Plant field investigation route dynamic planning method based on species distribution

Abstract

The invention discloses a plant field investigation route dynamic planning method based on species distribution, and relates to the technical field of plant investigation, a species distribution prediction model is established, the distribution probability of a target plant needing to be investigated in each distribution area is obtained, a high potential distribution area is divided, and a distribution thermodynamic diagram is constructed. Planning a preliminary plant field investigation route based on the distribution thermodynamic diagram and a path optimization algorithm, positioning the position coordinate of a surveyor on the plant field investigation route in real time, and judging whether an emergency event occurs at the current position coordinate, if so, re-planning the plant field investigation route based on the current position coordinate, and if not, re-planning the plant field investigation route based on the current position coordinate; and if the target plant is detected, keeping the original plant field investigation route for investigation, after the investigation of the target plant is completed, respectively uploading the final plant field investigation route and investigation data to the Web terminal and the database, establishing a data processing node for data interaction with the Web terminal and the database, and generating a regional investigation interaction graph layer.

Description

Technical Field

[0001] The invention relates to the technical field of plant survey, and in particular to a route dynamic planning method for plant field survey based on species distribution. Background Art

[0002] When conducting plant field surveys, traditional methods often rely on the experience of investigators and limited field survey data, which leads to low survey efficiency and the possibility of large data deviations. In addition, due to the lack of effective prediction models and path planning, survey teams often face challenges in determining survey routes, making it difficult to achieve optimal resource allocation and high survey efficiency. At present, although there are some GIS-based species distribution prediction models, they often cannot respond to emergencies in field surveys in real time, and lack the ability to effectively interact with the Web and database, which limits the sharing and subsequent analysis of field survey data. Therefore, the current plant field survey methods urgently need to be improved to improve the accuracy and efficiency of the survey. Summary of the invention

[0003] In order to solve the above problems, the object of the present invention is to provide a method for dynamic route planning of plant field survey based on species distribution.

[0004] The purpose of the present invention can be achieved by the following technical solution: A method for dynamic route planning of plant field survey based on species distribution, comprising the following steps: Step S1: Establish a species distribution prediction model based on existing species data and environmental variables, and obtain the distribution probability of the target plants to be investigated in each distribution area through the species distribution prediction model; Step S2: Divide the high potential distribution area according to the distribution probability of the target plant in each distribution area, construct a distribution heat map, and plan a preliminary plant field survey route based on the distribution heat map and path optimization algorithm; Step S3: real-time positioning of the position coordinates of the investigator on the plant field survey route, and determining whether an emergency event occurs at the current position coordinates. If so, a new plant field survey route is replanned based on the current position coordinates; if not, the original plant field survey route is maintained for the survey; Step S4: After completing the survey of the target plants, upload the final plant field survey route and survey data to the Web terminal and database respectively, establish a data processing node to interact with the Web terminal and database, and then generate a regional survey interaction layer.

[0005] Furthermore, a species distribution prediction model is established based on the existing species data and environmental variables. The distribution probability of the target plants to be investigated in each distribution area is obtained through the species distribution prediction model. The process includes: The initial convolutional neural network model is constructed through deep learning technology. The initial convolutional neural network model is trained according to the existing species data and environmental variables to predict the distribution area corresponding to each known species and the distribution probability of each known species in its respective distribution area. The predicted distribution area of ​​each known species and the distribution probability in the corresponding distribution area are compared with the actual distribution area and the actual distribution probability in each distribution area, thereby obtaining the prediction accuracy corresponding to the initial convolutional neural network model. The prediction accuracy is recorded as τ, and the accuracy threshold is set and recorded as ψ; When τ ≥ ψ, the initial convolutional neural network model is converted into the final species distribution prediction model, and the species dataset corresponding to the target plant to be investigated is constructed. The species dataset is input into the species distribution prediction model to obtain the distribution area of ​​the target plant and the distribution probability in each distribution area. When τ<ψ, the amount of existing species data and environmental variables is increased, and the initial convolutional neural network model is continued to be trained. After each model training, the real-time prediction accuracy and accuracy threshold are obtained for judgment.

[0006] Furthermore, the process of dividing the high potential distribution area according to the distribution probability of the target plant in each distribution area and constructing the distribution heat map includes: The distribution areas corresponding to the target plants are numbered and recorded as i, i = 1, 2, 3, ..., n, where n is a natural number greater than 0, and the distribution probability of the target plant in the distribution area numbered i is recorded as P[i], and the calibration value corresponding to the high potential distribution area is set and recorded as Γ; All distribution areas with P[i]≥Γ are divided into high potential distribution areas, and all distribution areas with P[i]<Γ are screened out. The distribution density of the target plant in each high potential distribution area is used as its corresponding thermal value. The thermal value of the current target plant in each high potential distribution area is mapped to a preset chart file, and then the distribution thermal map corresponding to several high potential distribution areas of the target plant is constructed.

[0007] Furthermore, the process of planning a preliminary plant field survey route based on the distribution heat map and path optimization algorithm includes: Based on the heat value of each distribution area included in the distribution heat map, the route weight of the distribution area is constructed, the route starting point and the route ending point are set, and each distribution area is used as a route pre-selected point. Based on the path optimization algorithm, starting from the route starting point, the route distance of all route pre-selected points adjacent to the route starting point is calculated, and then the route value coefficient of the segmented route formed between the route starting point and the route pre-selected point is obtained, and the segmented route with the highest route value coefficient is selected as the component route segment of the preliminary plant field survey route; Continue to repeat the acquisition of the route value coefficient of the segmented route formed by the route pre-selected points and the route pre-selected points, and select the segmented route with the highest route value coefficient as the component route segment of the preliminary plant field investigation route. Repeat the above method until the segmented route formed by the route pre-selected points and the route termination points is completed, and the preliminary plant field investigation route is successfully planned.

[0008] Furthermore, the process of real-time positioning the position coordinates of the investigator on the plant field investigation route and determining whether an emergency event occurs at the current position coordinates includes: After the preliminary planning of the plant field survey route is completed, the investigator is equipped with a GPS positioning device and debugged, and the investigator locates the coordinates of his / her own position on the plant field survey route in real time. When the position coordinates enter the distribution area corresponding to the target plant on the plant field survey route, it is determined whether an emergency event occurs in the current distribution area; If yes, a new plant field survey route is replanned based on the investigator's current location coordinates. If no, the investigator continues to follow the original plant field survey route after completing the survey of the target plants in the current distribution area.

[0009] Furthermore, the process of replanning a new plant field survey route based on the current location coordinates includes: For the distribution area where the emergency event occurred in the original plant field survey route, the corresponding route pre-selected point of the distribution area in the plant field survey route is set to an unselectable state, and all the distribution areas geographically adjacent to the current distribution area in the survey area are selected to construct a segmented route between the current distribution area and each adjacent distribution area; The next distribution area adjacent to the distribution area set to be unselectable in the original plant field survey route is marked as a candidate area, and a segmented route between each new segmented route and the current candidate area is constructed, and then several new survey area routes are spliced ​​and generated; The shortest route in the newly surveyed area is selected as the investigator's driving route, and then a new plant field survey route is finally constructed, and the investigator continues the survey along the new plant field survey route.

[0010] Furthermore, after completing the investigation of the target plants, the process of uploading the final plant field investigation route and the investigation data to the Web terminal and the database respectively includes: When the investigator completes the investigation of the target plants in all the distribution areas covered by the plant field investigation route from the starting point to the end point of the route, the final field investigation route taken by the investigator during the investigation is encrypted and uploaded to the set Web terminal, and the investigation data obtained from the corresponding investigation of the target plants in each distribution area is bound to the regional coordinates of the corresponding distribution area and encrypted and uploaded to the database; When the Web terminal receives the final plant field survey route, or the database stores the survey data corresponding to the target plant to be surveyed, the Web terminal or the database converts the corresponding received or stored data into a data stream in a preset data format. The data stream corresponding to the Web terminal is named the first data stream, and the data stream corresponding to the database is named the second data stream.

[0011] Furthermore, the process of establishing a data processing node to interact with the Web terminal and the database to generate a regional survey interactive layer includes: Establish a data processing node, obtain the communication protocols of the Web end and the database respectively, and send them to the data processing node. After the protocol stack set by the data processing node reads the communication protocol, it determines whether the Web end and the database can directly interact with the current data processing node according to the communication protocol; If so, a temporary operation space is created, and after program auditing the first data stream and the second data stream, it is determined whether there are abnormalities in the first data stream and the second data stream, and the first data stream and the second data stream without abnormalities are imported into the temporary operation space, and a regional survey layer is generated, and an interactive list of interactive operation permissions is configured for the regional survey layer, and then the regional survey layer is converted into a corresponding regional survey interactive layer; otherwise, the data of the data points with abnormalities in the first data stream and the second data stream are located, and correction operations are performed; If not, the protocol stack converts the data processing node's own communication protocol into an effective communication protocol that can interact with the Web side and the database, and then continues to operate the first data stream and the second data stream, and generates a regional survey interaction layer.

[0012] Compared with the prior art, the beneficial effects of the present invention are as follows: by establishing a species distribution prediction model, the distribution probability of target plants can be accurately predicted based on existing species data and environmental variables, thereby improving the accuracy of the survey; by dividing high potential distribution areas and constructing distribution heat maps, combined with path optimization algorithms, efficient plant field survey routes can be planned, unnecessary survey work can be reduced, survey efficiency can be improved, the position of investigators can be located in real time, and survey routes can be replanned based on real-time situations, emergency events in field surveys can be effectively responded to, and the continuity and safety of the survey can be ensured; by uploading survey routes and data to the Web and database, and establishing data processing nodes, effective data interaction and sharing are achieved, which is convenient for subsequent data analysis and decision support. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0014] like Figure 1 As shown, a method for dynamic route planning of plant field survey based on species distribution includes the following steps: Step S1: Establish a species distribution prediction model based on existing species data and environmental variables, and obtain the distribution probability of the target plants to be investigated in each distribution area through the species distribution prediction model; Step S2: Divide the high potential distribution area according to the distribution probability of the target plant in each distribution area, construct a distribution heat map, and plan a preliminary plant field survey route based on the distribution heat map and path optimization algorithm; Step S3: real-time positioning of the position coordinates of the investigator on the plant field survey route, and determining whether an emergency event occurs at the current position coordinates. If so, a new plant field survey route is replanned based on the current position coordinates; if not, the original plant field survey route is maintained for the survey; Step S4: After completing the survey of the target plants, upload the final plant field survey route and survey data to the Web terminal and database respectively, establish a data processing node to interact with the Web terminal and database, and then generate a regional survey interaction layer.

[0015] It should be further explained that, in the specific implementation process, a species distribution prediction model is established based on the existing species data and environmental variables, and the distribution probability of the target plants to be investigated in each distribution area is obtained through the species distribution prediction model. The process includes: The existing species data include historical plant survey records, plant storage specimens and remote sensing images, and the environmental variables include monthly temperature changes, monthly precipitation changes, monthly light changes, soil type and altitude; The initial convolutional neural network model is constructed through deep learning technology. The initial convolutional neural network model is trained according to the existing species data and environmental variables to predict the distribution area corresponding to each known species and the distribution probability of each known species in its respective distribution area. The predicted distribution area of ​​each known species and the distribution probability in the corresponding distribution area are compared with the actual distribution area and the actual distribution probability in each distribution area, thereby obtaining the prediction accuracy corresponding to the initial convolutional neural network model. The prediction accuracy is recorded as τ, and the accuracy threshold is set, and the accuracy threshold is recorded as ψ; When τ ≥ ψ, the initial convolutional neural network model is converted into the final species distribution prediction model, and the species dataset corresponding to the target plant to be investigated is constructed. The species dataset is input into the species distribution prediction model to obtain the distribution area of ​​the target plant and the distribution probability in each distribution area. When τ<ψ, the amount of existing species data and environmental variables is increased, and the initial convolutional neural network model is continued to be trained. After each model training, the real-time prediction accuracy and accuracy threshold are obtained for judgment.

[0016] It should be noted that if all the distribution areas of a certain type of known species and the distribution probability under each distribution area are the same as the actual distribution area and the actual distribution probability under the corresponding distribution area, it means that the prediction of the current known species is an accurate prediction. Otherwise, it is a series of wrong predictions. The number of accurate predictions is taken as the numerator and the total number of predictions is taken as the denominator to obtain the prediction accuracy τ corresponding to the initial convolutional neural network model.

[0017] It should be further explained that, in the specific implementation process, the process of dividing the high potential distribution area according to the distribution probability of the target plant in each distribution area and constructing the distribution heat map includes: The distribution areas corresponding to the target plant are numbered and the number is recorded as i, then i = 1, 2, 3, ..., n, where n is a natural number greater than 0, and the distribution probability of the target plant in the distribution area numbered i is recorded as P[i]; Set the calibration value corresponding to the high potential distribution area, and record the calibration value as Γ; For the target plant currently being investigated, all its distribution areas with P[i]≥Γ are divided into high potential distribution areas, and all its distribution areas with P[i]<Γ are screened out. The distribution density of the target plant in each high potential distribution area is used as its corresponding thermal value, and the thermal value of the current target plant in each high potential distribution area is mapped to a preset chart file, thereby constructing a distribution thermal map corresponding to several high potential distribution areas of the target plant.

[0018] The distribution density of target plants is expressed as follows: ;

[0019] in, The symbol corresponding to the distribution density of the target plant. Indicates the number of individuals of the target plant in the distribution area, Indicates the size of the distribution area.

[0020] It should be further explained that, in the specific implementation process, the process of planning a preliminary plant field survey route based on the distribution heat map and the path optimization algorithm includes: Based on the heat value of each distribution area included in the distribution heat map, the route weight corresponding to the corresponding distribution area is constructed with a positive correlation function relationship, the route starting point and the route ending point are set, and each distribution area is used as a route pre-selection point; Based on the path optimization algorithm, starting from the route starting point, the route distance of all the route pre-selected points adjacent to the route starting point is calculated, and then the route value coefficient of the segmented route formed between the route starting point and the route pre-selected points is obtained, and the segmented route with the highest route value coefficient is selected as the route segment of the preliminary plant field survey route; Continue to repeat the acquisition of the route value coefficient of the segmented route formed between the route pre-selected points and the route pre-selected points, and select a segmented route with the highest route value coefficient as the component route segment of the preliminary plant field survey route. Repeat the above method until the segmented route formed by the route pre-selected points and the route end points is completed, and the preliminary plant field survey route is successfully planned; The route value coefficient is denoted as ,but The statement is as follows: ; Among them, when the route weight is larger and the route distance is smaller, the value of the route value coefficient is higher, which means that the corresponding segmented route has a higher priority in selection and can be used as a component of the preliminary plant field survey route.

[0021] It should be further explained that, in the specific implementation process, the process of real-time positioning the position coordinates of the investigator during the investigation on the plant field investigation route and determining whether an emergency event occurs at the current position coordinates includes: After the preliminary planning of the plant field survey route is completed, the investigator is equipped with a GPS positioning device, and after the GPS positioning device is debugged, the investigator locates the coordinates of his / her position on the plant field survey route in real time; When the location coordinates enter the distribution area of ​​the target plant corresponding to the plant field survey route, it is determined whether an emergency event occurs in the current distribution area. If so, a new plant field survey route is replanned based on the current location coordinates of the investigator. If not, the investigator continues to maintain the original plant field survey route for investigation after completing the investigation of the target plants in the current distribution area. The emergencies include natural disasters in the current distribution area, such as floods, landslides, and mud-rock flows, which may cause the original field survey route to be blocked or dangerous, and encounter aggressive wild animals in the current distribution area, such as hornets, snakes, and wild boars, which may cause damage to the survey equipment carried by the investigators, or threaten the life and health of the investigators themselves. It also includes encountering bad weather in the distribution area where the current plant field survey route is located, which makes it impossible to survey the target plants in the current distribution area.

[0022] It should be further explained that, in the specific implementation process, the process of replanning a new plant field survey route based on the current location coordinates includes: For the distribution area where the emergency event occurred in the original plant field survey route, the corresponding route pre-selected point of the distribution area in the plant field survey route is set to an unselectable state, and all the distribution areas geographically adjacent to the current distribution area in the survey area are selected to construct a segmented route between the current distribution area and each adjacent distribution area; The next distribution area adjacent to the distribution area set to be unselectable in the original plant field survey route is marked as a candidate area, and a segmented route between each new segmented route and the current candidate area is constructed, and then several new survey area routes are spliced ​​and generated; The shortest route in the newly surveyed area is selected as the investigator's driving route, and then a new plant field survey route is finally constructed, and the investigator continues the survey along the new plant field survey route.

[0023] It should be further explained that in the specific implementation process, after completing the investigation of the target plants, the process of uploading the final plant field investigation route and investigation data to the Web terminal and the database includes: When the investigator completes the investigation of the target plants in all distribution areas covered by the plant field investigation route from the route starting point to the route ending point, the final field investigation route taken by the investigator during the investigation is encrypted and uploaded to the set web terminal; On the final plant field survey route, the survey data obtained from the corresponding survey of the target plants in each distribution area are bound to the regional coordinates of the corresponding distribution area, and the survey data after binding the regional coordinates are encrypted and uploaded to the database; When the Web end receives the final plant field survey route, or the database stores the survey data corresponding to the target plants to be surveyed in each distribution area on the final plant field survey route, the Web end or the database converts the corresponding received or stored data into a data stream in a preset data format; Among them, the data stream corresponding to the Web end is named the first data stream; The data stream corresponding to the database is named the second data stream.

[0024] It should be further explained that, in the specific implementation process, the process of establishing a data processing node to interact with the Web terminal and the database to generate a regional survey interactive layer includes: Establish a data processing node and configure the node identity code corresponding to the data processing node; The node identity code serves as a unique identity identifier of the data processing node; The communication protocols corresponding to the Web end and the database are obtained respectively, and the respective communication protocols are sent to the data processing node. After the protocol stack set by the data processing node reads the communication protocol, it is determined whether the Web end and the database can directly interact with the current data processing node according to the communication protocol; If yes, the data processing node obtains the first data stream in the Web terminal and the second data stream in the database respectively, creates a temporary operation space, performs program audit on the first data stream and the second data stream, and determines whether there are any abnormalities in the first data stream and the second data stream; The contents of the program review are as follows: Determine whether the data formats of the first data stream and the second data stream conform to a preset standard format, and determine whether data of a plurality of data points constituting the first data stream and the second data stream are missing, repeated, or erroneous. If the data format does not conform to the standard format, or the data at the data point is missing, repeated, or erroneous, it is determined that the corresponding first data stream or the second data stream is abnormal. Otherwise, it is determined that there is no abnormality. Importing the first data stream and the second data stream without abnormalities into the temporary operation space, the temporary operation space synchronously processes the first data stream and the second data stream, thereby generating a regional survey layer, configuring an interactive list of interactive operation permissions for the regional survey layer, and then converting the regional survey layer into a corresponding regional survey interactive layer; The contents of the temporary operation space synchronously processing the first data stream and the second data stream are as follows: The distribution areas of several target plants covered by the final plant field survey route are obtained by parsing the first data stream, and each distribution area is taken as an operation object, and all the operation objects are mapped to a preset blank layer according to their respective area coordinates, thereby obtaining the topological route of the final plant field survey route on the blank layer; The survey data of the target plants in all distribution areas on the final plant field survey route are obtained by parsing the second data stream, and the survey data are bound to several distribution areas represented on the topological route according to the distribution positions of the distribution areas on the plant field survey route; Then, survey data of target plants corresponding to several points on the topological route are formed; A trigger event to be interacted is set for each point, and then the final regional survey interactive layer is generated. When the user clicks on a point on the topological route on the regional survey interactive layer, the trigger event to be interacted corresponding to the current point is successfully triggered, and the interactive operation with the regional survey interactive layer is completed; The regional survey interactive layer includes a data display layer and a user interaction layer; The data display layer is used to visualize the survey data of target plants in each distribution area on the final plant field survey route, and set the corresponding operation area for the visually displayed survey data of each distribution area in the user interaction layer; The user interaction layer is used to provide interactive operations for all users in the interactive list. When the user clicks on the final plant field survey route and the visually displayed survey data in each operation area in the user interaction layer, detailed information corresponding to the survey data is further retrieved; And provide all users in the interactive list with the authority to download and forward the survey data of the target plants; For the first data stream and the second data stream with abnormalities, locate the data points with abnormalities in the first data stream and the second data stream, perform correction operations on the data at the abnormal data points, and then convert the abnormal first data stream and the second data stream to normal, and generate corresponding regional survey interactive layers; If not, the protocol stack of the data processing node converts the communication protocol of the data processing node itself into an effective communication protocol capable of data interaction with the Web end and the database, and then continues to operate the first data stream and the second data stream to generate a regional survey interaction layer; The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A method for dynamic route planning for plant field survey based on species distribution, characterized in that: The following steps are involved: Step S1: Establish a species distribution prediction model based on existing species data and environmental variables, and obtain the distribution probability of the target plants to be investigated in each distribution area through the species distribution prediction model; Step S2: Divide the high potential distribution area according to the distribution probability of the target plant in each distribution area, construct a distribution heat map, and plan a preliminary plant field survey route based on the distribution heat map and path optimization algorithm; Step S3: real-time positioning of the position coordinates of the investigator on the plant field survey route, and determining whether an emergency event occurs at the current position coordinates. If so, a new plant field survey route is replanned based on the current position coordinates; if not, the original plant field survey route is maintained for the survey; Step S4: After completing the survey of the target plants, upload the final plant field survey route and survey data to the Web terminal and database respectively, establish a data processing node to interact with the Web terminal and database, and then generate a regional survey interaction layer.

2. A method for dynamic route planning for plant field survey based on species distribution according to claim 1, characterized in that: The process of establishing a species distribution prediction model based on existing species data and environmental variables and obtaining the distribution probability of the target plants to be investigated in each distribution area through the species distribution prediction model includes: The initial convolutional neural network model is constructed through deep learning technology. The initial convolutional neural network model is trained according to the existing species data and environmental variables to predict the distribution area corresponding to each known species and the distribution probability of each known species in its respective distribution area. The predicted distribution area of ​​each known species and the distribution probability in the corresponding distribution area are compared with the actual distribution area and the actual distribution probability in each distribution area, thereby obtaining the prediction accuracy corresponding to the initial convolutional neural network model. The prediction accuracy is recorded as τ, and the accuracy threshold is set and recorded as ψ; When τ ≥ ψ, the initial convolutional neural network model is converted into the final species distribution prediction model, and the species dataset corresponding to the target plant to be investigated is constructed. The species dataset is input into the species distribution prediction model to obtain the distribution area of ​​the target plant and the distribution probability in each distribution area. When τ<ψ, the amount of existing species data and environmental variables is increased, and the initial convolutional neural network model is continued to be trained. After each model training, the real-time prediction accuracy and accuracy threshold are obtained for judgment.

3. A method for dynamic route planning for plant field survey based on species distribution according to claim 2, characterized in that: The process of dividing the high potential distribution area according to the distribution probability of the target plant in each distribution area and constructing the distribution heat map includes: The distribution areas corresponding to the target plants are numbered and recorded as i, i = 1, 2, 3, ..., n, where n is a natural number greater than 0, and the distribution probability of the target plant in the distribution area numbered i is recorded as P[i], and the calibration value corresponding to the high potential distribution area is set and recorded as Γ; All distribution areas with P[i]≥Γ are divided into high potential distribution areas, and all distribution areas with P[i]<Γ are screened out. The distribution density of the target plant in each high potential distribution area is used as its corresponding thermal value. The thermal value of the current target plant in each high potential distribution area is mapped to a preset chart file, and then the distribution thermal map corresponding to several high potential distribution areas of the target plant is constructed.

4. The method for dynamic route planning of plant field survey based on species distribution according to claim 3, characterized in that: The process of planning a preliminary plant field survey route based on the distribution heat map and path optimization algorithm includes: Based on the heat value of each distribution area included in the distribution heat map, the route weight of the distribution area is constructed, the route starting point and the route ending point are set, and each distribution area is used as a route pre-selected point. Based on the path optimization algorithm, starting from the route starting point, the route distance of all route pre-selected points adjacent to the route starting point is calculated, and then the route value coefficient of the segmented route formed between the route starting point and the route pre-selected point is obtained, and the segmented route with the highest route value coefficient is selected as the component route segment of the preliminary plant field survey route; Continue to repeat the acquisition of the route value coefficient of the segmented route formed by the route pre-selected points and the route pre-selected points, and select the segmented route with the highest route value coefficient as the component route segment of the preliminary plant field investigation route. Repeat the above method until the segmented route formed by the route pre-selected points and the route termination points is completed, and the preliminary plant field investigation route is successfully planned.

5. The method for dynamic route planning of plant field survey based on species distribution according to claim 4, characterized in that: The process of real-time positioning the position coordinates of the investigator on the plant field investigation route and determining whether an emergency event occurs at the current position coordinates includes: After the preliminary planning of the plant field survey route is completed, the investigator is equipped with a GPS positioning device and debugged, and the investigator locates the coordinates of his / her own position on the plant field survey route in real time. When the position coordinates enter the distribution area corresponding to the target plant on the plant field survey route, it is determined whether an emergency event occurs in the current distribution area; If yes, a new plant field survey route is replanned based on the investigator's current location coordinates. If no, the investigator continues to follow the original plant field survey route after completing the survey of the target plants in the current distribution area.

6. A method for dynamic route planning for plant field survey based on species distribution according to claim 5, characterized in that: The process of replanning a new plant field survey route based on the current location coordinates includes: For the distribution area where the emergency event occurred in the original plant field survey route, the corresponding route pre-selected point of the distribution area in the plant field survey route is set to an unselectable state, and all the distribution areas geographically adjacent to the current distribution area in the survey area are selected to construct a segmented route between the current distribution area and each adjacent distribution area; The next distribution area adjacent to the distribution area set to be unselectable in the original plant field survey route is marked as a candidate area, and a segmented route between each new segmented route and the current candidate area is constructed, and then several new survey area routes are spliced ​​and generated; The shortest route in the newly surveyed area is selected as the investigator's driving route, and then a new plant field survey route is finally constructed, and the investigator continues the survey along the new plant field survey route.

7. A method for dynamic route planning for plant field survey based on species distribution according to claim 6, characterized in that: After completing the survey of the target plants, the process of uploading the final plant field survey route and survey data to the Web terminal and database includes: When the investigator completes the investigation of the target plants in all the distribution areas covered by the plant field investigation route from the starting point to the end point of the route, the final field investigation route taken by the investigator during the investigation is encrypted and uploaded to the set Web terminal, and the investigation data obtained from the corresponding investigation of the target plants in each distribution area is bound to the regional coordinates of the corresponding distribution area and encrypted and uploaded to the database; When the Web terminal receives the final plant field survey route, or the database stores the survey data corresponding to the target plant to be surveyed, the Web terminal or the database converts the corresponding received or stored data into a data stream in a preset data format. The data stream corresponding to the Web terminal is named the first data stream, and the data stream corresponding to the database is named the second data stream.

8. The method for dynamic route planning of plant field survey based on species distribution according to claim 7, characterized in that: The process of establishing a data processing node to interact with the Web client and database to generate a regional survey interactive layer includes: Establish a data processing node, obtain the communication protocols of the Web end and the database respectively, and send them to the data processing node. After the protocol stack set by the data processing node reads the communication protocol, it determines whether the Web end and the database can directly interact with the current data processing node according to the communication protocol; If so, a temporary operation space is created, and after program auditing the first data stream and the second data stream, it is determined whether there are abnormalities in the first data stream and the second data stream, and the first data stream and the second data stream without abnormalities are imported into the temporary operation space, and a regional survey layer is generated, and an interactive list of interactive operation permissions is configured for the regional survey layer, and then the regional survey layer is converted into a corresponding regional survey interactive layer; otherwise, the data of the data points with abnormalities in the first data stream and the second data stream are located, and correction operations are performed; If not, the protocol stack converts the data processing node's own communication protocol into an effective communication protocol that can interact with the Web side and the database, and then continues to operate the first data stream and the second data stream, and generates a regional survey interaction layer.

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