CN115687850A - Method and device for calculating irrigation water demand of farmland - Google Patents
Method and device for calculating irrigation water demand of farmland Download PDFInfo
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Abstract
The invention provides a method and a device for calculating irrigation water demand of a farmland, belonging to the technical field of agricultural information, wherein the method comprises the following steps: performing image segmentation on a target image of a farmland according to color characteristics, and determining a target area where a green crop in the target image is located; determining the coverage rate of green crops according to the ratio of the number of pixels of the target area to the total number of pixels of the target image; and determining the irrigation water demand of the farmland according to the coverage rate and the meteorological data. The invention utilizes an image segmentation method based on color characteristics to calculate the crop coverage rate, calculates to obtain the crop coefficient, and then calculates to obtain the crop water demand according to the crop coefficient and the reference crop evapotranspiration amount, thereby changing the traditional crop water demand calculation mode, realizing the automatic calculation of the crop water demand, improving the production efficiency and saving the cost.
Description
Technical Field
The invention relates to the technical field of agricultural information, in particular to a method and a device for calculating irrigation water demand of a farmland.
Background
At present, the waste of agricultural water is quite serious, the utilization rate is low, and the development of water-saving agriculture is one of important measures taken by countries in the world. The crop water demand is an important component of agricultural water, and the reasonable and accurate estimation of the crop water demand is a basis for determining a scientific and reasonable crop irrigation system, regional irrigation water consumption and implementing fine irrigation.
The determination of the water demand of crops is the basis of designated reasonable irrigation, generally, empirical parameters are selected, but due to the difference of planting varieties and agricultural measures, the accuracy of standard crop coefficients is not high, and further, the calculation accuracy of the water demand of the irrigation amount is low.
Disclosure of Invention
The invention provides a method and a device for calculating irrigation water demand of a farmland, which are used for solving the defect of low calculation precision of the irrigation water demand in the prior art.
In a first aspect, the present invention provides a method for calculating an irrigation water demand of a farm field, comprising: performing image segmentation on a target image of a farmland according to color characteristics, and determining a target area where a green crop in the target image is located; determining the coverage rate of green crops according to the ratio of the number of pixels in the target area to the total number of pixels in the target image; and determining the irrigation water demand of the farmland according to the coverage rate and the meteorological data.
According to the irrigation water demand calculation method for the farmland, provided by the invention, the determination of the irrigation water demand of the farmland based on the coverage rate and the meteorological data comprises the following steps: inputting the coverage rate into a crop coefficient target estimation model to obtain a crop coefficient of the green crop; determining the evaporation capacity of the reference crops of the farmland according to the crop coefficient and the meteorological data; and determining the irrigation water demand of the farmland based on the crop coefficient and the reference crop evapotranspiration amount.
According to the irrigation water demand calculation method for the farmland, provided by the invention, before the image segmentation is carried out on the target image of the farmland according to the color characteristics and the target area where the green crop is located in the target image is determined, the method further comprises the following steps: acquiring an initial image of the farmland by using image acquisition equipment; optimizing the initial image by using a noise reduction algorithm and a perspective transformation method to obtain a target image; the image acquisition equipment comprises a mobile phone.
According to the farmland irrigation water demand calculation method provided by the invention, the step of establishing the crop coefficient estimation model comprises the following steps of: acquiring a plurality of target image sample sets with the same number, taking one of the target image sample sets as a target image test set, and taking each of the other target image sample sets as a target image training set; establishing a corresponding crop coefficient estimation model by utilizing each target image training set according to the functional relation between the coverage rate of the target image sample and the crop coefficient; and testing each crop coefficient estimation model by using the target image test set, and taking the optimal crop coefficient estimation model as a crop coefficient target estimation model.
According to the method for calculating the irrigation water demand of the farmland, provided by the invention, the reference crop evapotranspiration of the farmland is determined according to the crop coefficient and the meteorological data, and the calculation formula is as follows:
R n ＝R ns -R nl ；
G＝0.38(T d -T d-1 )；
γ＝0.00163P/λ；
U 2 ＝4.87·U h /ln(67.8h-5.42)；
ET 0 the evaporation capacity of the reference crop is the evaporation capacity; t is the average air temperature; delta is the tangent slope of the temperature-saturated water vapor pressure relation curve at the T position; r n For net solar radiation, R ns For radiation of static short waves, R nl Radiation of static long wave; g is the soil heat flux, ET is estimated for each day 0 Calculating the soil heat flux, T, on day d d And T d-1 The average air temperature on day d and day d-1, respectively; gamma is a thermometer constant, and lambda is latent heat; u shape 2 Wind speed at 2 m height, h height, U h Is the wind speed at height h; e.g. of the type a Saturated water vapor pressure; e.g. of the type d Is the actual water vapour pressure, wherein T min The daily minimum temperature, T max The daily maximum temperature, P is the precipitation amount of the day.
According to the farmland irrigation water demand calculation method provided by the invention, the farmland irrigation water demand is determined based on the crop coefficient and the reference crop evaporation capacity, and the specific formula is as follows:
ET c ＝K c *ET 0 ；
wherein, ET c For irrigation Water requirement, K c Is the crop coefficient.
In a second aspect, the present invention also provides an apparatus for calculating an irrigation water demand of an agricultural field, comprising:
the first processing module is used for carrying out image segmentation on a target image of a farmland according to color characteristics and determining a target area where a green crop in the target image is located;
the second processing module is used for determining the coverage rate of green crops according to the ratio of the number of pixels in the target area to the total number of pixels in the target image;
and the third processing module is used for determining the irrigation water demand of the farmland according to the coverage rate and the meteorological data.
In a third aspect, the present invention provides an electronic device, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to perform the steps of the method for calculating irrigation water demand of agricultural field as described in any one of the above.
In a fourth aspect, the present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method for calculating irrigation water demand for agricultural fields as described in any one of the above.
In a fifth aspect, the invention also provides a computer program product comprising a computer program which, when executed by a processor, carries out the steps of the method for calculating the irrigation water demand of an agricultural field as defined in any one of the preceding claims
The invention utilizes an image segmentation method based on color characteristics to calculate the crop coverage rate, calculates to obtain the crop coefficient, and then calculates to obtain the crop water demand according to the crop coefficient and the reference crop evapotranspiration amount, thereby changing the traditional crop water demand calculation mode, realizing the automatic calculation of the crop water demand, improving the production efficiency and saving the cost.
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In order to more clearly illustrate the technical solutions of the present invention or the prior art, the drawings needed for the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart of a method for calculating the irrigation water demand of a farm field according to the present invention;
FIG. 2 is a second schematic flow chart of the method for calculating irrigation water demand of agricultural land according to the present invention;
FIG. 3 is a schematic view of a device for calculating the irrigation water demand of an agricultural field according to the present invention;
fig. 4 is a schematic structural diagram of an electronic device provided in the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that, in the description of the embodiments of the present invention, the terms "comprises," "comprising," or any other variation thereof are intended to cover a non-exclusive inclusion, so that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but also other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrases "comprising a," "8230," "8230," or "comprising" does not exclude the presence of additional like elements in a process, method, article, or apparatus that comprises the element. The terms "upper", "lower", and the like, indicate orientations or positional relationships that are based on the orientations or positional relationships shown in the drawings, are merely for convenience in describing the present invention and to simplify the description, and do not indicate or imply that the referenced devices or elements must have a particular orientation, be constructed and operated in a particular orientation, and thus, are not to be construed as limiting the present invention. Unless expressly stated or limited otherwise, the terms "mounted," "connected," and "coupled" are to be construed broadly and encompass, for example, both fixed and removable coupling as well as integral coupling; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood according to specific situations by those of ordinary skill in the art.
The terms "first," "second," and the like in this application are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that embodiments of the application are capable of operation in sequences other than those illustrated or described herein, and that the terms "first," "second," etc. are generally used in a generic sense and do not limit the number of terms, e.g., a first term can be one or more than one.
In recent years, computer vision technology has been applied to agricultural engineering on a large scale. The computer vision comprises the aspects of target detection, image processing and the like, a camera is used for replacing human eyes to identify and measure the target, and the image processing is further carried out. Research shows that suitable computer vision algorithms can be used for many tasks, such as fruit grading and monitoring, grain germplasm inspection and evaluation, plant growth state monitoring and the like. The advent of computer vision has provided a new approach for non-destructive analysis of crop parameters. The color and biological characteristics of crops are recognized through a machine vision technology, and the property parameters of the crops, such as baldness rate, ear row number, line grain number and the like, can be accurately detected and calculated. The invention provides a method for calculating the irrigation water demand of a farmland based on a computer vision technology, which is used for guiding reasonable irrigation and has the advantages of online no damage, low cost and high implementability.
The method and the device for calculating the irrigation water demand of the farmland provided by the embodiment of the invention are described in the following by combining figures 1-4.
FIG. 1 is a schematic flow diagram of a method for calculating the irrigation water demand of a farm field according to the present invention, as shown in FIG. 1, including but not limited to the following steps:
step 101: and carrying out image segmentation on the target image of the farmland according to the color characteristics, and determining the target area where the green crop in the target image is located.
The green crops in the farmland are obviously distinguished from the background land in color, and the segmentation of different areas can be realized through the color characteristics of different areas in the target image. For example, a region in the target image where the green component proportion is large is set as the target region. The background can be taken out of the target image by an image segmentation technology, and the green crop image is reserved.
Step 102: and determining the coverage rate of the green crops according to the ratio of the number of the pixels in the target area to the total number of the pixels in the target image.
After the image segmentation based on the color features is applied, the ratio of the pixel number (namely the pixel number of green crops) of the target area to the total pixel number of the target image is as follows:
PGC＝px_crop/px_img；
the PGC is the coverage rate of green crops, px _ crop is the number of pixels in the target area, and px _ img is the total number of pixels in the target image.
Step 103: and determining the irrigation water demand of the farmland according to the coverage rate and the meteorological data.
The meteorological data comprise temperature, solar radiation, average temperature, wind speed, air pressure and other data. The crop coefficient of the green crop can be deduced based on the coverage rate, and the evaporation capacity of the reference crop is calculated according to a PM (Penman-Monteith) formula by combining meteorological data.
Further, the crop water demand is calculated according to the crop coefficient and the reference crop evaporation capacity so as to determine the irrigation water demand.
The invention utilizes an image segmentation method based on color characteristics to calculate the crop coverage rate, calculates to obtain the crop coefficient, and then calculates to obtain the crop water demand according to the crop coefficient and the reference crop evapotranspiration amount, thereby changing the traditional crop water demand calculation mode, realizing the automatic calculation of the crop water demand, improving the production efficiency and saving the cost.
Fig. 2 is a second schematic flow chart of the method for calculating irrigation water demand of agricultural fields according to the present invention, and as shown in fig. 2, the method for calculating irrigation water demand of agricultural fields according to the present invention includes: the system comprises an initial image acquisition unit, an image processing unit, a crop coefficient calculation unit, a reference crop evaporation amount calculation unit and an irrigation water demand calculation unit. In order to more clearly explain the technical solution of the present invention, the following describes the technical solution of the present invention with reference to specific examples.
Based on the content of the foregoing embodiment, as an optional embodiment, the method for calculating irrigation water demand of a farm field according to the present invention further includes, before performing image segmentation on a target image of the farm field according to color features and determining a target area where a green crop is located in the target image: acquiring an initial image of the farmland by using image acquisition equipment; and optimizing the initial image by using a noise reduction algorithm and a perspective transformation method to obtain a target image.
The invention takes the mobile phone photographing as the source of the initial image, and collects the initial image for a plurality of times in the whole growth cycle of the crop.
The invention provides a method for calculating irrigation water demand of a farmland, which is a main image acquisition device with low-cost mobile phone shooting, realizes that crop coefficients can be automatically calculated only by a handheld shooting mode, reduces the cost required by shooting equipment, and increases the flexibility of a data acquisition mode.
Optionally, the image processing unit of the present invention performs optimization processing on the initial image by using a noise reduction algorithm and a perspective transformation method to obtain a target image. The following describes a procedure of the image processing unit of the present invention for performing optimization processing on an initial image.
The noise of the initial image acquired by the invention mainly comes from the acquisition process and the transmission process. The noise source of the invention is mainly Gaussian noise. For the gaussian noise present in the initial image, the present invention will use a gaussian filter to process the gaussian noise present. The Gaussian filter is used as a smoothing processing algorithm with wide application, can well reduce image noise, and meanwhile, the filter does not eliminate image details due to noise removal.
For the noisy image T (x) acquired in the present invention, its additive noise is expressed by the following formula:
T(x)＝S(x)+η(x)，x∈Ω
t (x) represents a noisy initial image, S (x) represents a non-noisy initial image, and η (x) is an additive noise term; and Ω is the total pixel point contained in the whole initial image. After removing the noise term, an initial image without noise can be obtained.
The smoothing coefficients in the gaussian filter are replaced with exponential smoothing:
where α is a smoothing coefficient and t represents time.
The invention solves three-dimensional distortion by a perspective transformation method. Perspective transformation is a process of transforming a three-dimensional image, and affine transformation is a process of transforming a two-dimensional image. And after the coordinates of a group of four points in the distorted image and a group of four points in the target image are obtained, perspective transformation is applied to correct the distorted image. And calculating a transformation matrix of perspective transformation through the two groups of coordinate points, and further transforming the whole original image to realize image correction.
Converting a world coordinate system and a camera coordinate system, wherein the world coordinate is (X, Y, Z) and the camera coordinate is (X) C ，Y C ，Z C ) Between world coordinates and camera coordinates there are a rotation transformation matrix R and a displacement transformation matrix T.
The applied conversion formula from the world coordinate system to the camera coordinate system is:
the coordinates of four points in the distorted image are four vertexes of the standard frame of the reference object, and the coordinates of four points in the target image are four vertexes of the image. Since the viewing angle is large and the converted image is stretched in the height direction, the corrected image contrast is reduced but its basic color characteristics are not changed much.
Because the environment of image acquisition is a complex natural condition, the influence of image noise and distortion is easy to generate in the process of collecting pictures. The method well weakens the influence of environmental factors on the later image segmentation through a denoising algorithm and perspective distortion correction.
Because the light intensity change and shadow in the image can influence the image segmentation quality and have great influence on the subsequent crop identification, the accurate extraction of the crop color features is the key of the image segmentation. The color distribution characteristics of the crops are analyzed to accurately segment the green crops from the soil background image. The crop stem leaf color is mainly green and yellow in different degrees, so the method selects a plurality of color images for image segmentation under the RGB space condition.
By comparing the crop color models, the proportion of the green G component is the largest, the red R component is the second, and the blue B component is the smallest, so that the component operators 2G-B and 2G-R are applied as color operators for image processing. In order to keep the color information in the original image as much as possible, the component operator 0.299 r +0.587 g +0.114 b for converting the default color image into the gray image also corresponds to the proportion of each component. In summary, the operator fusion formula using the RGB space is:
neither the 2G-B,2G-R and 0.299R + 0.587G + 0.114B operators alone nor the operators fused two by two distinguish green crops from the background. In the image fused by the three operators, the difference between the gray value of the green crop and the background is the largest, so that grass and the background can be distinguished, and the segmentation effect is achieved. Because the histogram distribution of the gray level image has a peak trend, three color difference characteristics of the green crop class image are used as an image operator to solve the problem of converting the three-dimensional processing of the color image into one-dimensional processing of the gray level image.
Based on the content of the foregoing embodiment, as an alternative embodiment, the present invention further provides a method for calculating irrigation water demand of a farm field, wherein the step of establishing the crop coefficient estimation model includes: acquiring a plurality of target image sample sets with the same number, taking one of the target image sample sets as a target image test set, and taking each of the other target image sample sets as a target image training set; establishing a corresponding crop coefficient estimation model by utilizing each target image training set according to the functional relation between the coverage rate of the target image sample and the crop coefficient; and testing each crop coefficient estimation model by using the target image test set, and taking the optimal crop coefficient estimation model as a crop coefficient target estimation model.
Specifically, 800 target images are acquired, and are averagely divided into 4 target image sample sets, namely S1, S2, S3 and S4. Wherein S1, S2 and S3 are target image training sets, and S4 is a target image testing set.
And establishing a crop coefficient estimation model aiming at each target image training set S1, S2 and S3, testing by using a target image testing set S4, and selecting the crop coefficient estimation model with the highest accuracy as the crop coefficient target estimation model.
Optionally, the crop coefficient target estimation model is a nonlinear relation model of coverage and crop coefficient, and the specific formula is as follows:
K C ＝2.137PGC 2 -1.24PGC+0.2091
wherein, K C The crop coefficient for green crops and the PGC is the coverage of green crops.
According to the method, aiming at the condition that noise and distortion exist in image data obtained by mobile phone photographing, a denoising and perspective transformation method is used for optimizing a picture, finally, an image segmentation algorithm based on color space characteristics is used for calculating the crop coverage rate, a crop coefficient estimation model is established, inversion of crop coefficients is realized, and after a reference crop evapotranspiration amount is calculated, the crop water demand is further calculated.
Based on the content of the foregoing embodiment, as an optional embodiment, the method for calculating irrigation water demand of a farm field according to the present invention, which is based on the coverage rate and combined with meteorological data, includes: inputting the coverage rate into a crop coefficient target estimation model to obtain a crop coefficient of the green crop; determining the evapotranspiration amount of the reference crops of the farmland according to the crop coefficient and the weather data; and determining the irrigation water demand of the farmland based on the crop coefficient and the reference crop evapotranspiration amount.
Wherein, according to the crop coefficient and the meteorological data, the specific formula for determining the evapotranspiration amount of the reference crop in the farmland is as follows:
R n ＝R ns -R nl ；
G＝0.38(T d -T d-1 )；
γ＝0.00163P/λ；
U 2 ＝4.87·U h /ln(67.8h-5.42)；
ET 0 the evapotranspiration amount of the reference crop is determined; t is the average air temperature; delta is the tangent slope of the temperature-saturated water vapor pressure relation curve at the T position; r n For net solar radiation, R ns For radiation of static short waves, R nl Is static long wave radiation; g is the soil heat flux, ET is estimated for each day 0 Calculating the soil heat flux, T, on day d d And T d-1 The average air temperature on day d and day d-1, respectively; gamma is a thermometer constant, and lambda is latent heat; u shape 2 Wind speed at 2 m height, h height, U h Is the wind at height hSpeed; e.g. of the type a Saturated water vapor pressure; e.g. of the type d Is the actual water vapor pressure, wherein T min Is the daily lowest temperature, T max The daily maximum temperature and P the precipitation amount of the day.
ET c Can ET o And K C And calculating according to the following calculation formula:
ET c ＝K c *ET 0
wherein, ET 0 The water requirement of crops.
Fig. 3 is a schematic view showing the structure of an apparatus for calculating irrigation water demand of agricultural field according to the present invention, as shown in fig. 3, the apparatus comprising: a first processing module 301, a second processing module 302, and a third processing module 303.
The first processing module 301 is configured to perform image segmentation on a target image of a farmland according to color features, and determine a target area where a green crop in the target image is located;
a second processing module 302, configured to determine a coverage rate of a green crop according to a ratio of the number of pixels in the target area to the total number of pixels in the target image;
and the third processing module 303 is used for determining the irrigation water demand of the farmland according to the coverage rate and the meteorological data.
The invention utilizes an image segmentation method based on color characteristics to calculate the crop coverage rate, calculates to obtain the crop coefficient, and then calculates to obtain the crop water demand according to the crop coefficient and the reference crop evapotranspiration amount, thereby changing the traditional crop water demand calculation mode, realizing the automatic calculation of the crop water demand, improving the production efficiency and saving the cost.
It should be noted that, when the apparatus for calculating irrigation water demand of a farm field according to the embodiment of the present invention is in specific operation, the method for calculating irrigation water demand of a farm field according to any one of the above embodiments may be executed, and details of this embodiment are not described herein.
Fig. 4 is a schematic structural diagram of an electronic device provided in the present invention, and as shown in fig. 4, the electronic device may include: a processor (processor) 410, a communication Interface 420, a memory (memory) 430 and a communication bus 440, wherein the processor 410, the communication Interface 420 and the memory 430 are communicated with each other via the communication bus 440. The processor 410 may invoke logic instructions in the memory 430 to perform a method of calculating irrigation water demand for an agricultural field, the method comprising: performing image segmentation on a target image of a farmland according to color characteristics, and determining a target area where a green crop in the target image is located; determining the coverage rate of green crops according to the ratio of the number of pixels of the target area to the total number of pixels of the target image; and determining the irrigation water demand of the farmland according to the coverage rate and the meteorological data.
In addition, the logic instructions in the memory 430 may be implemented in the form of software functional units and stored in a computer readable storage medium when the software functional units are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In another aspect, the present invention also provides a computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions, which when executed by a computer, the computer is capable of executing the method for calculating irrigation water demand of agricultural fields provided by the above embodiments, the method comprising: performing image segmentation on a target image of a farmland according to color characteristics, and determining a target area where a green crop in the target image is located; determining the coverage rate of green crops according to the ratio of the number of pixels of the target area to the total number of pixels of the target image; and determining the irrigation water demand of the farmland according to the coverage rate and the meteorological data.
In yet another aspect, the present invention further provides a non-transitory computer readable storage medium, on which a computer program is stored, the computer program being implemented by a processor to perform the method for calculating irrigation water demand of an agricultural field according to the embodiments described above, the method including: performing image segmentation on a target image of a farmland according to color characteristics, and determining a target area where a green crop in the target image is located; determining the coverage rate of green crops according to the ratio of the number of pixels of the target area to the total number of pixels of the target image; and determining the irrigation water demand of the farmland according to the coverage rate and the meteorological data.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one position, or 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 solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment may be implemented by software plus a necessary general hardware platform, and may also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for calculating the irrigation water demand of a farmland is characterized by comprising the following steps:
performing image segmentation on a target image of a farmland according to color characteristics, and determining a target area where a green crop in the target image is located;
determining the coverage rate of green crops according to the ratio of the number of pixels of the target area to the total number of pixels of the target image;
and determining the irrigation water demand of the farmland according to the coverage rate and the meteorological data.
2. The method of claim 1, wherein determining the irrigation water demand of the agricultural field based on the coverage rate in combination with weather data comprises:
inputting the coverage rate into a crop coefficient target estimation model to obtain a crop coefficient of the green crop;
determining the evaporation capacity of the reference crops of the farmland according to the crop coefficient and the meteorological data;
and determining the irrigation water demand of the farmland based on the crop coefficient and the reference crop evapotranspiration amount.
3. The method of claim 1, wherein before performing image segmentation on a target image of an agricultural field according to color features and determining a target region where a green crop is located in the target image, the method further comprises:
acquiring an initial image of the farmland by using image acquisition equipment;
optimizing the initial image by using a noise reduction algorithm and a perspective transformation method to obtain a target image;
the image acquisition equipment comprises a mobile phone.
4. The method of claim 2, wherein the step of establishing the crop coefficient estimation model comprises:
acquiring a plurality of target image sample sets with the same number, taking one of the target image sample sets as a target image test set, and taking each of the other target image sample sets as a target image training set;
establishing a corresponding crop coefficient estimation model by utilizing each target image training set according to the functional relation between the coverage rate of the target image sample and the crop coefficient;
and testing each crop coefficient estimation model by using the target image test set, and taking the optimal crop coefficient estimation model as a crop coefficient target estimation model.
5. The method of claim 2, wherein the reference crop evapotranspiration of the agricultural field is determined according to the crop coefficient and the meteorological data, and the calculation formula is as follows:
R n ＝R ns -R nl ；
G＝0.38(T d -T d-1 )；
γ＝0.00163P/λ；
U 2 ＝4.87·U h /ln(67.8h-5.42)；
ET 0 the evapotranspiration amount of the reference crop is determined; t is the average air temperature; delta is the tangent slope of the temperature-saturated water vapor pressure relation curve at the T position; r n For net solar radiation, R ns For radiation of static short waves, R nl Is static long wave radiation; g is the soil heat flux, ET is estimated for each day 0 Calculating the soil heat flux, T, on day d d And T d-1 The average air temperature on day d and day d-1, respectively; gamma is a thermometer constant, and lambda is latent heat; u shape 2 Wind speed at 2 m height, h height, U h Is the wind speed at height h; e.g. of the type a Saturated water vapor pressure; e.g. of the type d Is the actual water vapor pressure, wherein T min The daily minimum temperature, T max The daily maximum temperature and P the precipitation amount of the day.
6. The method of calculating irrigation water demand of an agricultural field according to claim 2, wherein the determining of the irrigation water demand of the agricultural field based on the crop coefficient and the reference crop evapotranspiration is performed by a specific formula of:
ET c ＝K c *ET 0 ；
wherein, ET c Water requirement for irrigation, K c Is the crop coefficient.
7. An apparatus for calculating an irrigation water demand of an agricultural field, comprising:
the first processing module is used for carrying out image segmentation on a target image of a farmland according to color characteristics and determining a target area where a green crop in the target image is located;
the second processing module is used for determining the coverage rate of green crops according to the ratio of the number of pixels of the target area to the total number of pixels of the target image;
and the third processing module is used for determining the irrigation water demand of the farmland according to the coverage rate and the meteorological data.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the computer program performs the steps of the method for calculating irrigation water demand for an agricultural field according to any one of claims 1 to 6.
9. A non-transitory computer readable storage medium having stored thereon a computer program, wherein the computer program when executed by a processor implements the steps of the method for calculating irrigation water demand for an agricultural field according to any one of claims 1 to 6.
10. A computer program product comprising a computer program, wherein the computer program when executed by a processor implements the steps of a method for calculating the irrigation water demand of an agricultural field according to any one of claims 1 to 6.
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