A vegetation restoration monitoring method based on image analysis

Abstract

The present application relates to the technical field of vegetation monitoring, and particularly relates to a vegetation recovery monitoring method based on image analysis. The present application selects a photographed image of vegetation recovery in a monitoring area range, processes the photographed image, divides the monitoring area into regions, determines the processed photographed image corresponding to each divided region, determines the vegetation index of the corresponding divided region in turn, determines the vegetation recovery change amount of the corresponding divided region according to the vegetation index, determines whether the vegetation recovery meets the standard based on the vegetation recovery change amount, determines the reason why the vegetation recovery does not meet the standard based on the regional dispersion degree, determines the reason why the vegetation recovery does not meet the standard based on the standard deviation rate, adjusts the corresponding parameters or issues the corresponding notification. The present application effectively realizes timely analysis and intelligent adjustment of the image according to the vegetation recovery condition, and effectively improves the monitoring efficiency of the vegetation recovery.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vegetation monitoring, and in particular to a vegetation restoration monitoring method based on image analysis. BACKGROUND

[0002] Vegetation restoration refers to the process of gradually restoring the function and structure of damaged vegetation ecosystems through natural restoration or artificial intervention. Vegetation restoration monitoring based on image analysis uses remote sensing images, unmanned aerial photography or ground photography images to evaluate the restoration of regional vegetation through image analysis. Vegetation restoration is crucial to the ecological environment and human life, as it can prevent soil erosion and land desertification, regulate the climate, purify the environment, and maintain biodiversity. Vegetation restoration monitoring is essential in determining whether the desired goals have been achieved, quantifying vegetation changes, and providing data support for management decisions. Vegetation restoration monitoring based on image analysis addresses the shortcomings of traditional monitoring methods, such as reliance on manual labor, limited coverage, subjective judgment, and high costs. Therefore, research on vegetation restoration monitoring based on image analysis is of great practical significance in the field of vegetation restoration monitoring.

[0003] Chinese patent publication No. CN117523387A discloses a vegetation coverage monitoring system and method. The vegetation coverage monitoring system includes an image acquisition module, an image processing module, an image recognition module, and an image analysis module. The image acquisition module uses an image sensor mounted on a drone to capture images of a target area and obtain image data. The image processing module stitches the image data to obtain a panoramic image. The image recognition module identifies the vegetation area and non-vegetation area in the panoramic image using a vegetation recognition model and renders the vegetation area in the panoramic image to generate a rendered panoramic image. The image analysis module obtains vegetation coverage information of the target area based on the rendered panoramic image.

[0004] As can be seen, the above-mentioned scheme uses an image acquisition module to obtain image data of a target area, and uses an image processing module, an image recognition module, and an image analysis module to calculate the vegetation coverage of the target area and obtain vegetation coverage information, providing a reliable basis for natural vegetation protection and restoration. However, the above-mentioned scheme cannot analyze and intelligently adjust the image in a timely manner based on the vegetation restoration situation, thereby failing to ensure the monitoring efficiency of vegetation restoration. SUMMARY

[0005] Therefore, the present application provides a vegetation restoration monitoring method based on image analysis to overcome the problem of low monitoring efficiency of vegetation restoration caused by the inability to analyze and intelligently adjust the image in a timely manner based on the vegetation restoration situation in the prior art.

[0006] To achieve the above-mentioned purpose, the present application provides a vegetation restoration monitoring method based on image analysis, comprising:

[0007] selecting a photographed image of vegetation restoration in a monitoring area range;

[0008] processing the photographed image to improve monitoring accuracy;

[0009] dividing the monitoring area into regions and sequentially determining the processed photographed image corresponding to each divided region;

[0010] sequentially determining the vegetation index of the corresponding divided region based on the processed photographed image;

[0011] determining the vegetation restoration change amount of the corresponding divided region according to the vegetation index;

[0012] determining whether the vegetation restoration meets the standard based on the vegetation restoration change amount;

[0013] when determining that the vegetation restoration does not meet the standard, determining the reason why the vegetation restoration does not meet the standard based on the regional dispersion degree;

[0014] adjusting the cloud probability threshold based on the cloud coverage rate or adjusting the image resolution based on the boundary pixel density based on the reason determined by the regional dispersion degree; and increasing the cloud shadow buffer distance based on the solar elevation angle after the cloud probability threshold is increased;

[0015] after the cloud shadow buffer distance or the image resolution adjustment is completed, determining whether the vegetation restoration meets the standard based on the vegetation restoration change amount;

[0016] when determining that the vegetation restoration does not meet the standard, adjusting the aerosol optical depth based on the vegetation restoration change amount;

[0017] after the aerosol optical depth adjustment is completed, determining whether the vegetation restoration meets the standard based on the vegetation restoration change amount;

[0018] when determining that the vegetation restoration does not meet the standard, determining the reason why the vegetation restoration does not meet the standard based on the standard deviation rate; and issuing a corresponding notification according to the determination result of the standard deviation rate.

[0019] Further, the process of determining whether the vegetation restoration meets the standard based on the vegetation restoration change amount comprises,

[0020] when the vegetation restoration change amount is greater than or equal to a preset vegetation restoration change amount, determining that the vegetation restoration of the monitoring area meets the standard, completing the periodic determination of the vegetation restoration, and determining the vegetation restoration of the next period;

[0021] when the vegetation restoration change amount is less than the preset vegetation restoration change amount, determining the reason why the vegetation restoration does not meet the standard based on the regional dispersion degree.

[0022] Further, the process of determining the reason why the vegetation restoration does not meet the standard based on the area dispersion includes,

[0023] When the area dispersion is less than the preset area dispersion, it is determined that the cloud probability threshold of the photographed image does not meet the standard, and the cloud probability threshold is adjusted based on the cloud coverage;

[0024] When the area dispersion is greater than or equal to the preset area dispersion, it is determined that the image resolution of the photographed image does not meet the standard, and the image resolution is adjusted based on the boundary pixel density.

[0025] Further, the process of increasing the cloud probability threshold based on the cloud coverage includes,

[0026] The cloud probability threshold is increased based on the cloud coverage, and the increase amplitude of the cloud probability threshold is proportional to the cloud coverage.

[0027] Further, the process of increasing the cloud shadow buffer distance based on the solar elevation angle after the cloud probability threshold is increased includes,

[0028] The cloud shadow buffer distance is increased based on the solar elevation angle, and the increase amplitude of the cloud shadow buffer distance is inversely proportional to the solar elevation angle.

[0029] Further, the process of increasing the image resolution based on the boundary pixel density includes,

[0030] The image resolution is increased based on the boundary pixel density, and the increase amplitude of the image resolution is inversely proportional to the boundary pixel density.

[0031] Further, the process of determining whether the vegetation restoration meets the standard based on the vegetation restoration change amount after the cloud shadow buffer distance or the image resolution is adjusted includes,

[0032] When the vegetation restoration change amount is greater than or equal to the preset vegetation restoration change amount, it is determined that the vegetation restoration of the monitoring area meets the standard, the periodic determination of the vegetation restoration is completed, and the next period vegetation restoration is determined;

[0033] When the vegetation restoration change amount is less than the preset vegetation restoration change amount, the aerosol optical thickness is adjusted based on the vegetation restoration change amount.

[0034] Further, the process of decreasing the aerosol optical thickness based on the vegetation restoration change amount difference includes,

[0035] The aerosol optical depth is reduced based on the vegetation restoration change difference, and the reduction range of the aerosol optical depth is proportional to the vegetation restoration change difference.

[0036] Further, the process of determining whether the vegetation restoration meets the standard based on the vegetation restoration change after the aerosol optical depth adjustment is completed includes,

[0037] When the vegetation restoration change is greater than or equal to the preset vegetation restoration change, it is determined that the vegetation restoration of the monitoring area meets the standard, the periodic determination of the vegetation restoration is completed, and the next period vegetation restoration is determined;

[0038] When the vegetation restoration change is less than the preset vegetation restoration change, the reason why the vegetation restoration does not meet the standard is determined based on the standard deviation rate.

[0039] Further, the process of determining the reason why the vegetation restoration does not meet the standard based on the standard deviation rate includes,

[0040] When the standard deviation rate is less than the preset standard deviation rate, a notification that the vegetation restoration of the monitoring area does not meet the standard is sent out;

[0041] When the standard deviation rate is greater than or equal to the preset standard deviation rate, a notification that the photographing image needs to be reacquired is sent out.

[0042] Compared with the prior art, the present application has the beneficial effects that the present application determines whether the vegetation restoration meets the standard based on the vegetation restoration change, timely and accurately completes the determination of whether the vegetation restoration meets the standard, effectively realizes the timely analysis of the image according to the vegetation restoration, determines the reason why the vegetation restoration does not meet the standard based on the area dispersion and the standard deviation rate, further realizes the timely analysis of the image according to the vegetation restoration, adjusts or sends out the corresponding notification according to the corresponding parameters, effectively improves the monitoring efficiency of the vegetation restoration while effectively realizing the intelligent adjustment of the image according to the vegetation restoration.

[0043] Further, the present application determines whether the vegetation restoration meets the standard based on the vegetation restoration change, effectively determines whether the reason why the vegetation restoration does not meet the standard needs to be determined based on the area dispersion, is beneficial to realize the subsequent targeted adjustment, avoids the misjudgment, further realizes the timely analysis of the image according to the vegetation restoration, and further improves the monitoring efficiency of the vegetation restoration.

[0044] Further, the present application determines the reason for the non-standard vegetation restoration based on the regional dispersion, accurately determines whether the cloud probability threshold needs to be adjusted based on the cloud coverage or the image resolution needs to be adjusted based on the boundary pixel density, avoids misjudgment, and timely adjusts the cloud probability threshold or the image resolution, ensures the accuracy of the determination of whether the vegetation restoration meets the standard, further realizes timely analysis of the image according to the vegetation restoration, and further improves the monitoring efficiency of the vegetation restoration.

[0045] Further, the present application increases the cloud probability threshold based on the cloud coverage, effectively avoids the misjudgment of whether the vegetation restoration meets the standard due to the non-standard cloud probability threshold, further realizes intelligent adjustment of the image according to the vegetation restoration, and further improves the monitoring efficiency of the vegetation restoration.

[0046] Further, the present application increases the cloud shadow buffer distance based on the solar elevation angle after the cloud probability threshold is increased, and adjusting the cloud shadow buffer distance can effectively avoid the misjudgment of whether the vegetation restoration meets the standard due to the non-standard cloud shadow buffer distance, further realizes intelligent adjustment of the image according to the vegetation restoration, and further improves the monitoring efficiency of the vegetation restoration.

[0047] Further, the present application increases the image resolution based on the boundary pixel density, effectively avoids the misjudgment of whether the vegetation restoration meets the standard due to the non-standard image resolution, further realizes intelligent adjustment of the image according to the vegetation restoration, and further improves the monitoring efficiency of the vegetation restoration.

[0048] Further, the present application determines whether the vegetation restoration meets the standard based on the vegetation restoration change after the cloud shadow buffer distance or the image resolution is adjusted, can determine the adjustment effect of the cloud probability threshold, the cloud shadow buffer distance and the image resolution, and when it is determined that the vegetation restoration still does not meet the standard, adjusts the aerosol optical depth based on the vegetation restoration change, further ensures the accuracy of the determination of whether the vegetation restoration meets the standard, further realizes timely analysis of the image according to the vegetation restoration, and further improves the monitoring efficiency of the vegetation restoration.

[0049] Further, the present application reduces the aerosol optical depth based on the vegetation restoration change difference, effectively avoids the misjudgment of whether the vegetation restoration meets the standard due to the non-standard aerosol optical depth, further realizes intelligent adjustment of the image according to the vegetation restoration, and further improves the monitoring efficiency of the vegetation restoration.

[0050] Furthermore, this invention determines whether vegetation restoration meets the standard based on the change in vegetation restoration after aerosol optical thickness adjustment. This effectively assesses the adjustment effect of aerosol optical thickness, determines whether vegetation restoration still does not meet the standard after aerosol optical thickness adjustment, and determines whether the reason for vegetation restoration not meeting the standard needs to be determined based on the standard deviation rate. This further enables timely analysis of images based on vegetation restoration status and improves the monitoring efficiency of vegetation restoration.

[0051] Furthermore, this invention determines the reasons why vegetation restoration does not meet the standards based on the standard deviation rate, and issues timely and accurate notifications that the vegetation restoration in the monitoring area does not meet the standards or that images need to be re-acquired and photographed, avoiding misjudgments. While further realizing timely analysis and intelligent adjustment of images based on the vegetation restoration status, it further improves the monitoring efficiency of vegetation restoration. Attached Figure Description

[0052] Figure 1 A block diagram of a system using an image analysis-based vegetation restoration monitoring method;

[0053] Figure 2 The flowchart shows the vegetation restoration monitoring method based on image analysis according to the present invention.

[0054] Figure 3 This is a flowchart illustrating the process for determining whether vegetation restoration meets the standards and the reasons why it does not meet the standards according to the present invention.

[0055] Figure 4 This is a flowchart illustrating the reasons why vegetation restoration does not meet the standards, as presented in this invention. Detailed Implementation

[0056] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0057] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0058] Moreover, it needs to be explained that in the description of the present application, unless otherwise explicitly specified and limited, the terms "mounting", "connection", "linking" should be understood in a broad sense and for example, can be fixed connection, can also be detachable connection, or integral connection; can be mechanical connection, can also be electrical connection; can be direct connection, can also be indirect connection through intermediate medium, can be internal communication of two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0059] Please refer to Figure 1 The structure of the system for monitoring vegetation recovery using image analysis-based vegetation recovery monitoring method is shown in the figure. The structure of the embodiment of the present application comprises a selection module, a processing module, a division module, an operation module, a determination module and an adjustment module; wherein,

[0060] The selection module is used to select the photographed image of vegetation recovery in the monitoring area range;

[0061] The processing module is connected with the selection module, and is used to process the photographed image to improve the monitoring accuracy;

[0062] The division module is connected with the processing module, and is used to divide the monitoring area into regions, and sequentially determine the processed photographed image corresponding to each division region;

[0063] The operation module is connected with the division module, and is used to sequentially determine the vegetation index of the corresponding division region based on the processed photographed image;

[0064] The operation module is also used to determine the vegetation recovery change amount of the corresponding division region according to the vegetation index;

[0065] The determination module is connected with the operation module, and is used to determine whether the vegetation recovery meets the standard based on the vegetation recovery change amount;

[0066] The determination module is also used to determine the reason why the vegetation recovery does not meet the standard based on the regional dispersion degree when it is determined that the vegetation recovery does not meet the standard;

[0067] The adjustment module is connected with the processing module and the determination module respectively, and is used to adjust the cloud probability threshold based on the cloud coverage rate or adjust the image resolution based on the boundary pixel density based on the reason determined based on the regional dispersion degree; increase the cloud shadow buffer distance based on the solar elevation angle after the cloud probability threshold is increased;

[0068] The determination module is also used to determine whether the vegetation recovery meets the standard based on the vegetation recovery change amount after the cloud shadow buffer distance or the image resolution adjustment is completed;

[0069] The adjustment module is also used to adjust the aerosol optical thickness based on the change in vegetation restoration when it is determined that the vegetation restoration does not meet the standard.

[0070] The determination module is also used to determine whether the vegetation restoration meets the standard based on the vegetation restoration change after the aerosol optical thickness adjustment is completed;

[0071] The adjustment module is also used to determine the reason why vegetation restoration does not meet the standard when it is determined that vegetation restoration does not meet the standard based on the standard deviation rate; and to issue a corresponding notification based on the standard deviation rate determination result.

[0072] Specifically, the vegetation restoration change is the difference between the current vegetation index and the historical vegetation index. The current vegetation index is derived from the current image, and the historical vegetation index is derived from historical images. In this embodiment, the comparison is made between the vegetation restoration of the monitored area in September of the current year and September of the previous year to see if it meets the standard. Therefore, the current vegetation index is derived from the image taken in September of the current year, and the historical vegetation index is derived from the image taken in the monitored area in September of the previous year. The vegetation restoration change is the difference between the current vegetation index and the historical vegetation index. The monitored area is 100 km². 2 The monitoring area is a lightly polluted, remote region.

[0073] For a single segmented region, the difference between the reflectance value of a pixel in the near-infrared band and the reflectance value of a pixel in the red band is calculated. The sum of the reflectance values ​​of the pixel in the near-infrared band and the reflectance values ​​of the pixel in the red band is obtained. The ratio of the difference to the sum is calculated. The average value of each ratio in the segmented region is then calculated, and the average value is recorded as the vegetation index of the segmented region.

[0074] Please see Figure 2 The diagram shows a flowchart of the vegetation restoration monitoring method based on image analysis according to the present invention. The method described in this embodiment includes:

[0075] Step S1: Select images of vegetation restoration within the monitoring area;

[0076] The captured images are processed to improve monitoring accuracy;

[0077] Step S2: Divide the monitoring area into regions and sequentially determine the processed captured images corresponding to each region.

[0078] Step S3: Based on the processed captured images, determine the vegetation index of the corresponding divided regions in sequence;

[0079] The vegetation restoration change in the corresponding divided area is determined based on the vegetation index.

[0080] Step S4, determining whether the vegetation restoration meets the standard based on the vegetation restoration change amount;

[0081] Determining the reason why the vegetation restoration does not meet the standard based on the regional dispersion when it is determined that the vegetation restoration does not meet the standard;

[0082] Step S5, adjusting the cloud probability threshold based on the cloud coverage or adjusting the image resolution based on the boundary pixel density based on the reason determined based on the regional dispersion; increasing the cloud shadow buffer distance based on the solar elevation angle after the cloud probability threshold is increased;

[0083] Step S6, determining whether the vegetation restoration meets the standard based on the vegetation restoration change amount after the cloud shadow buffer distance or the image resolution is adjusted;

[0084] Step S7, adjusting the aerosol optical depth based on the vegetation restoration change amount when it is determined that the vegetation restoration does not meet the standard;

[0085] Step S8, determining whether the vegetation restoration meets the standard based on the vegetation restoration change amount after the aerosol optical depth is adjusted;

[0086] Step S9, determining the reason why the vegetation restoration does not meet the standard based on the standard deviation when it is determined that the vegetation restoration does not meet the standard; issuing a corresponding notification according to the determination result of the standard deviation.

[0087] Please refer to Figure 3 Fig. 1, which is a flowchart of the process of determining whether the vegetation restoration meets the standard and the reason why the vegetation restoration does not meet the standard according to the present application. The process of determining whether the vegetation restoration meets the standard based on the vegetation restoration change amount according to the present application comprises:

[0088] When the vegetation restoration change amount is greater than or equal to a preset vegetation restoration change amount Z, it is determined that the vegetation restoration in the monitoring area meets the standard, the periodic determination of the vegetation restoration is completed, and the vegetation restoration in the next period is determined. In this embodiment, the preset vegetation restoration change amount Z is 0.05;

[0089] When the vegetation restoration change amount is less than the preset vegetation restoration change amount Z, the reason why the vegetation restoration does not meet the standard is determined based on the regional dispersion;

[0090] Specifically, the preset vegetation restoration change amount in this embodiment is set to 0.05 according to the general standard, and when the vegetation restoration change amount is less than the preset vegetation restoration change amount, the distribution of the divided area that does not meet the standard is further determined.

[0091] Please continue to refer to Figure 3As shown, the process of determining the reasons why vegetation restoration does not meet the standards based on the regional dispersion in this embodiment of the invention includes:

[0092] When the regional dispersion is less than the preset regional dispersion F, it is determined that the cloud probability threshold of the captured image does not meet the standard, and the cloud probability threshold is adjusted based on the cloud coverage. In this embodiment, the preset regional dispersion F = 0.3.

[0093] When the regional dispersion is greater than or equal to the preset regional dispersion F, it is determined that the image resolution of the captured image does not meet the standard, and the image resolution is adjusted based on the boundary pixel density;

[0094] Specifically, the distribution of the non-compliant regions is determined, with non-compliant regions recorded as 1 and compliant regions recorded as 0. Moran's I index of the monitored region is calculated, and the calculated value is recorded as the regional dispersion. Based on the actual test results, the preset regional dispersion in this embodiment is set to 0.3.

[0095] If the regional dispersion is less than the preset regional dispersion, it indicates that the non-standard division areas are concentrated, and the cloud probability threshold of the monitoring area needs to be adjusted. The cloud coverage rate can be used to precisely adjust the cloud probability threshold. If the regional dispersion is greater than or equal to the preset regional dispersion, the non-standard division areas are scattered and not concentrated, and the image resolution should be adjusted accordingly based on the boundary pixel density.

[0096] Please continue reading. Figure 3 As shown, the process of increasing the cloud probability threshold based on the cloud coverage rate in this embodiment of the invention includes:

[0097] When the cloud coverage rate is greater than the second preset cloud coverage rate R2, the cloud probability threshold is increased to 1.98 times the initial cloud probability threshold, wherein in this embodiment, the second preset cloud coverage rate R2 = 50%;

[0098] When the cloud coverage rate is less than or equal to the second preset cloud coverage rate R2 and greater than the first preset cloud coverage rate R1, the cloud probability threshold is increased to 1.50 times the initial cloud probability threshold, wherein, in this embodiment, the first preset cloud coverage rate R1 = 35%;

[0099] When the cloud coverage rate is less than or equal to the first preset cloud coverage rate R1, the cloud probability threshold is increased to 1.27 times the initial cloud probability threshold.

[0100] Specifically, the cloud coverage value range of the embodiment is 10% to 60%, the initial cloud probability threshold is 22%, the cloud probability threshold can be increased to 60%, the value range of the increase multiple of the cloud probability threshold is 1 to 2.72, the cloud coverage is greater, the cloud probability threshold is greater, and the values of the cloud coverage and the cloud probability threshold are obtained according to actual debugging results.

[0101] Please continue to refer to Figure 3 As shown in the figure, the process of increasing the cloud shadow buffer distance based on the sun elevation angle after the cloud probability threshold is increased in the embodiment of the application includes:

[0102] When the sun elevation angle is greater than a second preset sun elevation angle A2, the cloud shadow buffer distance is increased to 1.33 times of the initial cloud shadow buffer distance, wherein the second preset sun elevation angle A2 of the embodiment is 36.9°.

[0103] When the sun elevation angle is less than or equal to the second preset sun elevation angle A2 and greater than a first preset sun elevation angle A1, the cloud shadow buffer distance is increased to 1.79 times of the initial cloud shadow buffer distance, wherein the first preset sun elevation angle A1 of the embodiment is 17.8°.

[0104] When the sun elevation angle is less than or equal to the first preset sun elevation angle A1, the cloud shadow buffer distance is increased to 2.27 times of the initial cloud shadow buffer distance.

[0105] Specifically, the value range of the sun elevation angle is 0° to 50°, the initial cloud shadow buffer distance is 118 m, the cloud shadow buffer distance can be increased to 300 m at most, the value range of the increase multiple of the cloud shadow buffer distance is 1 to 2.54, the lower the sun elevation angle, the greater the increase multiple of the cloud shadow buffer distance, and the values of the sun elevation angle and the cloud shadow buffer distance are obtained according to actual debugging results.

[0106] Please refer to Figure 4 As shown in the figure, it is a flowchart for determining the reason why the vegetation restoration does not meet the standard. The process of increasing the image resolution based on the boundary pixel density in the embodiment of the application includes:

[0107] When the boundary pixel density is greater than a second preset boundary pixel density L2, the image resolution is increased to 0.73 times of the initial image resolution, wherein the second preset boundary pixel density L2 of the embodiment is 1.56.

[0108] When the boundary pixel density is less than or equal to the second preset boundary pixel density L2 and greater than a first preset boundary pixel density L1, the image resolution is increased to 0.47 times of the initial image resolution, wherein the first preset boundary pixel density L1 of the embodiment is 0.97.

[0109] When the boundary pixel density is less than or equal to the first preset boundary pixel density L1, the image resolution is increased to 0.26 times of the initial image resolution.

[0110] Specifically, the boundary pixel density ranges from 0.5 pixel / m to 2 pixel / m, the initial image resolution is 3 m / pixel, the image resolution is increased to at most 0.5 m / pixel, and the increase multiple of the image resolution ranges from 0.17 to 1. The lower the boundary pixel density, the greater the increase multiple of the image resolution. The values of the boundary pixel density and the image resolution are obtained from actual debugging results.

[0111] Please continue to refer to Figure 4 As shown in the figure, the process of determining whether the vegetation restoration meets the standard based on the vegetation restoration change amount after the cloud shadow buffer distance or the image resolution adjustment is completed in the embodiment of the present application, and the process comprises:

[0112] When the vegetation restoration change amount is greater than or equal to the preset vegetation restoration change amount Z, it is determined that the vegetation restoration of the monitoring area meets the standard, the periodic determination of the vegetation restoration is completed, and the vegetation restoration of the next period is determined;

[0113] When the vegetation restoration change amount is less than the preset vegetation restoration change amount Z, the aerosol optical thickness is adjusted based on the vegetation restoration change amount.

[0114] Specifically, after the cloud probability threshold and the image resolution adjustment are completed, the vegetation restoration change amount still does not meet the standard, it is determined that there is a problem of radiation and atmospheric correction, the aerosol optical thickness needs to be adjusted, and the vegetation restoration change amount can be effectively adjusted based on the vegetation restoration change amount.

[0115] Please continue to refer to Figure 4 As shown in the figure, the process of reducing the aerosol optical thickness based on the vegetation restoration change amount difference in the embodiment of the present application comprises:

[0116] When the vegetation restoration change amount difference is greater than a second preset vegetation restoration change amount difference AJ2, the aerosol optical thickness is reduced to 0.62 times of the initial aerosol optical thickness, wherein the second preset vegetation restoration change amount difference AJ2 of the embodiment is 0.76.

[0117] When the vegetation restoration change amount difference is less than or equal to the second preset vegetation restoration change amount difference AJ2 and greater than a first preset vegetation restoration change amount difference AJ1, the aerosol optical thickness is reduced to 0.78 times of the initial aerosol optical thickness, wherein the first preset vegetation restoration change amount difference AJ1 of the embodiment is 0.38.

[0118] when the vegetation restoration change amount difference is less than or equal to the first preset vegetation restoration change amount difference ΔJ1, the aerosol optical thickness is reduced to 0.91 times of the initial aerosol optical thickness;

[0119] Specifically, the vegetation restoration change amount difference is a difference between the preset vegetation restoration change amount and the vegetation restoration change amount.

[0120] The vegetation restoration change amount difference ranges from 0 to 1.05, the initial aerosol optical thickness is 0.15, the aerosol optical thickness can be reduced to 0.08 at most, the reduction multiple of the aerosol optical thickness ranges from 0.53 to 1, the greater the vegetation restoration change amount difference, the smaller the vegetation restoration change amount, and the greater the reduction multiple of the aerosol optical thickness, and the values of the vegetation restoration change amount difference and the aerosol optical thickness are obtained from actual debugging results.

[0121] Please continue to refer to Figure 4 As shown in the figure, the process of determining whether the vegetation restoration meets the standard based on the vegetation restoration change amount after the aerosol optical thickness adjustment is completed in the embodiment of the present application includes:

[0122] When the vegetation restoration change amount is greater than or equal to the preset vegetation restoration change amount Z, it is determined that the vegetation restoration in the monitoring area meets the standard, the periodic determination of the vegetation restoration is completed, and the vegetation restoration in the next period is determined;

[0123] When the vegetation restoration change amount is less than the preset vegetation restoration change amount Z, the reason why the vegetation restoration does not meet the standard is determined based on the standard deviation rate.

[0124] Specifically, if the vegetation restoration change amount still does not meet the standard after the aerosol optical thickness adjustment is completed, it is necessary to determine whether the photographed image needs to be reacquired, and the standard deviation rate can accurately determine this.

[0125] Please continue to refer to Figure 4 As shown in the figure, the process of determining the reason why the vegetation restoration does not meet the standard based on the standard deviation rate in the embodiment of the present application includes:

[0126] When the standard deviation rate is less than a preset standard deviation rate X, a notification that the vegetation restoration in the monitoring area does not meet the standard is sent, wherein, in the embodiment, the preset standard deviation rate X = 0.15.

[0127] When the standard deviation rate is greater than or equal to the preset standard deviation rate X, a notification that the photographed image needs to be reacquired is sent.

[0128] Specifically, the vegetation index of the monitoring area in September of this year, September of last year and September of the year before last is calculated, the mean and standard deviation are calculated respectively, and the ratio of the standard deviation to the mean is calculated. The ratio obtained is recorded as the standard deviation rate. The preset standard deviation rate of the embodiment is set to 0.15, and 0.15 is an actual experience threshold. When the standard deviation rate is greater than or equal to the preset standard deviation rate, it indicates that the shooting image needs to be re-shot, so as to avoid misjudgment of the vegetation recovery due to the image not meeting the standard.

[0129] So far, the technical solutions of the present application have been described in combination with the preferred embodiments shown in the drawings, but those skilled in the art can easily understand that the protection scope of the present application is obviously not limited to these specific embodiments. Those skilled in the art can make equivalent changes or replacements to the related technical features without departing from the principles of the present application, and the technical solutions after the changes or replacements will fall within the protection scope of the present application.

[0130] The above is only the preferred embodiment of the present application and is not used to limit the present application; for those skilled in the art, the present application can have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A vegetation restoration monitoring method based on image analysis, characterized by, The method comprises: selecting a monitoring area range for vegetation recovery; processing the captured image to improve monitoring accuracy; dividing the monitoring area into regions and determining the processed captured image corresponding to each divided region in turn; determining the vegetation index of the corresponding divided region based on the processed captured image; determining the vegetation recovery change of the corresponding divided region according to the vegetation index; determining whether the vegetation recovery meets the standard based on the vegetation recovery change; determining the reason why the vegetation recovery does not meet the standard based on the regional dispersion when it is determined that the vegetation recovery does not meet the standard; adjusting the cloud probability threshold based on the cloud coverage or adjusting the image resolution based on the boundary pixel density based on the reason determined based on the regional dispersion; increasing the cloud shadow buffer distance based on the solar elevation angle after the cloud probability threshold is increased; determining whether the vegetation recovery meets the standard based on the vegetation recovery change after the cloud shadow buffer distance or the image resolution adjustment is completed; adjusting the aerosol optical depth based on the vegetation recovery change when it is determined that the vegetation recovery does not meet the standard; determining whether the vegetation recovery meets the standard based on the vegetation recovery change after the aerosol optical depth adjustment is completed; determining the reason why the vegetation recovery does not meet the standard based on the standard deviation when it is determined that the vegetation recovery does not meet the standard; and issuing a corresponding notification according to the determination result of the standard deviation.

2. The image analysis-based vegetation recovery monitoring method according to claim 1, characterized in that, The process of determining whether the vegetation recovery meets the standard based on the vegetation recovery change comprises: when the vegetation recovery change is greater than or equal to a preset vegetation recovery change, it is determined that the vegetation recovery of the monitoring area meets the standard, the periodic determination of the vegetation recovery is completed, and the next period of vegetation recovery is determined; when the vegetation recovery change is less than the preset vegetation recovery change, the reason why the vegetation recovery does not meet the standard is determined based on the regional dispersion.

3. The image analysis-based vegetation recovery monitoring method according to claim 2, characterized in that, The process of determining the reason why the vegetation recovery does not meet the standard based on the regional dispersion comprises: when the regional dispersion is less than a preset regional dispersion, it is determined that the cloud probability threshold of the captured image does not meet the standard, and the cloud probability threshold is adjusted based on the cloud coverage; when the regional dispersion is greater than or equal to the preset regional dispersion, it is determined that the image resolution of the captured image does not meet the standard, and the image resolution is adjusted based on the boundary pixel density.

4. The image analysis-based vegetation recovery monitoring method according to claim 3, characterized in that, The process of increasing the cloud probability threshold based on the cloud coverage comprises: the cloud probability threshold is increased based on the cloud coverage, and the increase amplitude of the cloud probability threshold is proportional to the cloud coverage.

5. The image analysis-based vegetation recovery monitoring method according to claim 4, characterized in that, The process of increasing the cloud shadow buffer distance based on the solar elevation angle after the cloud probability threshold is increased comprises: the cloud shadow buffer distance is increased based on the solar elevation angle, and the increase amplitude of the cloud shadow buffer distance is inversely proportional to the solar elevation angle.

6. The image analysis-based vegetation recovery monitoring method according to claim 5, characterized in that, The process of increasing the image resolution based on the boundary pixel density comprises: the image resolution is increased based on the boundary pixel density, and the increase amplitude of the image resolution is inversely proportional to the boundary pixel density.

7. The image analysis based vegetation restoration monitoring method according to claim 6, characterized in that, The process of determining whether the vegetation restoration meets the standard based on the vegetation restoration change amount after the cloud shadow buffer distance or the image resolution adjustment is completed includes, When the vegetation restoration change amount is greater than or equal to the preset vegetation restoration change amount, it is determined that the vegetation restoration in the monitoring area meets the standard, the periodic determination of the vegetation restoration is completed, and the next period of vegetation restoration is determined; When the vegetation restoration change amount is less than the preset vegetation restoration change amount, the aerosol optical depth is adjusted based on the vegetation restoration change amount.

8. The image analysis based vegetation restoration monitoring method according to claim 7, characterized in that, The process of reducing the aerosol optical depth based on the vegetation restoration change amount difference includes, The aerosol optical depth is reduced based on the vegetation restoration change amount difference, and the reduction amplitude of the aerosol optical depth is proportional to the vegetation restoration change amount difference.

9. The image analysis based vegetation restoration monitoring method according to claim 8, characterized in that, The process of determining whether the vegetation restoration meets the standard based on the vegetation restoration change amount after the aerosol optical depth adjustment is completed includes, When the vegetation restoration change amount is greater than or equal to the preset vegetation restoration change amount, it is determined that the vegetation restoration in the monitoring area meets the standard, the periodic determination of the vegetation restoration is completed, and the next period of vegetation restoration is determined; When the vegetation restoration change amount is less than the preset vegetation restoration change amount, the reason why the vegetation restoration does not meet the standard is determined based on the standard deviation rate.

10. The image analysis-based vegetation recovery monitoring method according to claim 9, characterized in that, The process of determining the reason why the vegetation restoration does not meet the standard based on the standard deviation rate includes, When the standard deviation rate is less than the preset standard deviation rate, a notification that the vegetation restoration in the monitoring area does not meet the standard is sent; When the standard deviation rate is greater than or equal to the preset standard deviation rate, a notification that the image needs to be re-acquired is sent.

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