Rapeseed planting area identification method, program product, electronic device, and storage medium

Abstract

The application relates to the technical field of remote sensing identification, and particularly provides a rape planting area identification method, a program product, an electronic device and a storage medium. The method comprises the following steps: acquiring multispectral imaging data of a target area; determining a pod stage identification index based on a corresponding relationship between a reflectivity difference parameter and the pod stage identification index; and determining a rape planting area according to a first identification index threshold value and the pod stage identification index of a pod stage period. The reflectivity difference parameter comprises a difference between near-infrared reflectivity and second red edge reflectivity, a difference between the second red edge reflectivity and red light reflectivity, and a difference between green light reflectivity and blue light reflectivity. The method can identify the rape planting area in the target area based on optical image data of the pod stage period, reduces the dependence of rape planting area identification on flowering period image data, thereby alleviating the problem of reduced identification accuracy caused by missing flowering period image data, and improving the identification accuracy of the rape planting area.

Description

Technical Field

[0001] This application relates to the field of remote sensing identification technology, and more specifically, to methods, software products, electronic devices, and storage media for identifying rapeseed planting areas. Background Technology

[0002] Remote sensing, with its advantages of real-time capability, rapid update speed, ease of repeated observation, and wide coverage, has become an important tool for land surface monitoring. The resolution of remote sensing data is continuously improving, developing towards higher temporal, higher spatial, and higher spectral resolutions, laying the foundation for high-precision identification of rapeseed.

[0003] In recent years, remote sensing extraction of rapeseed planting areas has mostly relied on spectral or phenological studies, with flowering period images being crucial for identifying rapeseed planting areas. Rapeseed flowers exhibit a distinct bright yellow color, making them easily distinguishable from other crops, and the flowering period is a key phenological stage for rapeseed remote sensing identification. However, these methods heavily depend on the availability of flowering period data, and because the rapeseed flowering period is short, optical remote sensing images are easily affected by clouds and rain; missing flowering period images can lead to a decrease in identification accuracy. Summary of the Invention

[0004] In view of this, the purpose of this application is to provide a method, program product, electronic device and storage medium for identifying rapeseed planting areas, so as to solve the above-mentioned technical problems.

[0005] In a first aspect, embodiments of this application provide a method for identifying rapeseed planting areas, the method comprising:

[0006] Acquire multispectral imaging data of the target region; wherein, the multispectral imaging data includes: the blue light reflectance of the target region in the blue light band. Green light reflectance in the green light band Red light reflectance in the red light band The second red-edge reflectivity of the second red-edge band and near-infrared reflectance in the near-infrared band ;

[0007] Based on the reflectance difference parameter and the correspondence between the reflectance difference parameter and the pod-stage identification index, the pod-stage identification index of the target area is determined; wherein, the reflectance difference parameter includes: near-infrared reflectance. With the second red edge reflectivity The difference, the second red edge reflectivity With red light reflectance The difference, and green light reflectance With blue light reflectivity The difference;

[0008] The rapeseed planting area in the target area is determined based on the first identification index threshold and the pod identification index during the pod stage period.

[0009] In the above implementation process, the rapeseed planting area identification method acquires multispectral imaging data of the target area; determines the pod-stage identification index of the target area based on the reflectance difference parameter and the correspondence between the reflectance difference parameter and the pod-stage identification index; and determines the rapeseed planting area in the target area according to the first identification index threshold and the pod-stage identification index within the pod-stage period. The reflectance difference parameter includes: near-infrared reflectance. With the second red edge reflectivity The difference, the second red edge reflectivity With red light reflectance The difference, and green light reflectance With blue light reflectivity The difference. Due to near-infrared reflectivity With the second red edge reflectivity The difference between the second red edge reflectance and the second red edge reflectance With red light reflectance The difference can amplify the image characteristics of rapeseed during the pod stage; while green light reflectance With blue light reflectivity The difference in image quality can amplify the image differences between different crops. Therefore, this method can identify rapeseed planting areas in the target region based on optical image data during the pod-stage, reducing the dependence of rapeseed planting area identification on flowering period image data, thereby alleviating the problem of reduced identification accuracy caused by missing flowering period images and improving the identification accuracy of rapeseed planting areas. Monitoring rapeseed planting conditions and rationally arranging the spatial distribution and planting patterns of rapeseed is of great significance for rational agricultural planning, improving land utilization, and ensuring sustainable environmental development.

[0010] Optionally, in this embodiment of the application, the method for determining the pod period includes: determining the pod period of the target area based on radar image data of the target area; wherein the radar image data includes the backscattering coefficient of the target area.

[0011] In the aforementioned implementation process, radar imagery data is unaffected by cloud cover or rain, providing continuous and stable all-weather imagery. Therefore, based on radar imagery data, the pod-growing period of the target area can be accurately determined. Combined with the pod-growing period identification indicators determined by multispectral imaging data within that period, the rapeseed planting area within the target area can be identified even more accurately.

[0012] Optionally, in this embodiment, the backscattering coefficient includes the VH scattering coefficient; determining the time period of the target area based on the radar image data of the target area includes: determining a first time when the backscattering coefficient is at its maximum value based on the radar image data of the target area; determining the normalized difference red-edge index of the target area and a second time when the normalized difference red-edge index is at its maximum value based on the multispectral imaging data; wherein, the normalized difference red-edge index... If the time interval between the first time and the second time is less than a preset interval, the pod period is determined based on the midpoint between the first time and the second time; if the time interval between the first time and the second time is greater than or equal to the preset interval, the pod period is determined based on the first time.

[0013] In the aforementioned implementation process, since the VH scattering coefficient is more sensitive to vegetation canopy density, and the scattering intensity of rapeseed increases significantly during the pod stage, the pod stage period can be identified more accurately based on the VH scattering coefficient. Furthermore, by comprehensively determining the pod stage period using the first time point with the highest backscattering coefficient determined from radar image data and the second time point with the highest normalized difference red-edge index determined from multispectral imaging data, the accuracy of identifying the pod stage period can be further improved, thereby enhancing the accuracy of identifying rapeseed planting areas within the target region.

[0014] Optionally, in this embodiment of the application, the method further includes: calculating a flowering period identification index for the target region based on a flowering period index calculation method and the multispectral imaging data; wherein, the flowering period index calculation method includes: , The flowering period identification index is used to identify the rapeseed planting area in the target area. Based on the second identification index threshold and the flowering period identification index within the flowering period, the rapeseed planting area in the target area is determined.

[0015] In the above implementation process, based on This method of calculating flowering period indicators can amplify the characteristics of rapeseed flowering period images. Even when flowering period images are not missing, it can more accurately identify rapeseed planting areas within a target region based on flowering period identification indicators, thus improving the accuracy of rapeseed planting area identification.

[0016] Optionally, in this embodiment, the method for determining the flowering period includes: determining the flowering period based on the pod-stage period and the interval between the pod-stage period and the flowering period; or, if the maximum value of the flowering period identification indicator is greater than a preset indicator threshold, determining the flowering period based on the time when the value of the flowering period identification indicator is the largest; or, if the maximum value of the flowering period identification indicator is less than or equal to the preset indicator threshold, determining the flowering period based on the pod-stage period and the interval between the pod-stage period and the flowering period.

[0017] In the above implementation process, after determining the pod-stage period, the flowering period can be determined directly based on the interval between the pod-stage period and the flowering period. Alternatively, if the maximum value of the flowering period identification indicator is greater than a preset threshold, the pod-stage period can be determined based on the time when the value of the flowering period identification indicator is the highest.

[0018] Optionally, in this embodiment of the application, the correspondence between the reflectance difference parameter and the pod-stage identification index includes: , The method further includes: when the multispectral imaging data includes both pod-stage optical image data and flowering optical image data during the flowering period, determining the rapeseed planting area in the target area based on the pod-stage identification index and the flowering identification index; and when the multispectral imaging data includes seedling-stage optical image data but does not include pod-stage optical image data and flowering optical image data, determining the rapeseed planting area in the target area based on the pod-stage identification index during the seedling stage.

[0019] Optionally, in this embodiment of the application, determining the rapeseed planting area in the target area based on the first identification index threshold and the pod-stage identification index within the pod-stage period includes: determining the winter crop planting area in the target area based on the normalized vegetation index; wherein, the normalized vegetation index... Based on the first identification index threshold and the pod identification index during the pod stage, the rapeseed planting area in the winter crop planting area is determined.

[0020] In the above implementation process, the winter crop planting area in the target area is first determined based on the normalized vegetation index; then, the rapeseed planting area in the winter crop planting area is accurately determined based on the first identification index threshold and the pod identification index during the pod stage; thus, the accurate identification of the rapeseed planting area is achieved.

[0021] Secondly, embodiments of this application provide a computer program product, including a computer program / instruction, which, when executed by a processor, implements the rapeseed planting area identification method as described in any of the first aspects above.

[0022] Thirdly, embodiments of this application also provide an electronic device; the electronic device includes:

[0023] Memory;

[0024] processor;

[0025] The memory stores a computer program executable by the processor. When the computer program is executed by the processor, it performs the rapeseed planting area identification method according to any one of the first aspects.

[0026] Fourthly, embodiments of this application also provide a computer-readable storage medium storing computer program instructions, which, when executed by a processor, perform the rapeseed planting area identification method as described in any of the first aspects.

[0027] The beneficial effects of this application include at least the following: the rapeseed planting area identification method acquires multispectral imaging data of the target area; determines the pod-stage identification index of the target area based on a reflectance difference parameter and the correspondence between the reflectance difference parameter and the pod-stage identification index; and determines the rapeseed planting area within the target area based on a first identification index threshold and the pod-stage identification index within the pod-stage period. The reflectance difference parameter includes: near-infrared reflectance. With the second red edge reflectivity The difference, the second red edge reflectivity With red light reflectance The difference, and green light reflectance With blue light reflectivity The difference. Due to near-infrared reflectivity With the second red edge reflectivity The difference between the second red edge reflectance and the second red edge reflectance With red light reflectance The difference can amplify the image characteristics of rapeseed during the pod stage; while green light reflectance With blue light reflectivity The difference in image quality can amplify the image differences between different crops. Therefore, this method can identify rapeseed planting areas in the target region based on optical image data during the pod-stage, reducing the dependence of rapeseed planting area identification on flowering period image data, thereby alleviating the problem of reduced identification accuracy caused by missing flowering period images and improving the identification accuracy of rapeseed planting areas. Monitoring rapeseed planting conditions and rationally arranging the spatial distribution and planting patterns of rapeseed is of great significance for rational agricultural planning, improving land utilization, and ensuring sustainable environmental development. Attached Figure Description

[0028] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0029] Figure 1 A flowchart illustrating a method for identifying rapeseed planting areas provided in an embodiment of this application;

[0030] Figure 2 A graph showing the change of pod-stage identification indicators provided in the embodiments of this application;

[0031] Figure 3 A graph showing the variation of the VV backscattering coefficient provided in an embodiment of this application;

[0032] Figure 4 A graph showing the variation of the VH backscattering coefficient provided in an embodiment of this application;

[0033] Figure 5 A graph showing the change in flowering period identification indicators provided in the embodiments of this application;

[0034] Figure 6 The normalized vegetation index variation curve provided in the embodiments of this application;

[0035] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0036] The embodiments of the technical solution of this application will now be described in detail with reference to the accompanying drawings. These embodiments are only used to more clearly illustrate the technical solution of this application and are therefore merely examples, and should not be used to limit the scope of protection of this application.

[0037] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this application.

[0038] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0039] Please see Figure 1 The illustration shows a flowchart of a rapeseed planting area identification method provided in an embodiment of this application. The rapeseed planting area identification method may include the following steps:

[0040] S101. Acquire multispectral imaging data of the target area; wherein, the multispectral imaging data includes: the blue light reflectance of the target area in the blue light band. Green light reflectance in the green light band Red light reflectance in the red light band The second red-edge reflectivity of the second red-edge band and near-infrared reflectance in the near-infrared band ;

[0041] S102. Based on the reflectance difference parameter and the correspondence between the reflectance difference parameter and the pod-stage identification index, determine the pod-stage identification index of the target area; wherein, the reflectance difference parameter includes: near-infrared reflectance. With the second red edge reflectivity The difference, the second red edge reflectivity With red light reflectance The difference, and green light reflectance With blue light reflectivity The difference;

[0042] S103. Determine the rapeseed planting area in the target area based on the first identification index threshold and the pod identification index during the pod period.

[0043] In step S101, the target area can be a winter crop planting area. In this case, the rapeseed planting area within the winter crop planting area can be determined directly based on the pod-stage identification index and the first identification index threshold during the pod-stage period. The target area can also be any surface area. In this case, the normalized vegetation coefficient (NVC) can be calculated first based on the multispectral imaging data of the target area. The process involves first identifying winter crop areas within the target region based on NDVI, and then determining rapeseed planting areas within the target region based on pod-stage identification indicators during the pod-stage period. Multispectral imaging data can be from satellite imagery (e.g., Sentinel-2 satellite imagery). The blue light band refers to a band with a center wavelength of 490 nm and an amplitude of 65 nm. The green light band refers to a band with a center wavelength of 560 nm and an amplitude of 35 nm. The red light band refers to a band with a center wavelength of 665 nm and an amplitude of 30 nm. The second red edge band refers to a band with a center wavelength of 740 nm and an amplitude of 15 nm. The near-infrared band refers to a band with a center wavelength of 842 nm and an amplitude of 115 nm. Blue light reflectance... This refers to the surface reflectivity of the target area in the blue light band and the green light reflectivity. This refers to the surface reflectivity of the target area in the green light band and the reflectivity in the red light band. This refers to the surface reflectivity of the target area in the red light band, the second red edge reflectivity. This refers to the surface reflectivity of the target area in the second red-edge band, near-infrared reflectivity. This refers to the surface reflectivity of the target area in the near-infrared band.

[0044] In step S102, the near-infrared reflectance can be determined based on the reflectance difference parameter. With the second red edge reflectivity The difference, the second red edge reflectivity With red light reflectance The difference, and green light reflectance With blue light reflectivity The difference. Based on near-infrared reflectance. With the second red edge reflectivity The difference, and the second red edge reflectivity With red light reflectance The difference can amplify the image features of rapeseed during the pod stage. Based on green light reflectance... With blue light reflectivity The difference can amplify the image differences between different crops.

[0045] In step S103, please refer to Figure 2 , Figure 2 A graph showing the change of the pod-stage identification index provided in the embodiments of this application. Figure 2 It shows the basis Determine the pod stage identification indicators In this context, the pod-stage identification indicators for rapeseed and other representative winter crops (winter wheat) The graph shows the changes over time, specifically illustrating the changes in pod-stage identification indicators for rapeseed and wheat during the period from October 1, 2022 to July 28, 2023, when rapeseed was in the pod-stage, flowering stage, harvest stage, and other stages. Figure 2 As shown, during the pod-stage period, the pod-stage identification indicators in rapeseed planting areas are significantly different from those in winter wheat planting areas. Therefore, based on the first identification indicator threshold and the pod-stage identification indicators within the pod-stage period, the rapeseed planting area in the target region can be accurately determined. Determine the pod stage identification indicators In this case, the first identification index threshold can be 1.5, 2, 4, or other reasonable values. The first identification index threshold can be appropriately adjusted according to the actual application scenario (e.g., the actual geographical location of the target area), and this application does not impose specific limitations on it. Taking a first identification index threshold of 1.5 as an example, the area in the target area where the pod-stage identification index during the pod-stage period is less than the first identification index threshold can be identified as a rapeseed planting area.

[0046] Therefore, the rapeseed planting area identification method provided in this application can identify rapeseed planting areas in a target region based on optical image data during the pod-stage period. This reduces the dependence of rapeseed planting area identification on flowering period image data, thereby alleviating the problem of reduced identification accuracy caused by missing flowering period images and improving the identification accuracy of rapeseed planting areas. Rapeseed is an important winter oilseed crop and a salt-tolerant crop, playing a vital role in restoring saline-alkali soil, expanding arable land, and strengthening food and oil security. Therefore, monitoring rapeseed planting and rationally arranging the spatial distribution and planting patterns of rapeseed are of great significance for rational agricultural planning, improving land utilization, and ensuring sustainable environmental development.

[0047] It should be noted that, if optical image data during the flowering period is not missing, the rapeseed planting area in the target region can be determined based on existing rapeseed flowering period identification methods. Alternatively, the rapeseed planting area in the target region can be determined jointly based on existing rapeseed flowering period identification methods and the rapeseed planting area identification method for the pod stage provided in this application. Furthermore, the flowering period identification index of the target region can be calculated based on the "flowering period index calculation method and the multispectral imaging data provided in this application; wherein the flowering period index calculation method includes: , The method for identifying rapeseed planting areas in the target area is determined by combining the second identification index threshold and the rapeseed planting area identification index within the flowering period with the rapeseed planting area identification method for the pod stage.

[0048] In some optional embodiments, the method for determining the pod period includes: determining the pod period of the target area based on radar image data of the target area; wherein the radar image data includes the backscattering coefficient of the target area.

[0049] The radar imagery data can be from satellite imagery (e.g., Sentinel-1 satellite imagery). Specifically, the radar imagery data may include the VV backscattering coefficient or VH backscattering coefficient of the target area, etc. Please refer to [reference needed]. Figure 3 , Figure 3 The graph showing the variation of the VV backscattering coefficient provided in the embodiments of this application is shown below. Please refer to... Figure 4 , Figure 4 A graph showing the variation of the VH backscattering coefficient provided in an embodiment of this application. Figure 3 The graph shows the VV backscattering coefficient of rapeseed and other representative winter crops (winter wheat) over time, specifically showing the changes in VV backscattering coefficient of rapeseed and wheat during the pod stage, flowering stage, harvest stage and other stages of rapeseed from October 1, 2022 to July 28, 2023. Figure 4The graph shows the variation of the VH backscattering coefficient over time for rapeseed and other representative winter crops (winter wheat), specifically illustrating the changes in VH backscattering coefficients during the pod-stage, flowering stage, harvest stage, and other stages of rapeseed from October 1, 2022 to July 28, 2023. From the budding stage, rapeseed shows increased water accumulation in stems, leaves, and other organs, leading to a gradual increase in both the VV and VH backscattering coefficients. Local low values ​​appear after entering the flowering stage, as rapeseed flowers block some of the scattered signals from the lower plant body. The VV backscattering coefficient is more sensitive to changes in the vegetation canopy; therefore, the low values ​​of the VV backscattering coefficient are more pronounced. After entering the pod-stage, rapeseed petals wither, leaves degenerate, and water is transferred to the pods, increasing the radar scattering signal to its maximum value (the peak value of the VH backscattering coefficient can reach -10 dB, and the peak value of the VV backscattering coefficient can reach -8 dB). After rapeseed matures, canopy dehydration is significant, with a rapid decrease in water content and a sharp drop in backscattering intensity. In contrast, the backscattering intensity of winter wheat does not fluctuate strongly during the flowering and pod-forming stages of rapeseed. Therefore, based on the pod-forming characteristics of rapeseed and other winter crops using the VV or VH backscattering coefficients, the pod-forming period in a target area can be determined. Taking the VH backscattering coefficient as an example, the pod-forming period can be determined based on the time when the VH backscattering coefficient is at its maximum. Furthermore, since radar imagery data is unaffected by cloud cover or rain, it provides continuous and stable all-weather imagery data. Therefore, based on radar imagery data, the pod-forming period in a target area can be accurately determined. Combining this with pod-forming identification indicators determined from multispectral imaging data within the pod-forming period, the rapeseed planting area within the target area can be identified even more accurately.

[0050] In some optional embodiments, the backscattering coefficient includes the VH scattering coefficient; determining the time period of the target area based on the radar image data of the target area includes: determining a first time when the value of the backscattering coefficient is the largest based on the radar image data of the target area; determining the normalized difference red-edge index of the target area and a second time when the value of the normalized difference red-edge index is the largest based on the multispectral imaging data; wherein, the normalized difference red-edge index... If the time interval between the first time and the second time is less than a preset interval, the pod period is determined based on the midpoint between the first time and the second time; if the time interval between the first time and the second time is greater than or equal to the preset interval, the pod period is determined based on the first time.

[0051] Taking radar imagery data, including Sentinel-1 satellite imagery data, as an example, Sentinel-1 satellite imagery data is affected by noise. Besides localized low values ​​caused by the rapeseed flowering period, noise also causes fluctuations in scattering signals in some areas, increasing the difficulty of identifying localized low values. Since the VH scattering coefficient is more sensitive to increases in vegetation canopy density, the scattering intensity of rapeseed increases significantly during the pod stage. Therefore, compared to the VV backscattering coefficient, the VH scattering coefficient can more accurately identify the pod stage period. The preset interval can be 8 days, 10 days, or 12 days, etc. By combining the first time point (where the time interval between the first and second times is less than the preset interval) with the first time point where the backscattering coefficient value determined by radar imagery data is the largest, and the second time point where the normalized difference red-edge index determined by multispectral imaging data is the largest, the pod stage period can be determined more accurately. This further improves the accuracy of identifying the pod stage period, and consequently, the accuracy of identifying rapeseed planting areas within the target region.

[0052] In some optional embodiments, the method further includes: calculating a flowering period identification index for the target region based on a flowering period index calculation method and the multispectral imaging data; wherein the flowering period index calculation method includes: , The flowering period identification index is used to identify the rapeseed planting area in the target area. Based on the second identification index threshold and the flowering period identification index within the flowering period, the rapeseed planting area in the target area is determined.

[0053] Please refer to Figure 5 , Figure 5 A graph showing the change in flowering period identification indicators provided in the embodiments of this application. Figure 5 This shows the flowering time identification indicators for rapeseed and other representative winter crops (winter wheat). The graph shows the changes over time, specifically illustrating the changes in flowering identification indicators for rapeseed and wheat during the period from October 1, 2022 to July 28, 2023, when rapeseed was in the pod stage, flowering stage, harvest stage, and other stages. Figure 5 As shown, during the flowering period, the flowering period identification indicators in rapeseed planting areas are significantly different from those in winter wheat planting areas. Therefore, based on the second identification indicator threshold and the flowering period identification indicators within the flowering period, the rapeseed planting area in the target region can be accurately determined. The second identification indicator threshold can be 0.1, 0.2, 0.6, or other reasonable values. The second identification indicator threshold can be appropriately adjusted according to the actual application scenario, and this application does not impose specific limitations on it. Based on This method of calculating flowering period indicators can amplify the characteristics of rapeseed flowering period images. Even when flowering period images are not missing, it can more accurately identify rapeseed planting areas within a target region based on flowering period identification indicators, thus improving the accuracy of rapeseed planting area identification.

[0054] In some optional embodiments, the method for determining the flowering period includes: determining the flowering period based on the pod-stage period and the interval between the pod-stage period and the flowering period; or, if the maximum value of the flowering period identification indicator is greater than a preset indicator threshold, determining the flowering period based on the time when the value of the flowering period identification indicator is the largest; or, if the maximum value of the flowering period identification indicator is less than or equal to the preset indicator threshold, determining the flowering period based on the pod-stage period and the interval between the pod-stage period and the flowering period.

[0055] The interval between the pod-stage and flowering period can be 25 days, 30 days, or 35 days, etc., and the specific interval can be adjusted according to the actual application scenario (e.g., the actual geographical location of the target area). The flowering period can be determined directly based on the interval between the pod-stage and flowering periods after the pod-stage period is determined. Alternatively, if the maximum value of the flowering period identification indicator is greater than a preset threshold, the pod-stage period can be determined based on the time when the flowering period identification indicator value is at its maximum; and if the maximum value of the flowering period identification indicator is less than or equal to the preset threshold, the flowering period can be determined based on the pod-stage period and the interval between the pod-stage and flowering periods.

[0056] In some optional embodiments, the correspondence between the reflectance difference parameter and the pod identification index includes: , The method further includes: when the multispectral imaging data includes both pod-stage optical image data and flowering optical image data during the flowering period, determining the rapeseed planting area in the target area based on the pod-stage identification index and the flowering identification index; and when the multispectral imaging data includes seedling-stage optical image data but does not include pod-stage optical image data and flowering optical image data, determining the rapeseed planting area in the target area based on the pod-stage identification index during the seedling stage.

[0057] Specifically, when the multispectral imaging data includes pod-stage optical image data but excludes flowering-stage optical image data: the rapeseed planting area in the target region is determined based on a first identification index threshold and a pod-stage identification index within the pod-stage period. When the multispectral imaging data includes flowering-stage optical image data but excludes pod-stage optical image data: the rapeseed planting area in the target region is determined based on a second identification index threshold and a flowering-stage identification index. When the multispectral imaging data includes both pod-stage and flowering-stage optical image data: the rapeseed planting area in the target region is determined comprehensively based on both the pod-stage and flowering-stage identification indices. Specifically, the rapeseed planting area can be defined as the region in the target region where the maximum value of the VH backscattering coefficient is greater than the scattering coefficient threshold (which can be -11dB, -12dB, -15dB, or other reasonable values), the flowering-stage identification index is greater than the second identification index threshold, and the pod-stage identification index is less than the first identification index threshold. When the multispectral imaging data includes seedling stage optical image data but excludes pod stage and flowering stage optical image data: the rapeseed planting area in the target region is determined based on the pod stage identification index during the seedling stage; specifically, the area in the target region where the maximum value of the VH backscattering coefficient is greater than the scattering coefficient threshold (which can be -11dB, -12dB, -15dB or other reasonable values) and the pod stage identification index during the seedling stage is greater than the third identification index threshold (which can be 6, 7, 8 or other reasonable values) is identified as the rapeseed planting area.

[0058] Please refer to Figure 6 , Figure 6 This is a curve illustrating the variation of the Normalized Difference Vegetation Index (NDVI) provided in an embodiment of this application. In some optional embodiments, determining the rapeseed planting area in the target region based on a first identification index threshold and the pod-stage identification index within the pod-stage period includes: determining the winter crop planting area in the target region based on the NDVI; wherein the NDVI... Based on the first identification index threshold and the pod identification index during the pod stage, the rapeseed planting area in the winter crop planting area is determined.

[0059] in, Figure 6 Specifically, the normalized vegetation index (NDI) is shown for regional types such as rapeseed, representative winter crops (winter wheat), rice (a non-winter crop), and forest land. A graph showing how the change has occurred over time. For example... Figure 6As shown, the Normalized Difference Vegetation Index (NDVI) can distinguish winter crop planting areas from other types of areas (non-winter crops, forest land, etc.). First, the NDVI is used to determine the winter crop planting areas within the target region; then, based on the first identification threshold and the pod-stage identification index during the pod-stage period, the rapeseed planting areas within the winter crop planting areas are accurately determined; thus, accurate identification of rapeseed planting areas is achieved.

[0060] This application also provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the rapeseed planting area identification method as described in any of the first aspects.

[0061] Please refer to Figure 7 , Figure 7 This is a schematic diagram of the structure of an electronic device 200 provided in an embodiment of this application. The electronic device 200 includes: a memory 202 and a processor 201; the memory 202 stores a computer program executable by the processor 201, and when the computer program is executed by the processor 201, it executes the rapeseed planting area identification method described in any of the first aspects.

[0062] The memory 202 and the processor 201 can be interconnected and communicate with each other via a communication bus 203 and / or other forms of connection mechanism (not shown). The memory 202 stores a computer program executable by the processor 201, which, when executed by the processor 201, performs the rapeseed planting area identification method described in the first aspect above.

[0063] This application also provides a computer-readable storage medium storing computer program instructions, which, when executed by processor 201, perform the rapeseed planting area identification method described in the first aspect above.

[0064] The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0065] It should be understood that the disclosed apparatus / systems and methods can also be implemented in other ways, as provided in the embodiments of this application. The apparatus embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, or they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0066] In addition, the functional modules in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0067] The above description is only an optional implementation of the embodiments of this application, but the protection scope of the embodiments of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the embodiments of this application should be covered within the protection scope of the embodiments of this application.

Claims

1. A method for identifying rapeseed planting areas, characterized in that, The method includes: Acquire multispectral imaging data of a target area; the target area is a planting area for rapeseed, winter wheat, rice, and woodland; wherein, the multispectral imaging data includes: the blue light reflectance of the target area in the blue light band. Green light reflectance in the green light band Red light reflectance in the red light band The second red-edge reflectivity of the second red-edge band and near-infrared reflectance in the near-infrared band The blue light band refers to the band with a center wavelength of 490 nanometers and an amplitude of 65 nanometers; the green light band refers to the band with a center wavelength of 560 nanometers and an amplitude of 35 nanometers; the red light band refers to the band with a center wavelength of 665 nanometers and an amplitude of 30 nanometers; the second red edge band refers to the band with a center wavelength of 740 nanometers and an amplitude of 15 nanometers; and the near-infrared band refers to the band with a center wavelength of 842 nanometers and an amplitude of 115 nanometers. Based on the reflectance difference parameter and the correspondence between the reflectance difference parameter and the pod-stage identification index, the pod-stage identification index of the target area is determined; wherein, the reflectance difference parameter includes: near-infrared reflectance. With the second red edge reflectivity The difference, the second red edge reflectivity With red light reflectivity The difference, and green light reflectance With blue light reflectivity The difference; The correspondence between the reflectance difference parameter and the pod identification index includes: , This refers to the pod-stage identification index; Based on the normalized vegetation index (NVI), the winter crop planting areas in the target region are determined; wherein, the normalized vegetation index... ; Based on the first identification index threshold and the pod identification index during the pod stage, the rapeseed planting area in the target area is determined, wherein the area in the target area where the pod identification index during the pod stage is less than the first identification index threshold is determined as the rapeseed planting area.

2. The method according to claim 1, characterized in that, in, The method for determining the pod period includes: Based on radar image data of the target area, the time period of the target area is determined; wherein, the radar image data includes the backscattering coefficient of the target area.

3. The method according to claim 2, characterized in that, in, The backscattering coefficient includes the VH scattering coefficient; determining the pod time period of the target area based on the radar image data of the target area includes: Based on the radar image data of the target area, determine the first time when the backscattering coefficient is at its maximum value; Based on the multispectral imaging data, the normalized difference red-edge index of the target region is determined, as well as the second time when the value of the normalized difference red-edge index is the largest; wherein, the normalized difference red-edge index... ; If the time interval between the first time and the second time is less than a preset interval, the pod period is determined based on the midpoint between the first time and the second time. If the time interval between the first time and the second time is greater than or equal to the preset interval, the pod period is determined based on the first time.

4. The method according to any one of claims 1-3, characterized in that, The method further includes: Based on the flowering period index calculation method and the multispectral imaging data, a flowering period identification index for the target region is calculated; wherein, the flowering period index calculation method includes: , This refers to the flowering period identification index; The rapeseed planting area in the target area is determined based on the second identification index threshold and the flowering period identification index within the flowering period.

5. The method according to claim 4, characterized in that, in, The methods for determining the flowering period include: The flowering period is determined based on the pod-stage period and the interval between the pod-stage period and the flowering period; or, If the maximum value of the flowering period identification index is greater than a preset index threshold, the flowering period is determined based on the time when the value of the flowering period identification index is the largest. If the maximum value of the flowering period identification index is less than or equal to the preset index threshold, the flowering period is determined based on the pod period and the interval between the pod period and the flowering period.

6. The method according to claim 4, characterized in that, The method further includes: When the multispectral imaging data includes both pod-stage optical image data and flowering-stage optical image data during the flowering period, the rapeseed planting area in the target region is determined comprehensively based on the pod-stage identification index and the flowering-stage identification index.

7. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the method as described in any one of claims 1-6.

8. An electronic device, characterized in that, The electronic device includes: Memory; processor; The memory stores a computer program executable by the processor, which, when executed by the processor, performs the method described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer program instructions that, when executed by a processor, perform the method described in any one of claims 1-6.

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