Intelligent weeding control method and weeding control system

Abstract

The invention relates to the technical field of intelligent weeding, and discloses an intelligent weeding control method and system, and the method comprises the steps: obtaining a remote sensing image, a high-definition real object image and a farmland planting plan of a farmland; determining a planting area and a weed area according to the farmland planting plan; determining leaf area indexes of the planting area and the weed area according to the remote sensing image; determining the average height of crops and the average height of weeds according to the high-definition real object image; determining the crop growth rate of the planting area according to the crop average height and the leaf area index, and determining the weed growth rate of the weed area according to the weed average height and the leaf area index; setting a weeding path of the weeding machine according to the crop growth rate and the weed growth rate, and controlling the weeding machine to move according to the weeding path so as to perform automatic weeding. Precise weeding is realized through an intelligent means, the weeding efficiency is improved, the use of chemical herbicides is reduced, the labor cost is reduced, and the ecological environment is protected.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent weeding, and in particular to an intelligent weeding control method and a weeding control system. Background Art

[0002] In recent years, intelligent weeding technology has received widespread attention and application in the agricultural field. With the continuous advancement of science and technology, traditional manual weeding methods have been unable to meet the needs of modern agriculture for high efficiency, precision and environmental protection. Traditional weeding methods are not only labor-intensive and inefficient, but also the large-scale use of chemical herbicides may pollute the soil and ecological environment, which is not conducive to the sustainable development of agriculture. Therefore, there is an urgent need for an intelligent weeding control method and a weeding control system to improve weeding efficiency. Summary of the invention

[0003] The purpose of the present invention is to provide an intelligent weed control method and a weed control system to solve the problem that traditional weed control methods are not only labor-intensive and inefficient, but also use a large amount of chemical herbicides, which may pollute the soil and ecological environment and is not conducive to the sustainable development of agriculture.

[0004] The present invention provides an intelligent weed control method, comprising:

[0005] Obtain remote sensing images, high-definition physical images and farmland planting plans of farmland;

[0006] Determining the planting area and weed area of ​​the farmland according to the farmland planting plan;

[0007] Preprocessing the remote sensing image to obtain remote sensing data corresponding to the remote sensing image, and determining the leaf area index of the planting area and the weed area according to the remote sensing data;

[0008] Determine the average height of crops in the planting area and the average height of weeds in the weed area according to the high-definition physical image;

[0009] Determine the crop growth rate in the planting area according to the average height of the crops and the leaf area index, and determine the weed growth rate in the weed area according to the average height of the weeds and the leaf area index;

[0010] A weeding path of the weeder is set according to the crop growth rate and the weed growth rate, and the movement of the weeder is controlled according to the weeding path to perform automatic weeding.

[0011] Preferably, determining the planting area and weed area of ​​the farmland according to the farmland planting plan includes:

[0012] The farmland planting plan includes crop planting locations and crop planting spacing;

[0013] Determining a planting area of ​​the farmland according to the crop planting location;

[0014] The weed area of ​​the farmland is determined according to the planting area and the crop planting spacing.

[0015] Preferably, determining the leaf area index of the planting area and the weed area according to the remote sensing data comprises:

[0016] The normalized vegetation index and the ratio vegetation index of the planting area and the weed area are determined according to the remote sensing data, and the leaf area index of the planting area and the weed area is determined based on the normalized vegetation index and the ratio vegetation index.

[0017] Preferably, determining the normalized vegetation index and the ratio vegetation index of the planting area and the weed area according to the remote sensing data includes:

[0018] The normalized vegetation index is determined according to the following formula:

[0019]

[0020] The ratio vegetation index is determined according to the following formula:

[0021]

[0022] Among them, NDVI represents the normalized difference vegetation index, RVI represents the ratio vegetation index, p(NIR) represents the near-infrared band reflectance, and p(R) represents the red band reflectance.

[0023] Preferably, determining the leaf area index of the planting area and the weed area based on the normalized difference vegetation index and the ratio vegetation index comprises:

[0024] The leaf area index of the planted area is determined according to the following formula:

[0025] LAIz=a·NDVIz+b·RVIz+c;

[0026] Among them, LAIz represents the leaf area index of the planting area, NDVIz represents the normalized difference vegetation index of the planting area, RVIz represents the ratio vegetation index of the planting area, and a, b, and c represent coefficients;

[0027] The leaf area index of the weed area is determined according to the following formula:

[0028] LAIc=a·NDVIc+b·RVIc+c;

[0029] Among them, LAIc represents the leaf area index of the weed area, NDVIc represents the normalized difference vegetation index of the weed area, and RVIc represents the ratio vegetation index of the weed area.

[0030] Preferably, determining the crop growth rate in the planting area according to the average height of the crops and the leaf area index, and determining the weed growth rate in the weed area according to the average height of the weeds and the leaf area index, comprises:

[0031] The crop growth rate in the planting area is determined according to the following formula:

[0032] WGz=k1·Hz 2 +k2·LAIz 2 +k3·Hz·LAIz+k4;

[0033] Among them, WGz represents the crop growth rate, Hz represents the average height of the crop, and k1, k2, k3, and k4 represent coefficients;

[0034] The weed growth rate in the weed area is determined according to the following formula:

[0035] WGc=k1·Hc 2 +k2·LAIc 2 +k3·Hc·LAIc+k4;

[0036] Wherein, WGc represents the weed growth rate, and Hc represents the average height of weeds.

[0037] Preferably, setting the weeding path of the weeder according to the crop growth rate and the weed growth rate includes:

[0038] There is a preset growth rate in advance;

[0039] Comparing the preset growth rate with the crop growth rate, and if the preset growth rate is less than the crop growth rate, setting a weeding path of the weeder according to the preset growth rate and the weed growth rate;

[0040] If the preset growth rate is greater than or equal to the crop growth rate, the weeding path of the weeder is set according to the crop growth rate and the weed growth rate.

[0041] Preferably, setting the weeding path of the weeder according to the preset growth rate and the weed growth rate includes:

[0042] The preset growth rate is compared with the weed growth rate, and if the preset growth rate is less than the weed growth rate, the weeding path of the weeder is set to be a path covered by the weed area;

[0043] If the preset growth rate is greater than or equal to the weed growth rate, the weeder is not controlled to perform weeding.

[0044] Preferably, setting the weeding path of the weeder according to the crop growth rate and the weed growth rate includes:

[0045] The crop growth rate is compared with the weed growth rate, and if the crop growth rate is lower than the weed growth rate, the weeding path of the weeder is set to be a path covered by the weed area;

[0046] If the crop growth rate is greater than or equal to the weed growth rate, the weeder is not controlled to perform weeding.

[0047] The present invention also discloses an intelligent weed control system, which is used to apply the above intelligent weed control method, including:

[0048] Acquisition module, used to obtain remote sensing images, high-definition physical images and farmland planting plans of farmland;

[0049] A region differentiation module, used for determining the planting area and weed area of ​​the farmland according to the farmland planting plan;

[0050] An analysis module is used to pre-process the remote sensing image to obtain remote sensing data corresponding to the remote sensing image, and determine the leaf area index of the planting area and the weed area according to the remote sensing data; and determine the average height of crops in the planting area and the average height of weeds in the weed area according to the high-definition physical image;

[0051] A growth determination module, used to determine the crop growth rate in the planting area according to the average height of the crops and the leaf area index, and to determine the weed growth rate in the weed area according to the average height of the weeds and the leaf area index;

[0052] The weeding control module is used to set a weeding path of the weeder according to the crop growth rate and the weed growth rate, and control the movement of the weeder according to the weeding path to perform automatic weeding.

[0053] Compared with the prior art, the beneficial effect of the present invention is that the present invention realizes precise weeding through intelligent means, improves weeding efficiency, reduces the use of chemical herbicides, reduces labor costs, and protects the ecological environment.

[0054] The intelligent weed control method provided by the present invention avoids the problem of accidental crop damage that may be caused by traditional weeding methods by accurately identifying and distinguishing crops from weeds, thereby improving the accuracy and efficiency of weeding. The automated weeding process reduces dependence on manual labor, reduces labor intensity and labor costs. Compared with traditional chemical weeding methods, the intelligent weed control method is more environmentally friendly, reduces the use of chemical pesticides, and is conducive to protecting the ecological environment. Through effective weeding management, the competition of weeds for crop nutrients and water can be reduced, thereby helping to improve the yield and quality of crops. In addition, the application of this method helps to achieve precision agricultural management, and provides a scientific basis for agricultural production through real-time monitoring and data analysis of crop growth conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0056] Figure 1 It is a schematic flow chart of an intelligent weed control method of the present invention.

[0057] Figure 2 It is a functional block diagram of an intelligent weeding control system of the present invention. DETAILED DESCRIPTION

[0058] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0059] like Figure 1 As shown, the present invention provides an intelligent weed control method, comprising:

[0060] Obtain remote sensing images, high-definition physical images and farmland planting plans;

[0061] Determining the planting area and weed area of ​​the farmland according to the farmland planting plan;

[0062] Preprocessing the remote sensing image to obtain remote sensing data corresponding to the remote sensing image, and determining the leaf area index of the planting area and the weed area according to the remote sensing data;

[0063] Determine the average height of crops in the planting area and the average height of weeds in the weed area according to the high-definition physical image;

[0064] Determine the crop growth rate in the planting area according to the average height of the crops and the leaf area index, and determine the weed growth rate in the weed area according to the average height of the weeds and the leaf area index;

[0065] A weeding path of the weeder is set according to the crop growth rate and the weed growth rate, and the movement of the weeder is controlled according to the weeding path to perform automatic weeding.

[0066] In some embodiments of the present application, the planting area and weed area of ​​the farmland are determined according to the farmland planting plan, including: the farmland planting plan includes crop planting positions and crop planting spacings; the planting area of ​​the farmland is determined according to the crop planting positions; and the weed area of ​​the farmland is determined according to the planting area and the crop planting spacings.

[0067] In this embodiment, first, it is necessary to clarify the planting plan of the farmland, which includes the planting position of the crops and the planting spacing between the crops. This information is the basis for the subsequent division of the area. According to the planting position of the crops in the planting plan, the corresponding planting area can be directly marked on the farmland map. These areas are the specific plots of land where the crops are to be planted in the plan. After the planting area is determined, the open space between adjacent crops can be calculated based on the planting spacing of the crops. These open spaces, outside the planting plan, are usually regarded as areas where weeds may grow. Therefore, through the joint analysis of the planting area and the crop planting spacing, the weed area in the farmland can be determined. The weed area represents an area where only weeds grow. By parsing the crop planting position and spacing information in the farmland planting plan, the accurate division of the planting area and the weed area in the farmland is achieved.

[0068] In some embodiments of the present application, the leaf area index of the planted area and the weed area is determined according to the remote sensing data, including: determining the normalized vegetation index and the ratio vegetation index of the planted area and the weed area according to the remote sensing data, and determining the leaf area index of the planted area and the weed area based on the normalized vegetation index and the ratio vegetation index.

[0069] Determining the normalized vegetation index and the ratio vegetation index of the planting area and the weed area according to the remote sensing data includes:

[0070] The normalized vegetation index is determined according to the following formula:

[0071]

[0072] The ratio vegetation index is determined according to the following formula:

[0073]

[0074] Among them, NDVI represents the normalized difference vegetation index, RVI represents the ratio vegetation index, p(NIR) represents the near-infrared band reflectance, and p(R) represents the red band reflectance.

[0075] In this embodiment, in the era of precision agricultural management, remote sensing technology, with its advantages of non-contact, large range, and high timeliness, has become an important tool for monitoring crop growth and identifying planting areas and weed areas. With the advancement of science and technology, sensors carried by remote sensing satellites and drones can capture the reflection characteristics of surface vegetation in different bands. These characteristics are closely related to the growth conditions, coverage and type of vegetation. NDVI and RVI, as two commonly used vegetation indices, can effectively reflect the greenness information and growth vitality of vegetation by processing remote sensing data through specific algorithms, thereby helping to identify planting areas and weed areas.

[0076] In some embodiments of the present application, determining the leaf area index of the planting area and the weed area based on the normalized vegetation index and the ratio vegetation index includes:

[0077] The leaf area index of the planted area is determined according to the following formula:

[0078] LAIz=a·NDVIz+b·RVIz+c;

[0079] Among them, LAIz represents the leaf area index of the planting area, NDVIz represents the normalized difference vegetation index of the planting area, RVIz represents the ratio vegetation index of the planting area, and a, b, and c represent coefficients;

[0080] The leaf area index of the weed area is determined according to the following formula:

[0081] LAIc=a·NDVIc+b·RVIc+c;

[0082] Among them, LAIc represents the leaf area index of the weed area, NDVIc represents the normalized difference vegetation index of the weed area, and RVIc represents the ratio vegetation index of the weed area.

[0083] In this embodiment, in the process of determining the growth status of crops, the leaf area index (LAI) is defined as the sum of the vertical projection areas of plant leaves per unit land area as a basic parameter to describe the canopy structure of plant populations. It is of great significance for understanding the functions of plant ecosystems, evaluating crop growth conditions, and formulating scientific agricultural management measures. However, traditional LAI measurement methods, such as direct measurement methods and destructive sampling methods, are not only time-consuming and labor-intensive, but also difficult to quickly obtain accurate data over a large range. Therefore, the present application proposes to calculate LAI through a linear regression model based on NDVI and RVI, and the coefficients a, b, and c in the model can be obtained through multiple verifications.

[0084] In some embodiments of the present application, determining the crop growth rate in the planting area according to the average crop height and the leaf area index, and determining the weed growth rate in the weed area according to the average weed height and the leaf area index, comprises:

[0085] The crop growth rate in the planting area is determined according to the following formula:

[0086] WGz=k1·Hz 2 +k2·LAIz 2 +k3·Hz·LAIz+k4;

[0087] Among them, WGz represents the crop growth rate, Hz represents the average height of the crop, and k1, k2, k3, and k4 represent coefficients;

[0088] The weed growth rate in the weed area is determined according to the following formula:

[0089] WGc=k1·Hc 2 +k2·LAIc 2 +k3·Hc·LAIc+k4;

[0090] Wherein, WGc represents the weed growth rate, and Hc represents the average height of weeds.

[0091] In this embodiment, WG represents growth rate, which is a quantitative index used to measure the growth rate of crops within a certain period of time. H represents the average height of crops or weeds, which is an important indicator of crop growth conditions and directly reflects the growth of crops in the vertical direction. LAI represents the leaf area index of crops or weeds, which refers to the multiple of the total area of ​​plant leaves per unit land area to the land area. It reflects the number and distribution of plant leaves and is an important indicator for evaluating crop growth status and productivity. It can be seen that this application provides a powerful tool for evaluating and optimizing crop growth conditions by quantifying the effects of crop average height and leaf area index and their interactions on growth rate, and both leaf area index and average height will affect the growth rate, and both are positive effects. The larger the leaf area index, the faster the crop or weed grows, and the higher the average height, the faster the crop or weed grows.

[0092] In some embodiments of the present application, the weeding path of the weeder is set according to the crop growth rate and the weed growth rate, including: presetting a preset growth rate; comparing the preset growth rate with the crop growth rate, if the preset growth rate is less than the crop growth rate, setting the weeding path of the weeder according to the preset growth rate and the weed growth rate; if the preset growth rate is greater than or equal to the crop growth rate, setting the weeding path of the weeder according to the crop growth rate and the weed growth rate.

[0093] In this embodiment, the crop growth rate and the weed growth rate are key factors affecting the balance of the farmland ecosystem. As the target we expect to harvest, the growth rate and health of crops are directly related to the final yield. As non-target plants in farmland, weeds not only compete with crops for resources such as nutrients, water and light, but may also become hosts of pests and diseases, posing a serious threat to crops. Therefore, it is one of the important tasks of farmland management to reasonably control the growth of weeds and ensure the healthy growth of crops. In order to control weeds more accurately and avoid unnecessary damage to crops, it is necessary to set the weeding path of the weeder according to the crop growth rate and the weed growth rate. Different weeding strategies are adopted according to plants with different growth rates. First, an acceptable minimum growth rate, that is, a preset growth rate, is set, and the preset growth rate is compared with the crop growth rate. When the preset growth rate is less than the crop growth rate, this means that the preset growth rate is a lower growth rate. At this time, the weeding path of the weeder can be set according to the preset growth rate and the weed growth rate. When the preset growth rate is greater than or equal to the crop growth rate, it means that the crop growth rate is a lower growth rate. At this time, it is necessary to flexibly adjust the weeding path of the weeder according to the crop growth rate and the weed growth rate.

[0094] In some embodiments of the present application, the weeding path of the weeder is set according to the preset growth rate and the weed growth rate, including: comparing the preset growth rate and the weed growth rate, if the preset growth rate is less than the weed growth rate, setting the weeding path of the weeder to a path covered by the weed area; if the preset growth rate is greater than or equal to the weed growth rate, not controlling the weeder to weed.

[0095] In this embodiment, the preset growth rate usually refers to the ideal growth rate of the target crop under specific environmental conditions, which is based on a comprehensive consideration of various factors such as crop varieties, soil conditions, and climatic conditions. The weed growth rate refers to the actual growth rate of weeds in actual farmland, which is affected by various environmental factors and weed species and often has high variability and uncertainty. When setting the weeding path of the weeder, it is crucial to compare the preset growth rate with the weed growth rate. This comparison process is not only related to the timing of weeding, but also directly affects the weeding effect and resource utilization efficiency. When the preset growth rate is less than the weed growth rate, it means that the growth rate of the weeds has exceeded the acceptable growth rate, which will pose a serious threat to the growth of crops. At this time, the intelligent weeder should be set to a path that fully covers the weed area. Through a high-precision GPS positioning system and advanced image recognition technology, the weeder can accurately identify the weed area and perform weeding operations along the optimal path. This strategy helps to control the spread of weeds in a timely manner, protect crops from damage, and ensure that crops can grow normally. On the contrary, when the preset growth rate is greater than or equal to the weed growth rate, it means that the crop is growing well and has a certain competitive advantage. At this time, if weeding is performed blindly, it may not only waste resources but also cause unnecessary damage to the crop. Therefore, in this case, the smart weeder should be set to a state of uncontrolled weeding.

[0096] In some embodiments of the present application, setting a weeding path of a weeder according to the crop growth rate and the weed growth rate includes: comparing the crop growth rate and the weed growth rate, and if the crop growth rate is less than the weed growth rate, setting the weeding path of the weeder to a path covered by the weed area; if the crop growth rate is greater than or equal to the weed growth rate, not controlling the weeder to perform weeding.

[0097] In this embodiment, the crop growth rate refers to the rate of increase of crop growth per unit time, which is affected by multiple environmental factors such as soil fertility, water conditions, light intensity and temperature. The weed growth rate refers to the growth rate of weed growth under the same environmental conditions. Since weeds often have stronger adaptability and reproductive ability, they may exceed the growth rate of crops in some cases, posing a serious threat to crops. By real-time monitoring of the growth rates of crops and weeds, the two are compared and analyzed. If the monitoring results show that the crop growth rate is less than the weed growth rate, it means that weeds are rapidly occupying soil nutrients and space resources, posing a direct threat to crops. At this time, the intelligent weeding system should respond quickly, automatically plan and execute the weeding path covered by the weed area to effectively curb the spread of weeds and ensure the normal growth of crops. On the contrary, if the crop growth rate is greater than or equal to the weed growth rate, it means that the crop is in a dominant position in the current environment and can better resist the intrusion of weeds. Therefore, the intelligent weeding system should suspend the weeding operation and switch to other more urgent field management tasks, such as irrigation and fertilization, to further optimize the crop growth environment.

[0098] like Figure 2 As shown, the present invention also discloses an intelligent weed control system, which is used to apply the above-mentioned intelligent weed control method, including:

[0099] The acquisition module is used to obtain remote sensing images, high-definition physical images and farmland planting plans of farmland.

[0100] The area differentiation module is used to determine the planting area and weed area of ​​the farmland according to the farmland planting plan.

[0101] The analysis module is used to pre-process the remote sensing image to obtain remote sensing data corresponding to the remote sensing image, determine the leaf area index of the planting area and the weed area according to the remote sensing data; and determine the average height of crops in the planting area and the average height of weeds in the weed area according to the high-definition physical image.

[0102] The growth determination module is used to determine the crop growth rate in the planting area according to the average height of the crops and the leaf area index, and to determine the weed growth rate in the weed area according to the average height of the weeds and the leaf area index.

[0103] The weeding control module is used to set a weeding path of the weeder according to the crop growth rate and the weed growth rate, and control the movement of the weeder according to the weeding path to perform automatic weeding.

[0104] By accurately distinguishing between planting areas and weed areas, the system can guide weeding machinery to operate efficiently, reduce manual intervention, and improve the efficiency of weeding operations. It can also monitor the growth of weeds in real time, and intelligently adjust the weeding strategy according to the difference in growth rate between crops and weeds, thereby reducing the use of chemical herbicides and reducing environmental pollution. At the same time, by analyzing remote sensing data and high-definition physical images, the system can accurately evaluate the growth status of crops and weeds, rationally plan weeding time and paths, and optimize the use of agricultural resources. Automated weeding control reduces dependence on manual weeding, reduces the labor intensity and labor costs of agricultural production. Through timely and effective weeding, the system helps to provide a better growth environment for crops, thereby potentially improving crop yield and quality.

[0105] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution 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 they can still modify or replace the technical solution of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solution to deviate from the spirit and scope of the technical solution of the present invention.

[0106] The system provided in the above embodiment is only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the modules or steps in the embodiments of the present invention can be decomposed or combined. For example, the modules in the above embodiment can be combined into one module, or further divided into multiple sub-modules to complete all or part of the functions described above. The names of the modules and steps involved in the embodiments of the present invention are only for distinguishing the modules or steps, and are not regarded as improper limitations of the present invention.

[0107] Those skilled in the art should be able to appreciate that the modules and method steps of each example described in conjunction with the embodiments disclosed herein can be implemented with electronic hardware, computer software or a combination of the two, and the programs corresponding to the software modules and method steps can be placed in random access memory (RAM), memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disks, removable disks, CD-ROMs or any other form of storage medium known in the technical field. In order to clearly illustrate the interchangeability of electronic hardware and software, the composition and steps of each example have been generally described in the above description according to the function. Whether these functions are performed in electronic hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

Claims

1. An intelligent weed control method, characterized in that: include: Obtain remote sensing images, high-definition physical images and farmland planting plans; Determining the planting area and weed area of ​​the farmland according to the farmland planting plan; Preprocessing the remote sensing image to obtain remote sensing data corresponding to the remote sensing image, and determining the leaf area index of the planting area and the weed area according to the remote sensing data; Determine the average height of crops in the planting area and the average height of weeds in the weed area according to the high-definition physical image; Determine the crop growth rate in the planting area according to the average height of the crops and the leaf area index, and determine the weed growth rate in the weed area according to the average height of the weeds and the leaf area index; A weeding path of the weeder is set according to the crop growth rate and the weed growth rate, and the movement of the weeder is controlled according to the weeding path to perform automatic weeding.

2. The intelligent weed control method according to claim 1, characterized in that: Determine the planting area and weed area of ​​the farmland according to the farmland planting plan, including: The farmland planting plan includes crop planting locations and crop planting spacing; Determining a planting area of ​​the farmland according to the crop planting location; The weed area of ​​the farmland is determined according to the planting area and the crop planting spacing.

3. The intelligent weed control method according to claim 1, characterized in that: Determining leaf area index of planted areas and weedy areas based on the remote sensing data includes: The normalized vegetation index and the ratio vegetation index of the planting area and the weed area are determined according to the remote sensing data, and the leaf area index of the planting area and the weed area is determined based on the normalized vegetation index and the ratio vegetation index.

4. The intelligent weed control method according to claim 3, characterized in that: Determining the normalized vegetation index and the ratio vegetation index of the planting area and the weed area according to the remote sensing data includes: The normalized vegetation index is determined according to the following formula: The ratio vegetation index is determined according to the following formula: Among them, NDVI represents the normalized difference vegetation index, RVI represents the ratio vegetation index, p(NIR) represents the near-infrared band reflectance, and p(R) represents the red band reflectance.

5. The intelligent weed control method according to claim 4, characterized in that: Determining the leaf area index of the planting area and the weed area based on the normalized vegetation index and the ratio vegetation index includes: The leaf area index of the planted area is determined according to the following formula: LAIz=a·NDVIz+b·RVIz+c; Among them, LAIz represents the leaf area index of the planting area, NDVIz represents the normalized difference vegetation index of the planting area, RVIz represents the ratio vegetation index of the planting area, and a, b, and c represent coefficients; The leaf area index of the weed area is determined according to the following formula: LAIc=a·NDVIc+b·RVIc+c; Among them, LAIc represents the leaf area index of the weed area, NDVIc represents the normalized difference vegetation index of the weed area, and RVIc represents the ratio vegetation index of the weed area.

6. The intelligent weed control method according to claim 4, characterized in that: Determining the crop growth rate in the planting area according to the average height of the crops and the leaf area index, and determining the weed growth rate in the weed area according to the average height of the weeds and the leaf area index, comprises: The crop growth rate in the planting area is determined according to the following formula: WGz=k1·Hz 2 +k2·LAIz 2 +k3·Hz·LAIz+k4; Among them, WGz represents the crop growth rate, Hz represents the average height of the crop, and k1, k2, k3, and k4 represent coefficients; The weed growth rate in the weed area is determined according to the following formula: WGc=k1 Hc 2 +k2 LAIc 2 +k3·Hc·LAIc+k4; Wherein, WGc represents the weed growth rate, and Hc represents the average height of weeds.

7. The intelligent weed control method according to claim 1, characterized in that: The weeding path of the weeder is set according to the crop growth rate and the weed growth rate, including: There is a preset growth rate in advance; Comparing the preset growth rate with the crop growth rate, and if the preset growth rate is less than the crop growth rate, setting a weeding path of the weeder according to the preset growth rate and the weed growth rate; If the preset growth rate is greater than or equal to the crop growth rate, the weeding path of the weeder is set according to the crop growth rate and the weed growth rate.

8. The intelligent weed control method according to claim 7, characterized in that: The weeding path of the weeder is set according to the preset growth rate and the weed growth rate, comprising: The preset growth rate is compared with the weed growth rate, and if the preset growth rate is less than the weed growth rate, the weeding path of the weeder is set to be a path covered by the weed area; If the preset growth rate is greater than or equal to the weed growth rate, the weeder is not controlled to perform weeding.

9. The intelligent weed control method according to claim 7, characterized in that: Setting a weeding path of the weeder according to the crop growth rate and the weed growth rate includes: The crop growth rate is compared with the weed growth rate, and if the crop growth rate is lower than the weed growth rate, the weeding path of the weeder is set to be a path covered by the weed area; If the crop growth rate is greater than or equal to the weed growth rate, the weeder is not controlled to perform weeding.

10. An intelligent weed control system, used for applying the intelligent weed control method according to any one of claims 1 to 9, characterized in that: The system comprises: Acquisition module, used to obtain remote sensing images, high-definition physical images and farmland planting plans of farmland; A region differentiation module, used for determining the planting area and weed area of ​​the farmland according to the farmland planting plan; An analysis module is used to pre-process the remote sensing image to obtain remote sensing data corresponding to the remote sensing image, and determine the leaf area index of the planting area and the weed area according to the remote sensing data; and determine the average height of crops in the planting area and the average height of weeds in the weed area according to the high-definition physical image; A growth determination module, used to determine the crop growth rate in the planting area according to the average height of the crops and the leaf area index, and to determine the weed growth rate in the weed area according to the average height of the weeds and the leaf area index; The weeding control module is used to set a weeding path of the weeder according to the crop growth rate and the weed growth rate, and control the movement of the weeder according to the weeding path to perform automatic weeding.

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