Wheat freeze injury monitoring method and system for wheat cultivation

Abstract

The invention relates to the technical field of remote sensing monitoring, in particular to a wheat freeze injury monitoring method and system for wheat cultivation. The method comprises the following steps: firstly, dividing a to-be-analyzed wheat freeze injury area from a monitoring area according to a freeze injury deterioration index of each wheat unit area at the current moment; according to the health deterioration measurement of each wheat unit area in the to-be-analyzed wheat freeze injury area in the monitoring time period, obtaining the freeze injury obvious degree of the to-be-analyzed wheat freeze injury area in the monitoring time period; acquiring the freeze injury severity of the to-be-analyzed wheat freeze injury area according to the freeze injury obvious degree of the to-be-analyzed wheat freeze injury area in each monitoring time period and the time sequence change condition and the freeze injury obvious degree of the current time period; and according to the freeze injury severity, performing freeze injury risk type division on the to-be-analyzed wheat freeze injury area. According to the method, the accuracy of monitoring the freezing injury risk is improved by fully considering the specific expression condition of the freezing injury characteristics of the wheat and the change condition along with time.

Description

Technical Field

[0001] The present invention relates to the technical field of remote sensing monitoring, and particularly relates to a method and system for monitoring wheat freezing injury for wheat cultivation. Background Art

[0002] Wheat cultivation refers to the whole process from sowing, growing to harvesting through scientific planting management techniques to ensure high yield and quality of wheat. Wheat freezing injury monitoring is an important part of wheat cultivation. Early freezing injury monitoring of wheat can timely monitor in the initial stage of freezing injury, quickly determine the affected areas and degrees, and provide time for remedial measures. Through freezing injury monitoring, the impact of freezing injury on wheat yield can be effectively reduced, ensuring the stability and sustainability of wheat production.

[0003] The prior art usually only analyzes the numerical values of real-time vegetation indicators in the monitoring area to classify the types of wheat freezing injury risks. When using the prior art to classify the types of wheat freezing injury risks, the specific manifestations of the freezing injury characteristics of wheat and their changes over time are not fully considered, resulting in inaccurate monitoring of the types of wheat freezing injury risks. Summary of the Invention

[0004] In order to solve the technical problem of inaccurate monitoring of wheat freezing injury risk types in the prior art, the purpose of the present invention is to provide a method and system for monitoring wheat freezing injury for wheat cultivation, and the specific technical solutions adopted are as follows: A method for monitoring wheat freezing injury for wheat cultivation, the method comprising: Obtaining a set of vegetation index data for each wheat unit area in the monitoring area; the set of vegetation index data includes chlorophyll content indexes, leaf area indexes, and freezing injury deterioration indexes at each sampling moment in each monitoring period; According to the reduction conditions of the chlorophyll content index and the leaf area index of the wheat unit area at the sampling moment, obtaining the health deterioration measure of the wheat unit area at the sampling moment; according to the freezing injury deterioration indexes of each wheat unit area in the monitoring area at the current moment, dividing the wheat freezing injury area to be analyzed from the monitoring area; according to the health deterioration measures of each wheat unit area in the wheat freezing injury area to be analyzed during the monitoring period, obtaining the obvious degree of freezing injury of the wheat freezing injury area to be analyzed during the monitoring period; According to the temporal change situation of the obvious degree of freezing injury of the wheat freezing injury area to be analyzed in each of the monitoring periods and the obvious degree of freezing injury in the current period, obtaining the severity of freezing injury of the wheat freezing injury area to be analyzed; according to the severity of freezing injury, classifying the types of freezing injury risks of the wheat freezing injury area to be analyzed.

[0005] Further, the method for obtaining the health deterioration measure includes: Take any sampling moment as the moment to be analyzed, and take the previous sampling moment of the moment to be analyzed as the reference moment; Calculate the mean of the chlorophyll content index and the leaf area index of the wheat unit area at the sampling moment to obtain the health metric of the wheat unit area at the sampling moment; Calculate the difference between the health metrics corresponding to the reference moment and the moment to be analyzed in the wheat unit area. If the difference is not less than zero, normalize the difference to obtain the health deterioration metric of the wheat unit area at the moment to be analyzed. If the difference is less than zero, set the health deterioration metric of the wheat unit area at the moment to be analyzed to 0.

[0006] Furthermore, the method for obtaining the wheat frost damage area to be analyzed includes: At the current moment, mark the wheat unit areas with the frost damage deterioration index greater than the preset deterioration threshold as frost damage unit areas; Take the Euclidean distance in the spatial dimension between every two frost damage unit areas as the distance metric between every two frost damage unit areas. According to the distance metric between every two frost damage unit areas, perform K-Means clustering on all frost damage unit areas in the monitoring area, and take each clustering cluster as each wheat frost damage area to be analyzed.

[0007] Furthermore, the method for obtaining the obvious degree of frost damage includes: For any monitoring period, obtain the health deterioration change rate of the wheat unit area during the monitoring period according to the health deterioration metrics corresponding to all sampling moments of the wheat unit area during the monitoring period; In the wheat frost damage area to be analyzed, cluster all wheat unit areas in the wheat frost damage area to be analyzed according to the absolute value of the difference between the health deterioration change rates of every two wheat unit areas to obtain each frost damage degree area; According to the spatial distribution and health deterioration change rate of the frost damage degree areas in the wheat frost damage area to be analyzed, obtain the obvious degree of frost damage of the wheat frost damage area to be analyzed during the monitoring period.

[0008] Furthermore, the method for obtaining the health deterioration change rate includes: Based on a two-dimensional coordinate system, that is, the horizontal axis of the two-dimensional coordinate is the sampling moment and the vertical axis is the value of the health deterioration metric. Take the health deterioration metric corresponding to each sampling moment as a data point, and count the data points of all sampling moments of the wheat unit area during the monitoring period as fitting data points. Use the least squares method to perform linear fitting on all fitting data points to obtain a fitting line. Take the slope of the fitting line as the health deterioration change rate of the wheat unit area during the monitoring period.

[0009] Further, the method for obtaining the freeze injury degree area includes: Taking the absolute value of the difference between the health deterioration change rates of every two wheat unit areas as the distance metric value between every two wheat unit areas; using the distance metric values between every two wheat unit areas, performing K-Means clustering on all wheat unit areas in the wheat freeze injury area to be analyzed, and obtaining each freeze injury degree area.

[0010] Further, the method for obtaining the obviousness of freeze injury includes: Taking the mean value of the health deterioration change rates of all wheat unit areas in the freeze injury degree area as the area deterioration change rate of the freeze injury degree area; taking the freeze injury degree area corresponding to the largest area deterioration change rate as the first area; taking the freeze injury degree area corresponding to the smallest area deterioration change rate as the second area; Calculating the Euclidean distance between the center point of the first area and the center point of the second area, calculating the absolute value of the difference between the area deterioration change rates corresponding to the first area and the second area, calculating the product of the Euclidean distance and the absolute value of the difference and performing normalization processing to obtain the obviousness of the wheat freeze injury area to be analyzed during the monitoring period.

[0011] Further, the method for obtaining the severity of freeze injury includes: Taking the monitoring periods except the first monitoring period as the control periods; calculating the difference between the obviousness of the control periods and the first monitoring period and performing normalization processing to obtain the local disease increase degree of the control periods; calculating the cumulative sum of the disease increase degrees of all control periods to obtain the overall disease increase degree; Calculating the product of the obviousness corresponding to the current period and the overall disease increase degree and performing normalization processing to obtain the severity of freeze injury.

[0012] Further, the method for classifying the freeze injury risk types of the wheat freeze injury area to be analyzed includes: Marking the freeze injury risk type of the wheat freeze injury area corresponding to the freeze injury severity not greater than the preset first classification parameter as a low-risk freeze injury area; Marking the freeze injury risk type of the wheat freeze injury area corresponding to the freeze injury severity greater than the preset first classification parameter and not greater than the preset second classification parameter as a medium-risk freeze injury area; marking the freeze injury risk type of the wheat freeze injury area corresponding to the freeze injury severity greater than the preset second classification parameter as a high-risk freeze injury area.

[0013] The present invention provides a wheat freeze injury monitoring system for wheat cultivation, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the wheat freeze injury monitoring method for wheat cultivation are implemented.

[0014] The present invention has the following beneficial effects: In order to analyze the specific manifestation of the freezing injury characteristics of wheat, combined with the reduction of the chlorophyll content index and the leaf area index, the health deterioration metric of the wheat unit area at the moment to be analyzed is obtained, and the health deterioration metric evaluates the health deterioration of the wheat unit area at the sampling moment; in order to analyze the real-time freezing injury situation, according to the freezing injury deterioration index of each wheat unit area at the current moment, the wheat freezing injury area to be analyzed is divided from the monitoring area. The wheat freezing injury area to be analyzed reflects the area with freezing injury in the real-time monitoring area. The obvious degree of freezing injury of the wheat freezing injury area to be analyzed during the monitoring period is used to reflect the obvious degree of the manifestation of the freezing injury characteristics of the wheat freezing injury area to be analyzed. Considering that the obvious degree of freezing injury in the current period can reflect the latest condition of the wheat being frozen, the change of the obvious degree of freezing injury of each monitoring period of the wheat freezing injury area to be analyzed over time can reflect the development trend of the freezing injury. Combining the change of the obvious degree of freezing injury of each monitoring period of the wheat freezing injury area to be analyzed over time and the obvious degree of freezing injury in the current period, the severity of the freezing injury of the wheat freezing injury area to be analyzed is obtained. The severity of the freezing injury can more accurately reflect the serious situation of the wheat being frozen, and further more accurately reflect and determine the type of freezing injury risk of the wheat freezing injury area to be analyzed. Description of the Drawings

[0015] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0016] Figure 1 It is a flowchart of a wheat freezing injury monitoring method for wheat cultivation provided by an embodiment of the present invention; Figure 2 It is a flowchart of a method for obtaining the obvious degree of freezing injury provided by an embodiment of the present invention. Detailed Embodiments

[0017] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following, in combination with the drawings and preferred embodiments, details the specific embodiments, structures, features and effects of a wheat freezing injury monitoring method and system for wheat cultivation proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field to which this invention belongs.

[0019] The following specifically describes the specific solutions of a wheat freeze injury monitoring method and system provided by the present invention in conjunction with the accompanying drawings.

[0020] The embodiments of the present invention provide a wheat freeze injury monitoring method and system for wheat cultivation. Please refer to Figure 1 , which shows a flowchart of a wheat freeze injury monitoring method provided by an embodiment of the present invention. The method includes the following steps: Step S1: Obtain a set of vegetation index data for each wheat unit area in the monitoring area; the set of vegetation index data includes chlorophyll content indexes, leaf area indexes, and freeze injury deterioration indexes at each sampling moment during each monitoring period.

[0021] Using the monitoring system, obtain a set of vegetation index data for each wheat unit area in the monitoring area. The specific obtaining process includes: using a remote sensing imager to collect images of the same monitoring area at a preset frequency, and obtaining remote sensing images of the monitoring area at each sampling moment.

[0022] In order to monitor the real-time freeze injury, use remote sensing image processing software (such as ENVI, ERDAS Imagine, etc.) to classify the remote sensing image at the current moment, and mark the wheat pixel points from the remote sensing image. Use empirical values to equally divide the remote sensing image, and use all the wheat pixel points in each divided area corresponding to the monitoring area as the wheat unit area. In other embodiments of the present invention, the inspector can also divide the monitoring area into several wheat unit areas according to factors such as the specific distribution of wheat planting, topography, and farmland management.

[0023] In order to detect wheat freeze injury, it is necessary to determine the chlorophyll content index, leaf area index, and freeze injury deterioration index of each wheat unit area at each sampling moment. The specific obtaining process includes: Since RENDVI (Red Edge Normalized Difference Vegetation Index) can monitor the chlorophyll content of wheat and reflect the health status of wheat, RENDVI is used as the chlorophyll content index. Since LAI (Leaf Area Index) can reflect the ratio of the total area of plant leaves to the surface area per unit ground surface area, LAI is used as the leaf area index. Since ΔNDVI (Delta Normalized Difference Vegetation Index) can monitor the dynamic changes of wheat frost damage and reflect the impact of frost damage on wheat growth, ΔNDVI is used as the frost damage deterioration index. Among them, NDVI (Normalized Difference Vegetation Index) is a commonly used vegetation index for evaluating vegetation coverage and health status. The ΔNDVI at the sampling moment is the NDVI at the sampling moment minus the NDVI at the previous sampling moment in the time series. It should be noted that determining NDVI, LAI, and RENDVI based on remote sensing images is prior art well-known to those skilled in the art and will not be elaborated here. Further using the remote sensing images at each sampling moment, the chlorophyll content index, leaf area index, and frost damage deterioration index of each wheat unit area in the monitoring area at each sampling moment are determined, that is, the chlorophyll content index, leaf area index, and frost damage deterioration index at each sampling moment in each monitoring period in the reference time interval are obtained.

[0024] It should be noted that in an embodiment of the present invention, sampling is performed at a preset frequency, and each sampling is regarded as a sampling moment, and the preset frequency is once every 10 minutes. It should be noted that for the convenience of calculation, all the index data involved in the operation in the embodiment of the present invention have undergone data preprocessing, thereby eliminating the influence of dimensions. The specific means of eliminating the influence of dimensions are technical means well-known to those skilled in the art and will not be limited here. In the present invention, the reference time interval is 48 hours, the last sampling moment of the reference time interval is the current moment, the monitoring period is from the start to the end of 1 hour, and the current period is the monitoring period including the current moment. The implementer can set it according to the implementation scenario.

[0025] Step S2: According to the reduction of the chlorophyll content index and leaf area index of the wheat unit area at the sampling moment, obtain the health deterioration measure of the wheat unit area at the sampling moment; according to the frost damage deterioration index of each wheat unit area at the current moment, divide the wheat frost damage area to be analyzed from the monitoring area; according to the health deterioration measure of each wheat unit area in the wheat frost damage area to be analyzed during the monitoring period, obtain the obvious degree of frost damage in the wheat frost damage area to be analyzed during the monitoring period.

[0026] To analyze the specific manifestation of the freezing injury characteristics of wheat, combined with the reduction of chlorophyll content index and leaf area index, the health deterioration measure of the wheat unit area at the moment to be analyzed is obtained, and the health deterioration measure evaluates the health deterioration of the wheat unit area at the sampling moment; to analyze the real-time freezing injury situation, according to the freezing injury deterioration index of each wheat unit area at the current moment, the wheat freezing injury area to be analyzed is divided from the monitoring area. The wheat freezing injury area to be analyzed reflects the area with freezing injury in the real-time monitoring area. The obvious degree of freezing injury of the wheat freezing injury area to be analyzed during the monitoring period is used to reflect the obvious degree of the manifestation of the freezing injury characteristics of the wheat freezing injury area to be analyzed.

[0027] Considering that under freezing injury conditions, the synthesis of chlorophyll in wheat is inhibited, resulting in a decrease in chlorophyll content; at the same time, freezing injury also inhibits cell division and leaf expansion, thereby affecting the growth of leaf area. The chlorophyll content index reflects the content of chlorophyll in wheat leaves and is an important index for evaluating the photosynthetic capacity and growth status of wheat; the leaf area index reflects the degree of leaf expansion and coverage area of wheat and is an important index for evaluating the growth rate and biomass of wheat. By analyzing the reduction of the chlorophyll content index and leaf area index of the wheat unit area at the sampling moment, the health deterioration of the wheat unit area at the sampling moment is evaluated. Preferably, in an embodiment of the present invention, the method for obtaining the health deterioration measure includes: Taking any sampling moment as the moment to be analyzed, and taking the previous sampling moment of the moment to be analyzed as the reference moment; Calculating the mean values of the chlorophyll content index and leaf area index of the wheat unit area at the sampling moment to obtain the health measure of the wheat unit area at the sampling moment; Calculating the difference between the corresponding health measures of the wheat unit area at the reference moment and the moment to be analyzed. If the difference is not less than zero, normalizing the difference to obtain the health deterioration measure of the wheat unit area at the moment to be analyzed; if the difference is less than zero, setting the health deterioration measure of the wheat unit area at the moment to be analyzed to 0. In the present invention, the normalization process can adopt linear normalization, etc., which is not limited herein.

[0028] For the above steps, first, any sampling moment is taken as the moment to be analyzed, and the previous sampling moment of the period to be analyzed is taken as the reference moment. The purpose of this is to compare the health status of wheat at different moments. For any sampling moment, the mean of the chlorophyll content index and the leaf area index of the wheat unit area is calculated to obtain the health metric of the wheat unit area at the sampling moment. These two indicators can intuitively reflect the photosynthesis capacity and growth status of wheat. Next, the difference between the health metrics corresponding to the reference moment and the moment to be analyzed of the wheat unit area is calculated. If the difference is not less than zero, that is, the health status has not improved or has deteriorated, then the difference is normalized to obtain the health deterioration metric. The normalization process is to ensure that the metric is comparable between different wheat unit areas and different sampling moments. If the difference is less than zero, that is, the health status has improved, then the health deterioration metric is set to 0, because the health status of wheat is developing in a good direction at this time, and there is no deterioration.

[0029] In order to identify the areas suffering from frost damage in the real-time monitoring area, considering that the areas suffering from early frost damage to wheat are usually located in low-lying areas with more water accumulation and lower temperature, which makes the frost damage often present in block form, preferably, in one embodiment of the present invention, the method for obtaining the frost damage area of ​​wheat to be analyzed includes: At the current moment, the wheat unit area whose freezing damage deterioration index is greater than the preset deterioration threshold is marked as a freezing damage unit area; The Euclidean distance between every two frost damage unit areas in the spatial dimension is used as the distance measure of every two frost damage unit areas; based on the distance measure of every two frost damage unit areas, K-Means clustering is performed on all frost damage unit areas in the monitoring area, and each clustering cluster is used as each wheat frost damage area to be analyzed. It should be noted that Euclidean distance and K-Means clustering are prior arts well known to those skilled in the art and will not be elaborated here. In one embodiment of the present invention, the preset deterioration threshold is 0, and the implementer can set it according to the implementation scenario.

[0030] For the above steps, wheat unit areas with freeze damage deterioration indicators greater than the preset deterioration threshold are marked as freeze damage unit areas. This step is to preliminarily screen out wheat areas that may be affected by freeze damage. For each of the preliminarily screened freeze damage unit areas, calculate the Euclidean distance between them pairwise. The Euclidean distance is a commonly used distance metric that can reflect the relative positional relationship between two points in the spatial dimension. Here, the Euclidean distance is used to measure the spatial proximity between different freeze damage unit areas. According to the calculated distance metric, perform K-Means clustering analysis on all freeze damage unit areas in the monitoring area. K-Means clustering is an unsupervised learning algorithm that can divide a data set into K clustering clusters, making the data points within the same clustering cluster as similar as possible, while the data points between different clustering clusters are as different as possible. Here, K-Means clustering is used to divide freeze damage unit areas that are spatially close into the same clustering cluster, and each clustering cluster is used as a wheat freeze damage area to be analyzed, and the wheat freeze damage area reflects the area where freeze damage actually exists in the monitoring area.

[0031] To analyze the obviousness of the freeze damage characteristics of the wheat freeze damage area to be analyzed during the monitoring period, please refer to Figure 2 , which shows a flowchart of a method for obtaining the obviousness of freeze damage in an embodiment of the present invention. Preferably, in an embodiment of the present invention, the method for obtaining the obviousness of freeze damage includes: Step S201: For any monitoring period, obtain the health deterioration change rate of the wheat unit area during the monitoring period according to the health deterioration metrics corresponding to all sampling moments of the wheat unit area during the monitoring period.

[0032] By analyzing the health deterioration metrics of the wheat unit area during the monitoring period, obtain its health deterioration change rate, which reflects the deterioration speed of the wheat health condition.

[0033] Preferably, in an embodiment of the present invention, the method for obtaining the health deterioration change rate includes: Based on a two-dimensional coordinate system, that is, the horizontal axis of the two-dimensional coordinate is the sampling moment, and the vertical axis is the value of the health deterioration metric. Take the health deterioration metric corresponding to each sampling moment as a data point, and count the data points of all sampling moments of the wheat unit area during the monitoring period as fitting data points; use the least squares method to perform linear fitting on all fitting data points to obtain a fitting line; take the slope of the fitting line as the health deterioration change rate of the wheat unit area during the monitoring period. It should be noted that the least squares method is a well-known prior art to those skilled in the art and will not be elaborated here.

[0034] Step S202: In the wheat freeze damage area to be analyzed, cluster all wheat unit areas in the wheat freeze damage area to be analyzed according to the absolute value of the difference between the health deterioration change rates of every two wheat unit areas, and obtain each freeze damage degree area.

[0035] According to the differences in the deterioration change rates of the health of wheat unit areas, the wheat unit areas in the wheat frost damage area to be analyzed are divided into frost damage degree areas with similar frost damage characteristics.

[0036] Preferably, in an embodiment of the present invention, the method for obtaining the frost damage degree area includes: Taking the absolute value of the difference in the deterioration change rates of the health of every two wheat unit areas as the distance measurement value between every two wheat unit areas; using the distance measurement values between every two wheat unit areas, performing K-Means clustering on all wheat unit areas in the wheat frost damage area to be analyzed, and obtaining each frost damage degree area. It should be noted that K-Means clustering is a well-known prior art to those skilled in the art and will not be elaborated here.

[0037] Regarding the above steps, considering that when wheat suffers from frost damage, it will cause the health of wheat to deteriorate, and the deterioration change rate of health can indirectly reflect the frost damage characteristics. Through cluster analysis, each cluster is obtained, and each cluster represents each frost damage degree area, and the frost damage degree area reflects the wheat unit areas with similar frost damage characteristics.

[0038] Step S203: According to the spatial distribution of the frost damage degree areas and the situation of the deterioration change rate of health in the wheat frost damage area to be analyzed, obtain the obvious degree of frost damage in the wheat frost damage area to be analyzed during the monitoring period.

[0039] Analyze the obvious degree of frost damage characteristics in the wheat frost damage area to be analyzed during the monitoring period according to the spatial distribution of the frost damage degree areas and the situation of the deterioration change rate of health in the wheat frost damage area to be analyzed.

[0040] Preferably, in an embodiment of the present invention, the method for obtaining the obvious degree of frost damage includes: Taking the average value of the deterioration change rates of the health of all wheat unit areas in the frost damage degree area as the area deterioration change rate of the frost damage degree area; taking the frost damage degree area corresponding to the largest area deterioration change rate as the first area; taking the frost damage degree area corresponding to the smallest area deterioration change rate as the second area; Calculating the Euclidean distance between the center points of the first area and the second area, calculating the absolute value of the difference between the area deterioration change rates corresponding to the first area and the second area, calculating the product of the Euclidean distance and the absolute value of the difference and performing normalization processing to obtain the obvious degree of frost damage in the wheat frost damage area to be analyzed during the monitoring period.

[0041] For the above steps, considering the influence of the freeze-damage air flow, the degree of freeze-damage gradually weakens from the starting position (where the degree of freeze-damage is relatively large) to the end position (where the degree of freeze-damage is relatively small), showing a stepped change characteristic. In the area where the similarity gap of the change in the degree of freeze-damage is larger, the degree of wheat freeze-damage during the monitoring period has a stepped change characteristic. The mean value of the health deterioration change rate of all wheat unit areas in each freeze-damage degree area is used as the area deterioration change rate of this area. The area deterioration change rate reflects the overall deterioration speed of the wheat health status in this freeze-damage degree area, and indirectly reflects the freeze-damage characteristics. The first area represents the area with the most obvious freeze-damage characteristics, and the second area represents the area with the least obvious freeze-damage characteristics. Calculate the Euclidean distance between the center point of the first area and the center point of the second area, calculate the absolute value of the difference between the corresponding area deterioration change rates of the first area and the second area, calculate the product of the Euclidean distance and the absolute value of the difference and perform normalization to obtain the obviousness degree of the freeze-damage of the wheat freeze-damage area to be analyzed during the monitoring period. If the difference is large and the Euclidean distance is far, it is considered that the possibility of this area being affected by the air flow is large and the obviousness degree of the freeze-damage is high.

[0042] Step S3: Obtain the severity of the freeze-damage of the wheat freeze-damage area to be analyzed according to the temporal change of the obviousness degree of the freeze-damage of the wheat freeze-damage area to be analyzed in each monitoring period and the obviousness degree of the freeze-damage in the current period; divide the wheat freeze-damage area to be analyzed into freeze-damage risk types according to the severity of the freeze-damage.

[0043] Considering that the obviousness degree of the freeze-damage in the current period can reflect the latest status of the wheat being frozen, and the temporal change of the obviousness degree of the freeze-damage of the wheat freeze-damage area to be analyzed in each monitoring period can reflect the development trend of the freeze-damage, combine the temporal change of the obviousness degree of the freeze-damage of the wheat freeze-damage area to be analyzed in each monitoring period and the obviousness degree of the freeze-damage in the current period to obtain the severity of the freeze-damage of the wheat freeze-damage area to be analyzed. The severity of the freeze-damage can more accurately reflect the serious situation of the wheat being frozen, and thus more accurately reflect and determine the freeze-damage risk type of the wheat freeze-damage area to be analyzed.

[0044] In order to comprehensively reflect the degree of the wheat being affected by the freeze-damage, preferably, in an embodiment of the present invention, the method for obtaining the severity of the freeze-damage includes: Take the monitoring periods except the first monitoring period as the control periods; calculate the difference between the obviousness degree of the freeze-damage in the control periods and that in the first monitoring period and perform normalization to obtain the local disease increase degree of the control periods; calculate the cumulative sum of the disease increase degrees of all control periods to obtain the overall disease increase degree; Calculate the product of the frost damage obviousness corresponding to the current time period and the overall disease increase degree, and perform normalization processing to obtain the frost damage severity. In the present invention, the current time period refers to the monitoring time period where the current moment is located. It should be noted that the normalization method adopted is: use the norm normalization function for normalization, and limit the numerical range between 0 and 1. Among them, normalization is a technical means well-known to those skilled in the art, and the choice of the normalization function can be linear normalization or standard normalization, etc. The specific normalization method is not limited here. As an example, the expression of the frost damage severity is: ; In the formula, represents the frost damage severity, represents the frost damage obviousness corresponding to the current time period; represents the overall disease increase degree; is the normalization function.

[0045] For the above steps, the monitoring time periods except the first monitoring time period are used as the control time periods. This is because the data of the first monitoring time period is usually used to establish the baseline or initial state, while the data of the subsequent time periods is used to observe the development of the frost damage. For each control time period, calculate the difference between its frost damage obviousness and that of the first monitoring time period. This difference reflects the increase in the degree of wheat frost damage during this control time period. Perform normalization processing on the calculated difference to obtain the local disease increase degree of the control time period. The normalization processing is to eliminate the numerical fluctuations caused by factors such as measurement conditions and environmental differences between different monitoring time periods, so that the data of different time periods is comparable. Accumulate the local disease increase degrees of all control time periods to obtain the overall disease increase degree. The overall disease increase degree comprehensively reflects the overall increase in the degree of wheat frost damage during all monitoring time periods. Calculate the product of the frost damage obviousness corresponding to the current time period and the overall disease increase degree, and perform normalization processing to obtain the frost damage severity. The frost damage severity takes into account both the frost damage situation of the current time period and combines historical monitoring data to more comprehensively reflect the degree of wheat frost damage.

[0046] In order to more precisely manage and respond to the wheat frost damage area, use the frost damage severity to divide the frost damage risk types. Preferably, in an embodiment of the present invention, the method for dividing the frost damage risk types of the wheat frost damage area to be analyzed includes: Mark the frost damage risk type of the wheat frost damage area corresponding to the frost damage severity not greater than the preset first division parameter as a low-risk frost damage area; Mark the frost damage risk type of the wheat frost damage area where the frost damage severity is greater than the preset first division parameter and not greater than the preset second division parameter as the medium-risk frost damage area; mark the frost damage risk type of the wheat frost damage area where the frost damage severity is greater than the preset second division parameter as the high-risk frost damage area. In an embodiment of the present invention, the preset first division parameter is 0.3, and the preset second division parameter is 0.6, which can be set by the implementer according to the implementation scenario.

[0047] Regarding the above steps, when the frost damage severity of the wheat frost damage area is lower than or equal to the preset first division parameter, it is considered that the frost damage risk in this area is relatively low. This means that in these areas, the possibility of wheat being damaged by frost is small, so the monitoring and management input for this area can be relatively reduced. When the frost damage severity of the wheat frost damage area is between the preset first division parameter and the second division parameter, it is classified as a medium-risk frost damage area. The possibility of wheat being damaged by frost in these areas is moderate, so certain attention and monitoring are required to take appropriate countermeasures when necessary. When the frost damage severity of the wheat frost damage area is higher than the preset second division parameter, this area is regarded as a high-risk frost damage area. In these areas, the possibility of wheat being damaged by frost is very high, so high attention and close monitoring are needed. At the same time, corresponding anti-frost measures should be formulated and implemented to minimize the loss of wheat.

[0048] Specifically, different management measures are adopted for different risk areas. For example, for low-risk frost damage areas, the care technician needs to pay timely attention to the weather forecast and take preventive measures in advance in case of cold snaps (such as covering with straw or plastic film). For medium-risk frost damage areas, after the greening stage, the care technician needs to combine foliar spraying of phosphorus and potassium fertilizers to enhance resistance and photosynthesis. For high-risk frost damage areas, the care technician needs to timely cover the wheat roots with soil to enhance the heat preservation performance of the soil and protect the roots from frost damage. Spray anti-freezing preparations (such as plant anti-freezing agents or regulators) to enhance the cold resistance of wheat cells. By this method, accurate division and effective management of the wheat frost damage area can be achieved, corresponding measures are taken for different risk areas, thereby improving the frost resistance of wheat and reducing the impact of frost damage on wheat yield. This method not only helps to protect the healthy growth of wheat but also improves agricultural production efficiency and economic benefits.

[0049] A wheat frost damage monitoring system for wheat cultivation includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the above-mentioned wheat frost damage monitoring method for wheat cultivation.

[0050] In summary, the embodiments of the present invention provide a method and system for monitoring wheat frost damage in wheat cultivation. First, according to the frost damage deterioration index of each wheat unit area at the current moment, the wheat frost damage area to be analyzed is divided from the monitoring area; according to the health deterioration measure of each wheat unit area in the wheat frost damage area to be analyzed during the monitoring period, the obvious degree of frost damage in the wheat frost damage area to be analyzed during the monitoring period is obtained; according to the temporal change of the obvious degree of frost damage in the wheat frost damage area to be analyzed in each monitoring period and the obvious degree of frost damage in the current period, the severity of frost damage in the wheat frost damage area to be analyzed is obtained; according to the severity of frost damage, the frost damage risk type of the wheat frost damage area to be analyzed is divided. In the present invention, by fully considering the specific manifestation of the frost damage characteristics of wheat and the change over time, the accuracy of monitoring frost damage risk is improved.

[0051] It should be noted that the above sequence of the embodiments of the present invention is only for description and does not represent the superiority or inferiority of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0052] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between each embodiment can be referred to each other. Each embodiment focuses on the differences from other embodiments.

Claims

1. A method for monitoring wheat frost damage in wheat cultivation, characterized in that: The method comprises: Obtaining a vegetation index data set for each wheat unit area in the monitoring area; the vegetation index data set includes a chlorophyll content index, a leaf area index, and a freezing damage aggravation index at each sampling time in each monitoring period; According to the decrease of the chlorophyll content index and the leaf area index of the wheat unit area at the sampling time, the health deterioration measure of the wheat unit area at the sampling time is obtained; according to the frost damage deterioration index of each wheat unit area at the current time, the wheat frost damage area to be analyzed is divided from the monitoring area; according to the health deterioration measure of each wheat unit area in the wheat frost damage area to be analyzed during the monitoring period, the obvious degree of frost damage in the wheat frost damage area to be analyzed during the monitoring period is obtained; According to the time-series changes of the frost damage severity of the wheat frost damage area to be analyzed in each of the monitoring periods and the frost damage severity in the current period, the frost damage severity of the wheat frost damage area to be analyzed is obtained; according to the frost damage severity, the frost damage risk type of the wheat frost damage area to be analyzed is divided.

2. A wheat frost damage monitoring method for wheat cultivation according to claim 1, characterized in that: The method for obtaining the health deterioration metric includes: Taking any sampling time as the time to be analyzed, and taking the sampling time before the time to be analyzed as the reference time; Calculate the mean of the chlorophyll content index and the leaf area index of the wheat unit area at the sampling time to obtain the health metric of the wheat unit area at the sampling time; Calculate the difference between the health metrics corresponding to the wheat unit area at the reference time and the time to be analyzed. If the difference is not less than zero, normalize the difference to obtain the health deterioration metric of the wheat unit area at the time to be analyzed; if the difference is less than zero, set the health deterioration metric of the wheat unit area at the time to be analyzed to 0.

3. A wheat frost damage monitoring method for wheat cultivation according to claim 1, characterized in that: The method for obtaining the wheat frost damage area to be analyzed comprises: At the current moment, the wheat unit area whose freezing damage deterioration index is greater than a preset deterioration threshold is marked as a freezing damage unit area; The Euclidean distance between every two frost damage unit areas in the spatial dimension is used as the distance measurement between every two frost damage unit areas; based on the distance measurement between every two frost damage unit areas, K-Means clustering is performed on all frost damage unit areas in the monitoring area, and each cluster is used as the wheat frost damage area to be analyzed.

4. A wheat frost damage monitoring method for wheat cultivation according to claim 1, characterized in that: The method for obtaining the degree of freezing damage includes: For any monitoring period, according to the health deterioration metric corresponding to all sampling moments of the wheat unit area in the monitoring period, the health deterioration change rate of the wheat unit area in the monitoring period is obtained; In the wheat frost damage area to be analyzed, according to the absolute value of the difference between the health deterioration change rates of every two wheat unit areas, all wheat unit areas in the wheat frost damage area to be analyzed are clustered to obtain various frost damage degree areas; According to the spatial distribution of frost damage areas in the wheat frost damage area to be analyzed and the rate of change of health deterioration, the degree of frost damage in the wheat frost damage area to be analyzed during the monitoring period is obtained.

5. A wheat frost damage monitoring method for wheat cultivation according to claim 4, characterized in that: The method for obtaining the health deterioration change rate includes: Based on a two-dimensional coordinate system, that is, the horizontal axis of the two-dimensional coordinate is the sampling time, and the vertical axis is the value of the health deterioration metric, each sampling time corresponding to the health deterioration metric is taken as a data point, and the data points of the wheat unit area at all sampling times during the monitoring period are counted as fitting data points; the least squares method is used to perform straight line fitting on all the fitting data points to obtain a fitting straight line; the slope of the fitting straight line is used as the health deterioration change rate of the wheat unit area during the monitoring period.

6. A wheat frost damage monitoring method for wheat cultivation according to claim 4, characterized in that: The method for obtaining the freezing damage degree area includes: The absolute value of the difference between the health deterioration change rates of every two wheat unit areas is used as the distance measurement value of every two wheat unit areas; the distance measurement value of every two wheat unit areas is used to perform K-Means clustering on all wheat unit areas in the wheat frost damage area to be analyzed to obtain various frost damage degree areas.

7. A wheat frost damage monitoring method for wheat cultivation according to claim 4, characterized in that: The method for obtaining the degree of freezing damage includes: The average of the health deterioration change rates of all wheat unit areas in the freezing damage area is used as the regional deterioration change rate of the freezing damage area; the largest regional deterioration change rate corresponds to the freezing damage area as the first area; the smallest regional deterioration change rate corresponds to the freezing damage area as the second area; Calculate the Euclidean distance between the center point of the first area and the center point of the second area, calculate the absolute value of the difference between the deterioration change rates of the first area and the second area corresponding to the area, calculate the product of the Euclidean distance and the absolute value of the difference and normalize them to obtain the degree of frost damage in the wheat frost damage area to be analyzed during the monitoring period.

8. A wheat frost damage monitoring method for wheat cultivation according to claim 1, characterized in that: The method for obtaining the severity of frost damage includes: The monitoring periods other than the first monitoring period are taken as control periods; the difference between the frost damage visibility during the control period and the first monitoring period is calculated and normalized to obtain the local disease increase degree during the control period; the cumulative sum of the disease increase degrees during all control periods is calculated to obtain the overall disease increase degree; The product of the frost damage severity corresponding to the current period and the overall disease increase degree is calculated and normalized to obtain the frost damage severity.

9. A wheat frost damage monitoring method for wheat cultivation according to claim 1, characterized in that: The method for classifying the frost damage risk type of the wheat frost damage area to be analyzed comprises: The frost damage risk type of the wheat frost damage area corresponding to the frost damage severity not greater than the preset first division parameter is marked as a low-risk frost damage area; The frost damage risk type of the wheat frost damage area corresponding to the frost damage severity being greater than the preset first division parameter and not greater than the preset second division parameter is marked as a medium-risk frost damage area; the frost damage risk type of the wheat frost damage area corresponding to the frost damage severity being greater than the preset second division parameter is marked as a high-risk frost damage area.

10. A wheat frost damage monitoring system for wheat cultivation, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of a wheat frost damage monitoring method for wheat cultivation as described in any one of claims 1 to 9 are implemented.

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