Irrigation control method and device, electronic equipment, storage medium and product

Abstract

The invention provides an irrigation control method and device, electronic equipment, a storage medium and a product, and relates to the technical field of data processing. Satellite remote sensing image data and soil moisture content data of a target area are acquired; inputting the satellite remote sensing image data and the soil moisture content data into a soil moisture content model to obtain soil moisture content data corresponding to the target area output by the soil moisture content model; determining water demand data of a target crop in the target area; determining a regional irrigation result according to the soil water content data and the water demand data; and controlling the target area to irrigate according to the area irrigation result. According to the technical scheme, the satellite remote sensing image data and the soil moisture content data of the target area are acquired based on the remote sensing image and the earth surface sensing equipment, and the soil moisture content data of the target area are timely mastered through the soil moisture content model, so that the area irrigation result is determined according to the soil moisture content data and the water demand data; precise irrigation of the target area is completed, and the efficiency and accuracy of automatic irrigation are improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to an irrigation control method, device, electronic equipment, storage medium and product. Background Art

[0002] With the development of science and technology, the level of intelligence, automation and informatization of agricultural production has been continuously improved. How to achieve precision irrigation is an urgent problem to be solved in the field of agricultural irrigation.

[0003] At present, in the prior art, precision irrigation for agriculture usually relies on manual experience to make judgments. Through years of agricultural practice and understanding of local climate, soil and other conditions and practical experience accumulation by agricultural practitioners, combined with personal professional knowledge and intuition, irrigation time and irrigation amount are configured, and irrigation is performed manually or mechanized irrigation is performed using irrigation-related equipment. Although this method of manual irrigation can solve the problem to a certain extent, it has obvious shortcomings. First, manual processing is very dependent on the practical experience of personnel. It is difficult for manual operation to accurately obtain the soil moisture content and the amount of water most suitable for crop growth, and then equip the crop growth with a suitable irrigation plan for crop growth. Secondly, human factors may lead to subjectivity and inconsistency in decision-making. It can only be judged by sampling soil moisture content measurement and crop growth to determine whether the crops have reached the amount of water required for growth, which affects the comprehensiveness and effectiveness of the irrigation plan; finally, manual irrigation and mechanized irrigation cannot maximize the use of water resources, easily waste water resources, and cannot achieve precision irrigation. Summary of the invention

[0004] The present invention provides an irrigation control method, device, electronic device, storage medium and product, which are used to solve the defects of the prior art that the method of artificial irrigation leads to waste of irrigation water resources and cannot irrigate accurately, and realizes the collection of satellite remote sensing image data and soil moisture data of the target area based on remote sensing images and surface sensing equipment, and timely grasps the soil moisture data of the target area through the soil moisture model, so as to determine the regional irrigation result based on the soil moisture data and the water requirement data of the target crop in the target area, complete the accurate irrigation of the target area, and improve the efficiency and accuracy of automatic irrigation.

[0005] The invention provides an irrigation control method, comprising the following steps.

[0006] Obtain satellite remote sensing image data and soil moisture data of the target area; wherein the satellite remote sensing image data is data corresponding to the target area acquired by remote sensing images, and the soil moisture data is soil moisture data corresponding to the target area acquired based on surface sensing equipment set in the target area.

[0007] Satellite remote sensing image data and soil moisture data are input into the soil moisture model to obtain soil moisture data corresponding to the target area output by the soil moisture model; wherein the soil moisture model is a model trained based on satellite remote sensing image sample data, soil moisture sample data and corresponding soil moisture data labels.

[0008] Determine the water requirement data of the target crop in the target area; wherein the water requirement data is the water requirement of the target crop in the target area under an ideal state.

[0009] Determine regional irrigation results based on soil moisture data and water requirement data.

[0010] Control irrigation in target areas based on regional irrigation results.

[0011] According to an irrigation control method provided by the present invention, the training process of a soil moisture model includes: obtaining satellite remote sensing image sample data, soil moisture sample data, soil moisture content data labels and a basic soil moisture inversion model; wherein the basic soil moisture inversion model is a predetermined basic model for inverting soil moisture; and the basic soil moisture inversion model is trained according to the satellite remote sensing image sample data, the soil moisture sample data and the soil moisture content data labels to obtain a soil moisture model.

[0012] According to an irrigation control method provided by the present invention, satellite remote sensing image data and soil moisture data are input into a soil moisture model to obtain soil moisture content data corresponding to a target area output by the soil moisture model, including: inputting satellite remote sensing image data into a feature variable selector of the soil moisture model to obtain a feature selection result output by the feature variable selector; wherein the feature variable operator is an operator that performs multi-band combination operations on the satellite remote sensing image data, and the feature selection result includes a plurality of vegetation indices obtained by performing multi-band combination operations on the satellite remote sensing image data; inputting the feature selection result and soil moisture data into a classification selector of the soil moisture model to obtain soil moisture content data corresponding to the target area output by the classification selector; wherein the classification selector is a selector that selects a plurality of vegetation indices that conform to the soil moisture data from the feature selection result.

[0013] According to an irrigation control method provided by the present invention, water requirement data of a target crop in a target area is determined, including: obtaining soil property data of the target area and a planting vector of the target crop; wherein the planting vector is the crop space range of the target crop in the target area; and determining the water requirement data of the target crop in the target area according to the soil property data, the planting vector and a water requirement rule table; wherein the water requirement rule table is a table containing the relationship between the soil property data and the water requirement data corresponding to the planting vector.

[0014] According to an irrigation control method provided by the present invention, a regional irrigation result is determined according to soil moisture data and water demand data, including: determining the irrigation method of the target area; determining the regional irrigation result according to the planting vector, irrigation method, soil moisture data and water demand data.

[0015] According to an irrigation control method provided by the present invention, regional irrigation results are determined according to planting vectors, irrigation methods, soil moisture data and water demand data, including: determining irrigation water demand according to the difference between soil moisture data and water demand data; determining regional irrigation results according to planting vectors, irrigation methods and irrigation water demand.

[0016] The present invention also provides an irrigation control device, comprising the following modules.

[0017] The data acquisition module is used to acquire satellite remote sensing image data and soil moisture data of the target area; wherein the satellite remote sensing image data is the data corresponding to the target area acquired by remote sensing images, and the soil moisture data is the soil moisture data corresponding to the target area acquired based on the surface sensing equipment set in the target area.

[0018] The data output module is used to input satellite remote sensing image data and soil moisture data into the soil moisture model to obtain the soil moisture data corresponding to the target area output by the soil moisture model; wherein the soil moisture model is a model trained based on satellite remote sensing image sample data, soil moisture sample data and corresponding soil moisture data labels.

[0019] The data determination module is used to determine the water requirement data of the target crop in the target area; wherein the water requirement data is the water requirement of the target crop in the target area under an ideal state.

[0020] The result determination module is used to determine the regional irrigation result according to the soil moisture content data and the water demand data.

[0021] The irrigation control module is used to control the irrigation of the target area according to the regional irrigation results.

[0022] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, any one of the above-mentioned irrigation control methods is implemented.

[0023] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, any of the above-mentioned irrigation control methods is implemented.

[0024] The present invention also provides a computer program product, comprising a computer program, and when the computer program is executed by a processor, any of the above irrigation control methods is implemented.

[0025] The present invention provides an irrigation control method, device, electronic device, storage medium and product, which obtain satellite remote sensing image data and soil moisture data of a target area; wherein the satellite remote sensing image data is data corresponding to the target area acquired by remote sensing images, and the soil moisture data is soil moisture data corresponding to the target area acquired based on a surface sensing device set in the target area; the satellite remote sensing image data and the soil moisture data are input into a soil moisture model to obtain soil moisture content data corresponding to the target area output by the soil moisture model; wherein the soil moisture model is a model trained based on satellite remote sensing image sample data, soil moisture content sample data and corresponding soil moisture content data labels; the water demand data of a target crop in the target area is determined; wherein the water demand data is the water demand of the target crop in the target area under an ideal state; the regional irrigation result is determined according to the soil moisture content data and the water demand data; and the target area is controlled to be irrigated according to the regional irrigation result. The technical solution of the present invention is used to solve the defects of the prior art that the method of manual irrigation leads to waste of irrigation water resources and inability to irrigate accurately, and realizes the collection of satellite remote sensing image data and soil moisture data of the target area based on remote sensing images and surface sensing equipment, and timely grasps the soil moisture data of the target area through the soil moisture model, so as to determine the regional irrigation result based on the soil moisture data and the water requirement data of the target crop in the target area, complete the accurate irrigation of the target area, and improve the efficiency and accuracy of automatic irrigation. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0027] Figure 1 It is a flow chart of the irrigation control method provided by the present invention.

[0028] Figure 2 It is a structural schematic diagram of the irrigation control device provided by the present invention.

[0029] Figure 3 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0030] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0031] Combine the following Figure 1 The irrigation control method provided by the present invention is described. The irrigation control method provided by the present invention can be applicable to automatic irrigation control situations. The execution subject of the method can be an electronic device or an irrigation control device set in the electronic device. The irrigation control device can be implemented by software, hardware or a combination of both. Figure 1 It is a flow chart of the irrigation control method provided by the present invention, such as Figure 1 As shown, the method includes the following steps 101, 102, 103, 104 and 105.

[0032] Step 101: Obtain satellite remote sensing image data and soil moisture data of a target area.

[0033] In this step, the satellite remote sensing image data is data corresponding to the target area collected by the remote sensing image, and the soil moisture data is soil moisture data corresponding to the target area collected based on the surface sensing equipment set in the target area. The target area is a specific irrigation area, and the satellite remote sensing image data is determined based on the specific irrigation area. The scope of the remote sensing image field collection covers the target area. The surface sensing equipment includes multiple single soil moisture sensors, and the target area is covered by multiple single soil moisture sensors. The soil moisture data is data obtained based on multiple single soil moisture sensors. Image data captured by remote sensing images of satellite transit Specifically, the satellite remote sensing image data corresponding to the target area is based on the remote sensing image taken by the satellite passing over, and the soil moisture data corresponding to the target area is collected by the surface sensing equipment set in the target area.

[0034] Step 102: input the satellite remote sensing image data and the soil moisture data into the soil moisture model to obtain the soil moisture content data corresponding to the target area output by the soil moisture model.

[0035] In this step, the soil moisture model is a model trained based on satellite remote sensing image sample data, soil moisture sample data and corresponding soil moisture content data labels. The soil moisture model specifically combines XGBoost (an optimized distributed gradient boosting library designed to achieve high efficiency, flexibility and portability) feature variable selection with a model of machine learning technologies such as a random forest model. The core algorithms of the soil moisture model include XGBoost feature variable selection, a variety of machine learning algorithms (such as partial least squares regression, back propagation neural network, genetic algorithm optimized back propagation neural network, random forest, continuous projection algorithm) for inversion model establishment and model accuracy verification, which is not limited in this embodiment.

[0036] Specifically, after obtaining satellite remote sensing image data and soil moisture data, the satellite remote sensing image data and soil moisture data are input into a soil moisture model, and a multi-band combination operation is performed on the remote sensing image through the soil moisture model to obtain a variety of vegetation indices, and then based on the multiple vegetation indices and soil moisture data, screening is performed to select variable combinations related to the soil moisture data, and based on the determined variable combination, the soil moisture content data corresponding to the target area output by the soil moisture model is obtained.

[0037] In a specific embodiment, the training process of the soil moisture model includes: obtaining satellite remote sensing image sample data, soil moisture sample data, soil moisture content data labels and a basic soil moisture inversion model; wherein the basic soil moisture inversion model is a predetermined basic model for inverting soil moisture; the basic soil moisture inversion model is trained according to the satellite remote sensing image sample data, soil moisture sample data and soil moisture content data labels to obtain a soil moisture model.

[0038] In this step, the satellite remote sensing image sample data, the soil moisture sample data and the corresponding soil moisture content data labels are all pre-determined sample data and corresponding data labels.

[0039] Specifically, satellite remote sensing image sample data, soil moisture sample data, soil water content data labels and a basic soil moisture inversion model are obtained, and the basic soil moisture inversion model is iteratively optimized and trained according to the satellite remote sensing image sample data, soil moisture sample data and soil moisture content data labels to obtain a soil moisture model.

[0040] In a specific implementation, satellite remote sensing image data and soil moisture data are input into a soil moisture model to obtain soil moisture data corresponding to a target area output by the soil moisture model, including: inputting satellite remote sensing image data into a feature variable selector of the soil moisture model to obtain a feature selection result output by the feature variable selector; wherein the feature variable operator is an operator that performs multi-band combination operations on the satellite remote sensing image data, and the feature selection result includes a plurality of vegetation indices obtained by performing multi-band combination operations on the satellite remote sensing image data; inputting the feature selection result and soil moisture data into a classification selector of the soil moisture model to obtain soil moisture data corresponding to the target area output by the classification selector; wherein the classification selector is a selector that selects a plurality of vegetation indices that conform to the soil moisture data from the feature selection results.

[0041] Specifically, the satellite remote sensing image data is input into the feature variable selector of the soil moisture model, and the feature variable operator performs multi-band combination operation on the satellite remote sensing image data to obtain the feature selection result output by the feature variable selector, which includes multiple vegetation indices obtained by performing multi-band combination operation on the satellite remote sensing image data. Then, the feature selection result and the soil moisture data are input into the classification selector of the soil moisture model, and the classification selector selects the soil moisture content data of multiple vegetation indices that meet the soil moisture data from the feature selection result.

[0042] The advantage of this setting is that the soil moisture data can be inverted by using satellite remote sensing image data obtained by remote sensing images and soil moisture data obtained by surface sensing equipment, thereby providing appropriate irrigation plans for crop growth.

[0043] Step 103: Determine the water requirement data of the target crop in the target area.

[0044] In this step, the water requirement data is the water requirement of the target crop in the target area under ideal conditions, for example, the water requirement of A mu of sandy loam is x tons, the water requirement of B mu of loam is y tons, etc. This embodiment does not limit this.

[0045] Specifically, after determining the target area, determine the soil texture of the target area, which may be sandy soil, loam, etc., which is not limited in this embodiment. Then determine the water requirement data of the target crop in the target area according to the soil texture of the target area.

[0046] In a specific embodiment, determining the water requirement data of a target crop in a target area includes: obtaining soil property data of the target area and a planting vector of the target crop; wherein the planting vector is the crop space range of the target crop in the target area; determining the water requirement data of the target crop in the target area according to the soil property data, the planting vector and a water requirement rule table; wherein the water requirement rule table is a table containing the relationship between the water requirement data corresponding to the soil property data and the planting vector.

[0047] In this step, the soil attribute data includes soil type, soil texture, etc. The soil type may be, for example, gray soil, grassland soil, red-yellow soil, alkaline soil, and alkaline soil. The soil texture may be, for example, sandy land, loam, and clay. Sandy land includes loose sand and tight sand, loam includes sandy loam, light loam, medium loam, and heavy loam, and clay includes light clay, medium clay, and heavy clay. This embodiment does not limit this.

[0048] Specifically, the soil property data of the target area and the planting vector of the target crop are obtained, the soil type and soil texture of the target area are determined, and the crop spatial range of the target area is determined. Then, the corresponding water demand data is found from the water demand rule table according to the soil type, soil texture and crop spatial range of the target area.

[0049] Step 104: Determine the regional irrigation result according to the soil moisture content data and the water demand data.

[0050] Specifically, after the water demand data is determined, the regional irrigation results are determined based on the soil moisture data and the water demand data.

[0051] In a specific embodiment, determining the regional irrigation result based on soil moisture data and water demand data includes: determining the irrigation method of the target area; determining the regional irrigation result based on the planting vector, irrigation method, soil moisture data and water demand data.

[0052] In this step, the irrigation method is the method set for the target area, such as sprinkler irrigation and drip irrigation, etc. The irrigation speed, irrigation duration, and irrigation range of the sprinkler irrigation and drip irrigation are also related to the pump room, water pump, pipe, water outlet pile, and matching solenoid valve set in the target area. This embodiment does not limit this.

[0053] Specifically, determine the irrigation speed, irrigation duration, irrigation range, etc. of the irrigation method set in the target area, and determine the regional irrigation results based on the planting vector, irrigation speed, irrigation duration, irrigation range, soil moisture data and water demand data of the irrigation method.

[0054] In a specific embodiment, the regional irrigation results are determined based on the planting vector, irrigation method, soil moisture data and water demand data, including: determining the irrigation water requirement based on the difference between the soil moisture data and the water demand data; determining the regional irrigation results based on the planting vector, irrigation method and irrigation water requirement.

[0055] In this step, the irrigation water requirement is the determined amount of water required for irrigation in the target area at this time. The irrigation water requirement is determined by the difference between the water requirement data and the soil moisture content data, that is, the irrigation water requirement = water requirement data - soil moisture content data.

[0056] Specifically, the irrigation water requirement is determined based on the difference between the water requirement data and the soil moisture content data, and then the regional irrigation result is determined based on the planting vector, the irrigation speed of the irrigation method, the irrigation duration, the irrigation range and the irrigation water requirement.

[0057] In this step, the regional irrigation result is to adjust the irrigation speed, irrigation duration and irrigation range of the irrigation method in real time based on the irrigation water demand and planting vector to achieve automatic irrigation of the target area.

[0058] Step 105: Control the target area for irrigation according to the regional irrigation result.

[0059] Specifically, after determining the regional irrigation results, the irrigation speed, irrigation duration and irrigation range of the irrigation method are adjusted in real time based on the irrigation water demand and planting vector to achieve automatic irrigation of the target area.

[0060] The advantage of this setting is that, in order to address the problem of inaccurate and inconvenient artificial irrigation, the soil moisture model outputs soil moisture data, and determines the regional irrigation results based on the soil moisture data and water demand data. The regional irrigation results link the irrigation method of the irrigation equipment set in the target area to automatically irrigate the target area. This will effectively solve the problem of inaccurate and inconvenient irrigation in traditional methods, and at the same time, solve the problem of water resource waste in traditional methods of artificial flooding.

[0061] The present invention provides an irrigation control method, which obtains satellite remote sensing image data and soil moisture data of a target area; wherein the satellite remote sensing image data is data corresponding to the target area acquired by remote sensing images, and the soil moisture data is soil moisture data corresponding to the target area acquired based on a surface sensing device set in the target area; the satellite remote sensing image data and the soil moisture data are input into a soil moisture model to obtain soil moisture content data corresponding to the target area output by the soil moisture model; wherein the soil moisture model is a model trained based on satellite remote sensing image sample data, soil moisture content sample data and corresponding soil moisture content data labels; determines water demand data of a target crop in the target area; wherein the water demand data is the water demand of the target crop in the target area under an ideal state; determines a regional irrigation result according to the soil moisture content data and the water demand data; and controls the target area to be irrigated according to the regional irrigation result. The technical solution of the present invention is used to solve the defects of the prior art that the method of manual irrigation leads to waste of irrigation water resources and inability to irrigate accurately, and realizes the collection of satellite remote sensing image data and soil moisture data of the target area based on remote sensing images and surface sensing equipment, and timely grasps the soil moisture data of the target area through the soil moisture model, so as to determine the regional irrigation result based on the soil moisture data and the water requirement data of the target crop in the target area, complete the accurate irrigation of the target area, and improve the efficiency and accuracy of automatic irrigation.

[0062] The irrigation control device provided by the present invention is described below. The irrigation control device described below and the irrigation control method described above can be referenced to each other.

[0063] Figure 2 is a schematic diagram of the structure of the irrigation control device provided by the present invention, referring to Figure 2 As shown, the irrigation control device 200 includes: a data acquisition module 201, a data output module 202, a data determination module 203, a result determination module 204 and an irrigation control module 205.

[0064] The data acquisition module 201 is used to acquire satellite remote sensing image data and soil moisture data of the target area; wherein the satellite remote sensing image data is data corresponding to the target area acquired by remote sensing images, and the soil moisture data is soil moisture data corresponding to the target area acquired based on surface sensing equipment set in the target area.

[0065] The data output module 202 is used to input satellite remote sensing image data and soil moisture data into the soil moisture model to obtain soil moisture data corresponding to the target area output by the soil moisture model; wherein the soil moisture model is a model trained based on satellite remote sensing image sample data, soil moisture sample data and corresponding soil moisture data labels.

[0066] The data determination module 203 is used to determine the water requirement data of the target crop in the target area; wherein the water requirement data is the water requirement of the target crop in the target area under an ideal state.

[0067] The result determination module 204 is used to determine the regional irrigation result according to the soil moisture content data and the water demand data.

[0068] The irrigation control module 205 is used to control the target area to be irrigated according to the regional irrigation result.

[0069] In an exemplary embodiment, the device further includes: a model training module. The model training module is used to: obtain satellite remote sensing image sample data, soil moisture sample data, soil water content data labels and a basic soil moisture inversion model; wherein the basic soil moisture inversion model is a predetermined basic model for inverting soil moisture; and train the basic soil moisture inversion model according to the satellite remote sensing image sample data, the soil moisture sample data and the soil water content data labels to obtain a soil moisture model.

[0070] In an exemplary embodiment, the data output module 202 is specifically used to: input the satellite remote sensing image data into a feature variable selector of a soil moisture model to obtain a feature selection result output by the feature variable selector; wherein the feature variable operator is an operator that performs multi-band combination operations on the satellite remote sensing image data, and the feature selection result includes a variety of vegetation indices obtained by performing multi-band combination operations on the satellite remote sensing image data; input the feature selection result and soil moisture data into a classification selector of the soil moisture model to obtain soil moisture content data corresponding to the target area output by the classification selector; wherein the classification selector is a selector that selects a variety of vegetation indices that conform to the soil moisture data from the feature selection results.

[0071] In an exemplary embodiment, the data determination module 203 is specifically used to: obtain soil property data of a target area and a planting vector of a target crop; wherein the planting vector is the crop space range of the target crop in the target area; determine the water requirement data of the target crop in the target area based on the soil property data, the planting vector and a water requirement rule table; wherein the water requirement rule table is a table containing the relationship between the water requirement data corresponding to the soil property data and the planting vector.

[0072] In an exemplary embodiment, the result determination module 204 is specifically used to: determine the irrigation method of the target area; and determine the regional irrigation result according to the planting vector, the irrigation method, the soil moisture data, and the water demand data.

[0073] In an exemplary embodiment, the result determination module 204 determines the regional irrigation result based on the planting vector, irrigation method, soil moisture data and water demand data, and is specifically used to: determine the irrigation water requirement based on the difference between the soil moisture data and the water demand data; determine the regional irrigation result based on the planting vector, irrigation method and irrigation water demand.

[0074] The device of this embodiment can be used to execute the method of any embodiment in the irrigation control method side embodiment. Its specific implementation process and technical effects are similar to those in the irrigation control method side embodiment. For details, please refer to the detailed description in the irrigation control method side embodiment, which will not be repeated here.

[0075] Figure 3 is a schematic diagram of the structure of the electronic device provided by the present invention, such as Figure 3 As shown, the electronic device may include: a processor 310 , a communications interface 320 , a memory 330 and a communication bus 340 , wherein the processor 310 , the communications interface 320 , and the memory 330 communicate with each other via the communication bus 340 . The processor 310 can call the logic instructions in the memory 330 to execute the irrigation control method, which includes: obtaining satellite remote sensing image data and soil moisture data of the target area; wherein the satellite remote sensing image data is the data corresponding to the target area collected by the remote sensing image, and the soil moisture data is the soil moisture data corresponding to the target area collected based on the surface sensing equipment set in the target area; inputting the satellite remote sensing image data and the soil moisture data into the soil moisture model to obtain the soil moisture content data corresponding to the target area output by the soil moisture model; wherein the soil moisture model is a model trained based on satellite remote sensing image sample data, soil moisture sample data and corresponding soil moisture content data labels; determining the water requirement data of the target crop in the target area; wherein the water requirement data is the water requirement of the target crop in the target area under ideal conditions; determining the regional irrigation result according to the soil moisture content data and the water requirement data; and controlling the target area to irrigate according to the regional irrigation result.

[0076] In addition, the logic instructions in the above-mentioned memory 330 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0077] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the irrigation control method provided by the above methods, which includes: obtaining satellite remote sensing image data and soil moisture data of the target area; wherein the satellite remote sensing image data is data corresponding to the target area collected by remote sensing images, and the soil moisture data is soil moisture data corresponding to the target area collected based on a surface sensing device set in the target area; inputting the satellite remote sensing image data and the soil moisture data into a soil moisture model to obtain soil moisture content data corresponding to the target area output by the soil moisture model; wherein the soil moisture model is a model trained based on satellite remote sensing image sample data, soil moisture sample data and corresponding soil moisture content data labels; determining water requirement data of target crops in the target area; wherein the water requirement data is the water requirement of the target crops in the target area under ideal conditions; determining regional irrigation results based on the soil moisture content data and the water requirement data; and controlling the target area for irrigation based on the regional irrigation results.

[0078] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the irrigation control method provided by the above-mentioned methods, the method comprising: obtaining satellite remote sensing image data and soil moisture data of a target area; wherein the satellite remote sensing image data is data corresponding to the target area acquired by remote sensing images, and the soil moisture data is soil moisture data corresponding to the target area acquired based on a surface sensing device arranged in the target area; inputting the satellite remote sensing image data and the soil moisture data into a soil moisture model to obtain soil moisture content data corresponding to the target area output by the soil moisture model; wherein the soil moisture model is a model trained based on satellite remote sensing image sample data, soil moisture sample data and corresponding soil moisture content data labels; determining water requirement data of a target crop in the target area; wherein the water requirement data is the water requirement of the target crop in the target area under ideal conditions; determining a regional irrigation result based on the soil moisture content data and the water requirement data; and controlling irrigation of the target area based on the regional irrigation result.

[0079] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0080] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0081] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An irrigation control method, characterized in that: include: Acquire satellite remote sensing image data and soil moisture data of the target area; wherein the satellite remote sensing image data is data corresponding to the target area collected by remote sensing images, and the soil moisture data is soil moisture data corresponding to the target area collected by surface sensing equipment; Inputting the satellite remote sensing image data and the soil moisture data into a soil moisture model to obtain soil moisture data corresponding to the target area output by the soil moisture model; wherein the soil moisture model is a model trained based on satellite remote sensing image sample data, soil moisture sample data and corresponding soil moisture data labels; Determine the water requirement data of the target crop in the target area; wherein the water requirement data is the water requirement of the target crop in the target area under an ideal state; Determine regional irrigation results based on the soil moisture data and the water demand data; The target area is controlled to be irrigated according to the regional irrigation result.

2. The irrigation control method according to claim 1, characterized in that: The training process of the soil moisture model includes: Acquire the satellite remote sensing image sample data, the soil moisture sample data, the soil moisture content data label and the basic soil moisture inversion model; wherein the basic soil moisture inversion model is a predetermined basic model for inverting soil moisture; The basic soil moisture inversion model is trained according to the satellite remote sensing image sample data, the soil moisture sample data, and the soil moisture content data label to obtain the soil moisture model.

3. The irrigation control method according to claim 1, characterized in that: The step of inputting the satellite remote sensing image data and the soil moisture data into a soil moisture model to obtain soil moisture content data corresponding to the target area output by the soil moisture model comprises: The satellite remote sensing image data is input into the feature variable selector of the soil moisture model to obtain a feature selection result output by the feature variable selector; wherein the feature variable operator is an operator for performing multi-band combination operation on the satellite remote sensing image data, and the feature selection result includes a plurality of vegetation indices obtained by performing multi-band combination operation on the satellite remote sensing image data; The feature selection results and the soil moisture data are input into the classification selector of the soil moisture model to obtain the soil moisture content data corresponding to the target area output by the classification selector; wherein the classification selector is a selector for selecting the multiple vegetation indices that meet the soil moisture data from the feature selection results.

4. The irrigation control method according to claim 1, characterized in that: The step of determining the water requirement data of the target crop in the target area comprises: Acquire soil property data of the target area and a planting vector of the target crop; wherein the planting vector is a crop spatial range of the target crop in the target area; The water requirement data of the target crop in the target area is determined according to the soil property data, the planting vector and the water requirement rule table; wherein the water requirement rule table is a table containing the relationship between the soil property data and the water requirement data corresponding to the planting vector.

5. The irrigation control method according to claim 4, characterized in that: The determining of the regional irrigation result according to the soil moisture content data and the water demand data comprises: determining an irrigation method for the target area; The regional irrigation result is determined according to the planting vector, the irrigation method, the soil moisture content data and the water demand data.

6. The irrigation control method according to claim 5, characterized in that: The determining of the regional irrigation result according to the planting vector, the irrigation method, the soil moisture data and the water demand data comprises: Determine the irrigation water requirement according to the difference between the soil moisture content data and the water requirement data; The regional irrigation result is determined according to the planting vector, the irrigation method and the irrigation water requirement.

7. An irrigation control device, characterized in that: include: A data acquisition module, used to acquire satellite remote sensing image data and soil moisture data of a target area; wherein the satellite remote sensing image data is data corresponding to the target area acquired by remote sensing images, and the soil moisture data is soil moisture data corresponding to the target area acquired based on a surface sensing device set in the target area; A data output module, used for inputting the satellite remote sensing image data and the soil moisture data into a soil moisture model to obtain the soil moisture data corresponding to the target area output by the soil moisture model; wherein the soil moisture model is a model trained based on satellite remote sensing image sample data, soil moisture sample data and corresponding soil moisture data labels; A data determination module, used to determine the water requirement data of the target crop in the target area; wherein the water requirement data is the water requirement of the target crop in the target area under an ideal state; A result determination module, used for determining a regional irrigation result according to the soil moisture content data and the water demand data; The irrigation control module is used to control the target area for irrigation according to the regional irrigation result.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the irrigation control method according to any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the irrigation control method according to any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the irrigation control method according to any one of claims 1 to 6 is implemented.

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