with the delineation results of the plot to be measured to obtain associated data of the plot to be measured.

7. The intelligent plot delineation method according to claim 6, characterized in that: After associating the crop characteristics, meteorological data and soil data with the delineation result of the plot to be measured to obtain the associated data of the plot to be measured, the method further includes: Analyze the associated data of the plot to be measured by using a pre-trained risk assessment model to obtain an analysis result; A risk assessment report is generated according to the analysis results.

8. An intelligent plot delineation device, characterized in that: The device comprises: An acquisition module, used to acquire multiple control points selected by a user on a preset map software; A simplification module, used for simplifying the multiple control points to obtain a target control point set; A first calculation module, configured to generate a plurality of land parcel boundary curves by using a Bezier curve algorithm according to adjacent target control points in the target control point set; A generation module, used to generate a closed polygon based on multiple plot boundary curves to obtain boundary information of the plot to be measured; A second calculation module is used to calculate the area of ​​the land parcel of the boundary information using an area calculation tool; The association module is used to associate the boundary information with the area of ​​the plot to obtain the delineation result of the plot to be measured.

9. A computer device, characterized in that: The computer device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the intelligent delineation method of a plot of land as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the intelligent delineation method of a plot of land as described in any one of claims 1 to 7 is implemented.

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