Method and device for correcting the effect of marine ranch facilities on satellite remote sensing reflectivity

Abstract

The present invention discloses a method and device for correcting the influence of marine ranch facilities on satellite remote sensing reflectivity. The method comprises: using the satellite specific band remote sensing reflectivity of the area outside the ranch as a discrimination standard, comparing the satellite specific band remote sensing reflectivity of the pixel in the ranch area with the discrimination standard, and screening the affected pixel according to the comparison result; calculating the degree of deviation between the satellite specific band remote sensing reflectivity of the affected pixel and the discrimination standard, comparing the degree of deviation with the actual remote sensing reflectivity of the breeding facility, and calculating the breeding facility influence quantitative factor of the breeding facility on the water body in the ranch area; using the breeding facility influence quantitative factor to calculate the influence degree value on the water body in the ranch area, and correcting the satellite remote sensing reflectivity of the water body by the influence degree value. The above scheme is adopted to improve the accuracy of the remote sensing reflectivity of the water body of the marine ranch by correcting the remote sensing reflectivity of the water body of the marine ranch sensed by the satellite sensor.

Description

Technical Field

[0001] The present invention relates to the field of marine remote sensing technology, and in particular to a method and a device for correcting the influence of marine ranch facilities on satellite remote sensing reflectivity. Background Art

[0002] The concept of marine ranching combines traditional fisheries with modern technology. Through scientific planning and management, it improves the production efficiency of marine resources while protecting the health and diversity of marine ecosystems. Therefore, it is necessary to carry out monitoring and evaluation of water environment elements in marine ranching areas. Among the existing technologies, water color remote sensing technology has the advantages of rapid observation, low cost, and high temporal and spatial coverage. It has become the main means of obtaining information on marine water environment elements in a large temporal and spatial range.

[0003] In the past few decades, researchers have conducted a lot of research on satellite remote sensing monitoring of marine water environment elements, and have made significant research progress. A relatively mature technical system has been formed. The basic process of water color remote sensing technology is: use satellite water color sensors to observe the target sea area, obtain satellite remote sensing images, and then obtain water body remote sensing reflectivity (basic data for water environment element inversion) through data preprocessing such as geometric calibration, radiation calibration, and atmospheric correction. After that, using the water environment element remote sensing inversion algorithm, various water environment element remote sensing products can be calculated through remote sensing reflectivity.

[0004] However, the problem with current water color remote sensing technology is that its accuracy is high when targeting conventional open water bodies (without the influence of aquaculture facilities, etc.), but marine ranches are complex areas with many interference factors to remote sensing. The remote sensing reflectivity of water bodies in marine ranches obtained by satellite sensors has low accuracy and poor usability, which leads to high errors in existing remote sensing products of marine water environment elements in marine ranch areas. Summary of the invention

[0005] Purpose of the invention: The present invention provides a method and device for correcting the influence of marine ranch facilities on satellite remote sensing reflectivity, aiming to solve the technical problem of low accuracy of remote sensing reflectivity of water bodies in marine ranches obtained by satellite sensors.

[0006] Technical solution: The present invention provides a method for correcting the influence of marine ranch facilities on satellite remote sensing reflectivity, comprising: obtaining the satellite remote sensing reflectivity of a target area through a satellite sensor; dividing the target area into an area within the ranch and an area outside the ranch; using the satellite specific band remote sensing reflectivity of the area outside the ranch as a discrimination criterion to screen whether the pixels in the area within the ranch are affected by the breeding facilities of the ranch, comparing the satellite specific band remote sensing reflectivity of the pixels in the area within the ranch with the discrimination criterion, and screening out the affected pixels according to the comparison result; calculating the degree of deviation between the satellite specific band remote sensing reflectivity of the affected pixels and the discrimination criterion, and comparing the degree of deviation with the actual remote sensing reflectivity of the breeding facilities to calculate the breeding facility impact quantification factor of the breeding facilities on the water body in the area within the ranch; using the breeding facility impact quantification factor to calculate the degree of influence of the breeding facilities on the water body in the area within the ranch, and correcting the satellite remote sensing reflectivity of the water body according to the degree of influence value to obtain the corrected satellite remote sensing reflectivity of the water body in the area within the ranch.

[0007] Specifically, the satellite remote sensing reflectivity of the target area at multiple time nodes is obtained through satellite sensors.

[0008] Specifically, the satellite remote sensing reflectivity in a specific band is the satellite remote sensing reflectivity in a band from 1500nm to 1700nm, or the satellite remote sensing reflectivity in a band from 2100nm to 2300nm.

[0009] Specifically, the satellite remote sensing reflectivity in a specific wavelength band is the satellite remote sensing reflectivity at a wavelength of 1609 nm, or the satellite remote sensing reflectivity at a wavelength of 2201 nm.

[0010] Specifically, the satellite remote sensing reflectivity in a specific waveband is the satellite remote sensing reflectivity at a wavelength of 2201 nm.

[0011] Specifically, the satellite remote sensing reflectance of the area outside the pasture in a specific band used as the discrimination standard, the satellite remote sensing reflectance of the pixels in the pasture area for comparison with the discrimination standard, and the satellite remote sensing reflectance of the water body in the pasture area before correction, all have their time nodes within the same time period.

[0012] Specifically, the discrimination criterion is calculated using the following formula:

[0013] b=R rs-out-avg (X)+na,

[0014] Among them, b represents the discrimination standard, X represents the wavelength of a specific band, and R rs-out-avg (X) represents the mean value of the satellite specific band remote sensing reflectance of the area outside the pasture, a represents the standard deviation of the satellite specific band remote sensing reflectance of the area outside the pasture, and n represents the adjustment coefficient of a.

[0015] Specifically, the quantitative factor of the impact of the breeding facilities is calculated using the following formula:

[0016] A=(R rs-in (X)-b) / R rs-buoy (X),

[0017] Among them, A represents the quantitative factor of the impact of breeding facilities, R rs-in (X) represents the satellite specific band remote sensing reflectance of the affected pixels in the pasture area, R rs-buoy (X) represents the actual specific band remote sensing reflectivity of the aquaculture facility.

[0018] Specifically, the corrected water remote sensing reflectivity in the pasture area is calculated using the following formula:

[0019] R rs-corrected (λ) = R rs (λ)-AR rs-buoy (λ),

[0020] Among them, λ represents the wavelength of the water in the pasture area, R rs-corrected (λ) represents the corrected satellite remote sensing reflectance of the water body in the pasture area, R rs (λ) represents the satellite remote sensing reflectance of the water body in the pasture area before correction, R rs-buoy (λ) represents the actual remote sensing reflectivity of the aquaculture facilities.

[0021] The present invention also provides a device for correcting the influence of marine ranch facilities on satellite remote sensing reflectivity, comprising: a satellite remote sensing reflectivity acquisition unit, a division unit, a discrimination unit, an influence quantification unit and a correction unit, wherein: the satellite remote sensing reflectivity acquisition unit is used to obtain the satellite remote sensing reflectivity of the target area through a satellite sensor; the division unit is used to divide the target area into an area within the ranch and an area outside the ranch; the discrimination unit is used to use the satellite specific band remote sensing reflectivity of the area outside the ranch as a discrimination standard, to screen whether the pixels in the area within the ranch are affected by the breeding facilities of the ranch, and to use the satellite specific band remote sensing reflectivity of the pixels in the area within the ranch as a discrimination standard. The remote sensing reflectance is compared with the discrimination standard, and the affected pixels are screened according to the comparison result; the impact quantification unit is used to calculate the deviation degree between the satellite specific band remote sensing reflectance of the affected pixels and the discrimination standard, and compare the deviation degree with the actual remote sensing reflectance of the breeding facilities to calculate the breeding facility impact quantification factor of the breeding facilities on the water body in the pasture area; the correction unit is used to calculate the impact degree of the breeding facilities on the water body in the pasture area using the breeding facility impact quantification factor, and correct the satellite remote sensing reflectance of the water body according to the impact degree value to obtain the corrected satellite remote sensing reflectance of the water body in the pasture area.

[0022] Beneficial effects: Compared with the prior art, the present invention has the following significant advantages: by correcting the remote sensing reflectivity of the water body of the marine ranch sensed by the satellite sensor, the accuracy of the remote sensing reflectivity of the water body of the marine ranch is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 A schematic flow chart of a method for correcting the effect of marine ranch facilities on satellite remote sensing reflectivity provided by the present invention;

[0024] Figure 2 is the average remote sensing reflectance spectral curve of the target area at the first time node;

[0025] Figure 3 is the average remote sensing reflectance spectral curve of the target area at the second time node;

[0026] Figure 4 is the average remote sensing reflectance spectral curve of the target area at the third time node;

[0027] Figure 5 is the average remote sensing reflectance spectral curve of the target area at the fourth time node;

[0028] Figure 6 is the satellite remote sensing reflectivity of the area inside the pasture and outside the pasture at a wavelength of 2201nm at the first time node;

[0029] Figure 7is the satellite remote sensing reflectivity of the area inside the pasture and outside the pasture at a wavelength of 2201nm at the second time node;

[0030] Figure 8 is the satellite remote sensing reflectivity of the area inside the pasture and outside the pasture at a wavelength of 2201nm at the third time node;

[0031] Fig. 9 is the satellite remote sensing reflectivity of the area inside the pasture and outside the pasture at a wavelength of 2201nm at the fourth time node;

[0032] Fig.10 A schematic diagram of water transparency obtained by inversion calculation based on the corrected water remote sensing reflectivity;

[0033] Fig.11 This is a schematic diagram of water transparency obtained by inverting and calculating the water body remote sensing reflectivity before correction. DETAILED DESCRIPTION

[0034] The technical solution of the present invention is further described below in conjunction with the accompanying drawings.

[0035] Existing remote sensing products of marine water environment elements often have high errors in marine ranch areas. This is because there are often aquaculture facilities (such as aquaculture cages, rafts and buoys) in marine ranch aquaculture areas, which will inevitably reflect the downward light of the sun. The reflected light then enters the field of view of the satellite sensor together with the water body's off-water radiance, which undoubtedly affects the water body remote sensing reflectivity data, thereby causing errors in the remote sensing inversion of water environment elements. Therefore, how to quantify the impact of the reflected signal of marine ranch aquaculture facilities, propose an effective correction method, and then eliminate the impact of aquaculture facilities on the remote sensing reflectivity of water bodies, and ensure the accuracy of remote sensing inversion of water environment elements in marine ranch areas, is a technical problem that needs to be solved urgently.

[0036] See also Figure 1 , which is a flow chart of the method provided by the present invention for correcting the impact of marine ranch facilities on satellite remote sensing reflectivity.

[0037] In the specific implementation, in the preliminary preparation work, based on the field investigation voyage, the ASD (Analytical Spectral Devices) FieldSpec Pro portable field spectrometer can be used to measure the remote sensing reflectance hyperspectral data of the marine ranch aquaculture facilities, and according to the spectral response function of the Landsat-8 satellite OLI sensor, it is resampled to the multispectral data of the corresponding band of the OLI sensor, so that the actual remote sensing reflectance of the aquaculture facilities can be obtained.

[0038] In the embodiment of the present invention, the satellite remote sensing reflectivity of the target area is obtained by a satellite sensor.

[0039] In the embodiment of the present invention, the satellite remote sensing reflectivity of the target area at multiple time nodes is obtained by using a satellite sensor.

[0040] In a specific implementation, all or at least part of the target ranch (target marine ranch breeding area) is within the target area. As for the size of the target area itself, the present invention does not make any special limitation and can be selected according to the needs of the actual application scenario.

[0041] In a specific implementation, the satellite remote sensing reflectivity of multiple time nodes is obtained through satellite sensors, which is usually manifested as obtaining the satellite remote sensing reflectivity of the target area on a certain day in four seasons, for example Figures 2 to 5 , are the average remote sensing reflectance spectral curves of the target marine ranch area on November 16, 2021 (autumn), January 3, 2022 (winter), March 8, 2022 (spring), and August 15, 2022 (summer). The reason for obtaining satellite remote sensing reflectance at multiple time nodes is that the appearance of the target area will change in different seasons, the reflectance will also change accordingly, and the degree of interaction between pixels in the area will also be different. In order to improve the correction accuracy, the discrimination criteria mentioned later in the present invention will also be adjusted accordingly at different time nodes.

[0042] In the embodiment of the present invention, the target area is divided into an area inside the ranch and an area outside the ranch, that is, an area inside the marine ranch breeding area and an area outside the breeding area.

[0043] In an embodiment of the present invention, the satellite remote sensing reflectivity in a specific band is the satellite remote sensing reflectivity in a band from 1500nm to 1700nm, or the satellite remote sensing reflectivity in a band from 2100nm to 2300nm.

[0044] In the embodiment of the present invention, the satellite remote sensing reflectivity in a specific waveband is the satellite remote sensing reflectivity at a wavelength of 1609 nm or the satellite remote sensing reflectivity at a wavelength of 2201 nm.

[0045] See also Figures 2 to 5 , which are the first time nodes (November 16, 2021, Figure 2 ), the second time node (January 3, 2022, Figure 3 ), the third time node (March 8, 2022, Figure 4 ) and the fourth time node (August 15, 2022, Figure 5The average remote sensing reflectance spectral curve of the target area (target marine ranch area) was obtained by comparing the remote sensing reflectance data at seven wavelengths: 443, 483, 561, 655, 865, 1609 and 2201 nm. After comparison, it can be found that there are obvious differences in the remote sensing reflectance at 1609nm and 2201nm between the area inside the ranch and the area outside the ranch.

[0046] See also Figures 6 to 9 , which are the first time nodes (November 16, 2021, Figure 6 ), the second time node (January 3, 2022, Figure 7 ), the third time node (March 8, 2022, Figure 8 ) and the fourth time node (August 15, 2022, Fig. 9 Satellite remote sensing reflectance (R rs (2201)).

[0047] In the specific implementation, the pre-processed satellite remote sensing data is processed according to the scope of the marine ranch breeding area, and the entire remote sensing image is divided into the internal area of ​​the marine ranch breeding area (the area inside the ranch) and the external area of ​​the breeding area (the area outside the ranch), and the two will not overlap. The internal data of the marine ranch breeding area and the external data of the marine ranch breeding area are extracted, and the remote sensing reflectance spectral data inside and outside the marine ranch breeding area are averaged respectively, and the change characteristics of the average spectrum are analyzed (see Figures 2 to 5 ). It can be concluded from the average spectral curve that the difference in remote sensing reflectivity inside and outside the breeding area is mainly manifested in the shortwave infrared (SWIR) band. Outside the marine ranch breeding area, due to the strong absorption characteristics of the water body, the remote sensing reflectivity values ​​at wavelengths of 1609nm and 2201nm are close to 0, while inside the marine ranch breeding area, the remote sensing reflectivity values ​​at wavelengths of 1609nm and 2201nm show obvious differences, and the values ​​are significantly greater than 0, which is mainly due to the high reflectivity characteristics of the breeding facilities in these bands. Therefore, the bands in which breeding facilities have a significant impact on the remote sensing reflectivity of water bodies are near 1609nm and 2201nm. In the embodiments of the present invention, the satellite remote sensing reflectivity at a wavelength of 2201nm is cited for subsequent explanations and calculations.

[0048] In the specific implementation, the R values ​​of pixels in the marine ranch breeding area (which may be affected by the breeding facilities) and pixels outside the breeding area (open water areas not affected by the breeding facilities) in the images at different time points are counted respectively. rs (2201) Distribution characteristics (see Figures 6 to 9 ). It can be seen that Rrs (2201) Only a small part is close to the outside of the marine ranch breeding area, and the maximum value can reach 0.008sr -1 , and outside the marine ranch breeding area rs (2201) Maximum only 0.002sr -1 Since the reflectivity of aquaculture facilities is much higher than the remote sensing reflectivity of water bodies, it can be inferred that the R rs The abnormally high value of (2201) is mainly affected by the breeding facilities.

[0049] In an embodiment of the present invention, the satellite specific band remote sensing reflectivity of the area outside the pasture is used as a discrimination criterion to screen whether the pixels in the area inside the pasture are affected by the breeding facilities of the pasture, and the satellite specific band remote sensing reflectivity of the pixels in the area inside the pasture is compared with the discrimination criterion, and the affected pixels are screened according to the comparison results.

[0050] In the specific implementation, considering that the marine ranch and the surrounding sea areas are turbid water bodies, R rs (2201) may still be slightly affected by water bodies. In addition, satellite remote sensing data may also have certain systematic biases during preprocessing. Figures 2 to 9 The results also show that even for pixels outside the marine ranch that are not affected by ranch facilities, R rs (2201) also presents a certain small value, which may be the influence of turbid water or the residual system deviation during satellite data preprocessing. rs (2201) histogram, a discriminant parameter b is proposed for automatically judging whether a pixel is indeed affected by ranch facilities. Then, with this discriminant parameter as a reference, the internal area of ​​the marine ranch is judged pixel by pixel whether it is affected by the marine ranch aquaculture facilities, that is: when the R rs When the value of (2201) is greater than b, the pixel is considered to be affected by the aquaculture facilities. On the contrary, when the R value of a pixel in the aquaculture area is greater than b, the pixel is considered to be affected by the aquaculture facilities. rs (2201) When the value is less than or equal to b, the pixel is identified as a pixel not affected by aquaculture facilities. It is worth noting that the b value may be a variable value, and there may be certain differences in the b values ​​at different time nodes, mainly because the remote sensing reflectivity of the water body outside the aquaculture area also changes in different seasons. In addition, the data system deviation of different scene images may also be inconsistent. Therefore, the value of the discriminant parameter b can be determined for different time nodes.

[0051] In the specific implementation, the b value is based on the R rs(2201) is calculated because the external pixels are not affected by the aquaculture facilities but may be affected by the turbidity of the water body. Therefore, R rs The value calculated based on (2201) can represent the benchmark that is affected by water turbidity but not by aquaculture facilities, and can be used to screen which pixels are affected by aquaculture facilities.

[0052] In the specific implementation, in order to further optimize the discrimination criteria as a measure to distinguish whether the pixels in the pasture area are affected by the breeding facilities of the pasture, the pixels R outside the marine pasture breeding area (outside the pasture area) can be rs The mean value of (2201) plus its standard deviation is used to represent the average and comprehensive R of the pixels outside the pasture area. rs (2201) level.

[0053] In the embodiment of the present invention, the discrimination criterion is calculated using the following formula:

[0054] b=R rs-out-avg (X)+na,

[0055] Where b represents the discrimination standard, X represents the wavelength of a specific band (e.g. 2201nm), and R rs-out-avg (X) represents the mean value of the satellite specific band remote sensing reflectance of the area outside the pasture, a represents the standard deviation of the satellite specific band remote sensing reflectance of the area outside the pasture, and n represents the adjustment coefficient of a (which can be set accordingly according to the application scenario).

[0056] In an embodiment of the present invention, the degree of deviation between the satellite specific band remote sensing reflectivity of the affected pixel and the discrimination standard is calculated, and the degree of deviation is compared with the actual remote sensing reflectivity of the breeding facility to calculate the quantitative factor of the breeding facility impact on the water body in the pasture area.

[0057] In the specific implementation, after screening out the affected pixels in the pasture area, we further prepare to calculate the specific degree of impact of these affected pixels and make corrections accordingly. The specific calculation method is to calculate the impact size of the affected pixels themselves (the degree of deviation between the remote sensing reflectance of a specific band and the discrimination standard), and then compare the degree of deviation with the actual remote sensing reflectance of the breeding facilities. The quantitative results obtained in this way can characterize the overall impact of the breeding facilities on these pixels (the quantitative factor of the impact of breeding facilities).

[0058] In the embodiment of the present invention, the quantitative factor of the impact of the breeding facilities is calculated using the following formula:

[0059] A=(R rs-in (X)-b) / R rs-buoy (X),

[0060] Among them, A represents the quantitative factor of the impact of breeding facilities, R rs-in (X) represents the satellite specific band remote sensing reflectance of the affected pixels in the pasture area, R rs-buoy (X) represents the actual specific band remote sensing reflectivity of the aquaculture facility. In the embodiment of the present invention, X can be 2201 nm.

[0061] In an embodiment of the present invention, a quantitative impact factor of breeding facilities is used to calculate the numerical value of the impact degree of breeding facilities on the water body in the pasture area, and the satellite remote sensing reflectivity of the water body is corrected according to the impact degree value to obtain the corrected satellite remote sensing reflectivity of the water body in the pasture area.

[0062] In specific implementation, the quantitative impact factor of breeding facilities characterizes the overall impact of breeding facilities on pixels. Therefore, the impact degree value of water bodies in the pasture area (the impact degree value of remote sensing reflectivity) can be calculated through the quantitative impact factor of breeding facilities. Furthermore, the impact degree value of water bodies can be used to correct the satellite remote sensing reflectivity of water bodies.

[0063] In the embodiment of the present invention, the corrected water remote sensing reflectivity of the pasture area is calculated using the following formula:

[0064] R rs-corrected (λ) = R rs (λ)-AR rs-buoy (λ),

[0065] Among them, λ represents the wavelength of the water in the pasture area, R rs-corrected (λ) represents the corrected satellite remote sensing reflectance of the water body in the pasture area (at wavelength λ), R rs (λ) represents the satellite remote sensing reflectance of the water body in the pasture area before correction (at wavelength λ), R rs-buoy (λ) represents the actual remote sensing reflectivity of the aquaculture facility (at wavelength λ).

[0066] In a specific implementation, the full-band wavelength of the water body in the pasture area can be corrected using the influence degree value of the water body, and the value range of λ is the full-band wavelength of the water body in the pasture area.

[0067] In an embodiment of the present invention, the satellite remote sensing reflectivity of a specific band of an area outside the pasture used as a discrimination standard, the satellite remote sensing reflectivity of a specific band of pixels in the pasture area used for comparison with the discrimination standard, and the satellite remote sensing reflectivity of water bodies in the pasture area before correction, all have their time nodes within the same time period.

[0068] In a specific implementation, the judgment criteria used for calculation in the present invention, the satellite remote sensing reflectivity of the pixels in the pasture area in a specific band, and the satellite remote sensing reflectivity of the water body in the pasture area before correction are all collected within a time period, that is, within the same image, for example, an image of November 16, 2021. The start and end nodes of the time period of the specific image are determined by the actual application scenario.

[0069] See also Fig.10 , which is the water transparency Z obtained by inversion calculation based on the corrected water remote sensing reflectivity (using the correction method provided by the present invention) sd , and a comparison diagram with the measured results; see Fig.11 , which is the water transparency Z obtained by inversion based on the water remote sensing reflectivity before correction sd , and a comparison diagram with the measured results. Fig.10 and Fig.11 Among them, the circle corresponds to the numerical value on the Y-axis, which represents the water transparency obtained by inversion calculation based on the remote sensing reflectivity of the water body before (after) correction; the circle corresponds to the numerical value on the X-axis, which represents the measured result of water transparency; and the inclined dotted line represents the 1:1 line.

[0070] from Fig.10 and Fig.11 It can be seen that the transparency obtained based on the inversion of the corrected water body remote sensing reflectivity is more consistent with the measured results, and the sample points are concentrated near 1:1. The transparency obtained by inverting the uncorrected water body remote sensing reflectivity is significantly underestimated compared with the measured results. At the same time, the calculated mean absolute percentage error (MAPE) and root mean square error (RMSE) values ​​also show that the transparency based on the corrected remote sensing reflectivity inversion is more accurate, with biases of -0.13 and -0.25 respectively. The above verification results show that the aquaculture facility impact correction method provided by the present invention is effective and ensures the inversion accuracy of water environment elements in complex areas of marine ranches.

[0071] The present invention also provides a device for correcting the influence of marine ranch facilities on satellite remote sensing reflectivity, comprising: a satellite remote sensing reflectivity acquisition unit, a division unit, a discrimination unit, an influence quantification unit and a correction unit, wherein: the satellite remote sensing reflectivity acquisition unit is used to obtain the satellite remote sensing reflectivity of the target area through a satellite sensor; the division unit is used to divide the target area into an area within the ranch and an area outside the ranch; the discrimination unit is used to use the satellite specific band remote sensing reflectivity of the area outside the ranch as a discrimination standard, to screen whether the pixels in the area within the ranch are affected by the breeding facilities of the ranch, and to use the satellite specific band remote sensing reflectivity of the pixels in the area within the ranch as a discrimination standard. The remote sensing reflectance is compared with the discrimination standard, and the affected pixels are screened according to the comparison result; the impact quantification unit is used to calculate the deviation degree between the satellite specific band remote sensing reflectance of the affected pixels and the discrimination standard, and compare the deviation degree with the actual remote sensing reflectance of the breeding facilities to calculate the breeding facility impact quantification factor of the breeding facilities on the water body in the pasture area; the correction unit is used to calculate the impact degree of the breeding facilities on the water body in the pasture area using the breeding facility impact quantification factor, and correct the satellite remote sensing reflectance of the water body according to the impact degree value to obtain the corrected satellite remote sensing reflectance of the water body in the pasture area.

[0072] The device for correcting the influence of marine ranch facilities on satellite remote sensing reflectivity provided by the present invention, wherein the units for executing methods, steps and functions, and the specific methods, steps and functions executed therein, can refer to the method for correcting the influence of marine ranch facilities on satellite remote sensing reflectivity provided by the present invention.

Claims

1. A method for correcting the effect of marine ranch facilities on satellite remote sensing reflectivity, characterized in that: include: Obtain satellite remote sensing reflectivity of the target area through satellite sensors; Divide the target area into the area inside the pasture and the area outside the pasture; The satellite specific band remote sensing reflectance of the area outside the pasture is used as a discrimination standard to screen whether the pixels in the pasture area are affected by the breeding facilities of the pasture, and the satellite specific band remote sensing reflectance of the pixels in the pasture area is compared with the discrimination standard, and the affected pixels are screened according to the comparison result; the discrimination standard is calculated using the following formula: b=R rs-out-avg (X)+na, Among them, b represents the discrimination standard, X represents the wavelength of a specific band, and R rs-out-avg (X) represents the mean value of the satellite specific band remote sensing reflectance of the area outside the pasture, a represents the standard deviation of the satellite specific band remote sensing reflectance of the area outside the pasture, and n represents the adjustment coefficient of a; The deviation between the satellite specific band remote sensing reflectance of the affected pixels and the discrimination standard is calculated, and the deviation is compared with the actual remote sensing reflectance of the breeding facilities to calculate the quantitative factor of the breeding facility impact on the water body in the pasture area; the quantitative factor of the breeding facility impact is calculated using the following formula: A=(R rs-in (X)-b) / R rs-buoy (X), Among them, A represents the quantitative factor of the impact of breeding facilities, R rs-in (X) represents the satellite specific band remote sensing reflectance of the affected pixels in the pasture area, R rs-buoy (X) represents the actual specific band remote sensing reflectivity of the aquaculture facility; The impact quantification factor of aquaculture facilities is used to calculate the impact degree of aquaculture facilities on the water body in the pasture area, and the satellite remote sensing reflectivity of the water body is corrected by the impact degree value to obtain the corrected satellite remote sensing reflectivity of the water body in the pasture area; the corrected water body remote sensing reflectivity in the pasture area is calculated using the following formula: R rs-corrected (λ)=R rs (l)-AR rs-buoy (l), Among them, λ represents the wavelength of the water in the pasture area, R rs-corrected (λ) represents the corrected satellite remote sensing reflectance of the water body in the pasture area, R rs (λ) represents the satellite remote sensing reflectance of the water body in the pasture area before correction, R rs-buoy (λ) represents the actual remote sensing reflectivity of the aquaculture facilities.

2. The method for correcting the effect of marine ranch facilities on satellite remote sensing reflectivity according to claim 1, characterized in that: The step of obtaining the satellite remote sensing reflectivity of the target area by using a satellite sensor includes: The satellite remote sensing reflectivity of the target area at multiple time nodes is obtained through satellite sensors.

3. The method for correcting the effect of marine ranch facilities on satellite remote sensing reflectivity according to claim 1, characterized in that: The satellite specific band remote sensing reflectivity is the satellite remote sensing reflectivity in the 1500nm to 1700nm band, or the satellite remote sensing reflectivity in the 2100nm to 2300nm band.

4. The method for correcting the effect of marine ranch facilities on satellite remote sensing reflectivity according to claim 3, characterized in that: The satellite remote sensing reflectivity in a specific waveband is the satellite remote sensing reflectivity at a wavelength of 1609 nm or the satellite remote sensing reflectivity at a wavelength of 2201 nm.

5. The method for correcting the effect of marine ranch facilities on satellite remote sensing reflectivity according to claim 4, characterized in that: The satellite specific band remote sensing reflectivity is the satellite remote sensing reflectivity at a wavelength of 2201nm.

6. The method for correcting the effect of marine ranch facilities on satellite remote sensing reflectivity according to claim 2, characterized in that: The satellite remote sensing reflectance of the area outside the pasture in a specific band as the judgment standard, the satellite remote sensing reflectance of the pixels in the pasture area for comparison with the judgment standard, and the satellite remote sensing reflectance of the water body in the pasture area before correction, all have their time nodes within the same time period.

7. A device for correcting the effect of marine ranch facilities on satellite remote sensing reflectivity, characterized in that: include: Satellite remote sensing reflectivity acquisition unit, division unit, discrimination unit, impact quantification unit and correction unit, wherein: The satellite remote sensing reflectivity acquisition unit is used to acquire the satellite remote sensing reflectivity of the target area through a satellite sensor; The division unit is used to divide the target area into an area within the pasture and an area outside the pasture; The discrimination unit is used to use the satellite specific band remote sensing reflectance of the area outside the pasture as a discrimination standard to screen whether the pixels in the pasture area are affected by the breeding facilities of the pasture, compare the satellite specific band remote sensing reflectance of the pixels in the pasture area with the discrimination standard, and screen out the affected pixels according to the comparison result; the discrimination standard is calculated using the following formula: b=R rs-out-avg (X)+na, Among them, b represents the discrimination standard, X represents the wavelength of a specific band, and R rs-out-avg (X) represents the mean value of the satellite specific band remote sensing reflectance of the area outside the pasture, a represents the standard deviation of the satellite specific band remote sensing reflectance of the area outside the pasture, and n represents the adjustment coefficient of a; The impact quantification unit is used to calculate the degree of deviation between the satellite specific band remote sensing reflectance of the affected pixel and the discrimination standard, and compare the degree of deviation with the actual remote sensing reflectance of the breeding facility to calculate the breeding facility impact quantification factor of the breeding facility on the water body in the pasture area; the breeding facility impact quantification factor is calculated using the following formula: A=(R rs-in (X)-b) / R rs-buoy (X), Among them, A represents the quantitative factor of the impact of breeding facilities, R rs-in (X) represents the satellite specific band remote sensing reflectance of the affected pixels in the pasture area, R rs-buoy (X) represents the actual specific band remote sensing reflectivity of the aquaculture facility; The correction unit is used to calculate the impact degree of the breeding facilities on the water body in the pasture area using the breeding facility impact quantification factor, and correct the satellite remote sensing reflectivity of the water body according to the impact degree value to obtain the corrected satellite remote sensing reflectivity of the water body in the pasture area; the corrected water body remote sensing reflectivity in the pasture area is calculated using the following formula: R rs-corrected (λ)=R rs (l)-AR rs-buoy (l), Among them, λ represents the wavelength of the water in the pasture area, R rs-corrected (λ) represents the corrected satellite remote sensing reflectance of the water body in the pasture area, R rs (λ) represents the satellite remote sensing reflectance of the water body in the pasture area before correction, R rs-buoy (λ) represents the actual remote sensing reflectivity of the aquaculture facilities.

Images