Method, system, device and medium for retrieving sea surface wind speed

Abstract

The present application relates to providing a sea surface wind speed inversion method, system, device and medium. The method comprises: obtaining a sea surface glint area aerial image, atmospheric parameters, an observation angle corresponding to the aerial image, a shooting time, and latitude and longitude, and seawater material concentration data; radiometrically calibrating the aerial image to obtain sea surface reflection radiation intensity; inputting the shooting time, latitude and longitude, and atmospheric parameters into a radiation transfer model to obtain sea surface incident radiation intensity; inputting the seawater material concentration data and the observation angle into a seawater directional reflection model to obtain the sea surface wind speed based on the ratio of the sea surface reflection radiation intensity and the sea surface incident radiation intensity; wherein the seawater directional reflection model is the OCEABRDF model. In the calculation process, the radiation transfer physical process is strictly followed, and on the basis of accurately calculating the radiation contribution of each component of the seawater in the glint area, the quantitative inversion of the sea surface wind speed is realized.

Description

Technical Field

[0001] This invention relates to the field of sea surface wind speed calculation, and particularly to a method, system, device and medium for inverting sea surface wind speed. Background Technology

[0002] Sea surface winds are the primary driving force behind upper-layer seawater movement and a crucial medium for regulating water, vapor, and heat exchange between the sea and air, playing a pivotal role in regional and global climate change. Currently, the main methods for acquiring sea surface wind field information are conventional contact measurements and remote sensing. Conventional observations primarily utilize anemometers, wind vanes, and buoys for single-point measurements. These methods can only measure wind speed at the observation point, are easily affected by environmental factors, and present difficulties in deploying and retrieving buoys and other equipment. Furthermore, the acquired data lacks temporal and spatial continuity. With the rapid development of marine satellite remote sensing technology, the emergence of high spatiotemporal resolution marine satellite remote sensing technology has made it possible to observe global sea surface wind fields. In particular, the development of scatterometers, satellite altimeters, and synthetic aperture radar has enabled the acquisition of long-term and large-scale sea surface wind field data. However, satellite marine remote sensing technology also has certain limitations, such as the low resolution of scatterometers, difficulty in measuring sea surface wind field information in areas close to the coastline, and low resampling frequency, making continuous observation impossible. Furthermore, existing methods for acquiring wind speed typically rely on remote sensing images from ocean satellites. This involves acquiring multi-angle satellite data, extracting sea surface roughness, and then using the relationship between sea surface roughness and wind speed to retrieve the wind speed. However, this method, while dependent on satellite remote sensing data, suffers from long revisit times and lacks continuous observation capabilities. Secondly, it fails to consider the contributions of white-hat reflection and seawater reflectivity in the uplink radiation information from the sea surface, and ignores the impact of solar intensity variations on ocean flare roughness. This deviates from the quantitative requirements of remote sensing, relying solely on image-level wind speed retrieval. Since roughness information can be affected by factors such as camera performance, illumination intensity and angle, and imaging integration time, considerable errors are inevitably introduced. Therefore, a method, system, equipment, and medium for retrieving sea surface wind speed are needed. Summary of the Invention

[0003] This invention provides a method, system, device, and medium for retrieving sea surface wind speed, in order to solve the problem that existing technologies do not consider the quantitative aspect of radiation, but instead obtain wind speed based on the relative roughness of the image, resulting in inaccurate wind speed results.

[0004] The present invention provides a method for inverting sea surface wind speed, comprising: Aerial images of the sea surface glare area, atmospheric parameters, the observation angle, shooting time and latitude and longitude of the aerial images, and seawater substance concentration data were obtained. The intensity of reflected radiation from the sea surface was obtained from the aerial images obtained through radiometric calibration. The shooting time, latitude and longitude, and atmospheric parameters are input into the radiative transfer model to obtain the intensity of incident radiation on the sea surface; The seawater concentration data and observation angle are input into the seawater directional reflection model. Based on the ratio of the sea surface reflected radiation intensity to the sea surface incident radiation intensity, the sea surface wind speed is obtained by inversion. The seawater directional reflection model is the OCEABRDF model. In one embodiment of the present invention, the step of inputting the shooting time, latitude and longitude, and atmospheric parameters into the radiative transfer model to obtain the sea surface incident radiation intensity includes: The shooting time, latitude and longitude, and atmospheric parameters are input into the radiative transfer model to obtain solar downlink illuminance data and atmospheric downlink illuminance data; The solar downward illuminance data and the atmospheric downward illuminance data are added together, and the sum is taken as a unit directional angle to obtain the incident radiation intensity at the sea surface.

[0005] In one embodiment of the present invention, the step of inputting seawater substance concentration data and observation angle into a seawater direction reflection model, and obtaining sea surface wind speed based on the ratio of the sea surface reflected radiation intensity to the sea surface incident radiation intensity, includes: The ratio of the reflected radiation intensity to the incident radiation intensity is taken as the reflectivity of the sea surface; The seawater concentration data and observation angle are input into the seawater direction reflection model, and the sea surface wind speed is obtained by inversion based on the sea surface reflectivity.

[0006] In one embodiment of the present invention, the step of inputting seawater concentration data and observation angle into the seawater direction reflection model, and obtaining the sea surface wind speed based on the sea surface reflectivity, includes: Based on the preset effective reflectivity of marine foam and the area of ​​the white cap in seawater, the white cap reflectivity of seawater is obtained: ;in, wavelength The corresponding white cap reflectance, For the area of ​​the white hat, For the effective reflectivity of marine foam, The reflectance of a single white cap; The scattering reflectance of seawater is obtained based on seawater concentration data and observation angle; wherein, the observation angle includes the observation zenith angle and the observation azimuth angle. The reflectivity of the glare zone is obtained based on the observation angle and the sea surface roughness; wherein the reflectivity of the glare zone and the sea surface roughness are only variable factors of wind speed; The sea surface reflectance is obtained by adding the white cap reflectance, the scattered reflectance, and the glare zone reflectance with different weights: The sea surface wind speed is obtained through inversion; among them, The reflectivity of the sea surface, Let W be the reflectance of the white cap and W be the area of ​​the white cap. Reflectivity in the glare region This represents the scattering reflectivity.

[0007] In one embodiment of the present invention, the process of acquiring the solar irradiance data includes: Read the spectral channels corresponding to the aerial image; By integrating the preset downlink radiant intensity and corresponding spectral channel response function of each wavelength within the imaging band of the aerial image, the downlink solar illuminance data is obtained.

[0008] In one embodiment of the present invention, the radiometric calibration of the aerial image to obtain the intensity of reflected radiation from the sea surface includes: The aerial image is grayscale processed to obtain the pixel brightness values ​​of the grayscale processed aerial image; Based on a preset calibration coefficient, the pixel brightness value is converted into the sea surface reflected radiation intensity.

[0009] In one embodiment of the present invention, after radiometrically calibrating the aerial image to obtain the sea surface reflected radiation intensity, the method further includes: inputting the sea surface reflected radiation intensity into a hybrid pixel model to obtain the average sea surface radiation intensity.

[0010] In another aspect of the present invention, a sea surface wind speed inversion system is also provided, the system comprising: The data acquisition module is used to acquire aerial images of the sea surface glare area, atmospheric parameters, the observation angle, shooting time and latitude and longitude of the aerial images, as well as seawater substance concentration data; A radiometric calibration module is used to radiometrically calibrate the aerial images to obtain the intensity of radiation reflected from the sea surface. The incident radiation intensity acquisition module is used to input the shooting time, latitude and longitude and atmospheric parameters into the radiation transfer model to obtain the incident radiation intensity of the sea surface; The wind speed inversion module is used to input seawater material concentration data and observation angle into the seawater directional reflection model, and obtain the sea surface wind speed based on the ratio of the sea surface reflected radiation intensity to the sea surface incident radiation intensity; wherein, the seawater directional reflection model is the OCEABRDF model.

[0011] In one embodiment of the present invention, a sea surface wind speed inversion device is also provided, comprising one or more processors and a storage device, wherein the storage device is used to store one or more programs, and when the one or more programs are executed by the one or more processors, the electronic device enables the electronic device to implement any of the above-described sea surface wind speed inversion methods.

[0012] In one embodiment of the present invention, a computer-readable storage medium is also provided, on which a computer program is stored, which, when executed by a computer processor, causes the computer to perform the sea surface wind speed inversion method described in any of the preceding claims.

[0013] This invention proposes a method, system, equipment, and medium for inverting sea surface wind speed. Based on the OCEABRDF seawater directional reflection model in quantitative remote sensing, it strictly follows the physical process of radiative transfer during calculation. By accurately calculating the radiative contributions of each component of seawater in the glare zone, it achieves quantitative inversion of sea surface wind speed, thus obtaining a more accurate result. This solves the problem of inaccurate sea surface wind speed measurement in existing technologies. It fully considers the influence of different solar illumination conditions and the radiative contributions of other seawater components when inverting sea surface wind speed based on image roughness, improving the quantification of sea surface wind speed inversion. It has advantages such as simple operation, low measurement cost, high speed, and short revisit period. Attached Figure Description

[0014] Figure 1 The diagram shows a flowchart of a method for retrieving sea surface wind speed in one embodiment of the present invention. Figure 2 The diagram shows a flowchart of obtaining reflected radiation intensity in one embodiment of the present invention. Figure 3 This is a schematic diagram of the process for obtaining incident radiation intensity in one embodiment of the present invention; Figure 4 The diagram shows a flowchart of the process for acquiring solar downhill illuminance data in one embodiment of the present invention. Figure 5 The diagram shows a process for obtaining sea surface wind speed inversion in one embodiment of the present invention. Figure 6 The image shows the global chlorophyll concentration distribution in water bodies in December 2022, based on MODIS data. Figure 7 The image shown is a diagram from a sea surface measurement experiment. Figure 8 The image shows an aerial view of the shimmering area on the sea surface. Figure 9 This is a diagram showing the comparison between the retrieved wind speed and the wind speed measured by the handheld weather station. Figure 10This is a structural block diagram of a sea surface wind speed inversion system provided in an embodiment of the present invention. Detailed Implementation

[0015] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, unless otherwise specified, the following embodiments and features described therein can be combined with each other.

[0016] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0017] In the following description, numerous details are explored to provide a more thorough explanation of embodiments of the invention. However, it will be apparent to those skilled in the art that embodiments of the invention may be practiced without these specific details. In other embodiments, well-known structures and devices are shown in block diagram form rather than in detail to avoid obscuring embodiments of the invention.

[0018] This invention provides a method for inverting sea surface wind speed, offering a convenient, fast, low-cost, and highly applicable method. This method strictly follows the radiative transfer process, utilizing the OCEABRDF model within the 6S radiative transfer model to quantitatively invert the real-time wind speed in the sea surface glare zone, based on the relationship between sea surface reflectivity and sea surface wind speed. This effectively solves the problems of complex operation and high cost associated with traditional control point measurement methods, as well as the low detector accuracy and long revisit cycles in marine satellite remote sensing methods, providing a new solution for sea surface wind speed measurement. Please see Figure 1 The method for retrieving sea surface wind speed includes the following steps: S1. Acquire aerial images of the sea surface glare area, atmospheric parameters, the observation angle corresponding to the aerial images, the shooting time and latitude and longitude, and seawater substance concentration data.

[0019] Solar flares are direct reflections of sunlight from the sea surface. In marine optical remote sensing, because the intensity of the reflected sunlight is so high, it completely obscures the radiation information of ground targets, which is considered a serious data loss. However, on the other hand, solar flares also contain rich information on sea surface roughness, and the roughness of the sea surface is directly related to the wind speed at sea. This makes it possible to use solar flare data to infer sea surface wind speed.

[0020] Please see Figure 6 In one embodiment of the present invention, the seawater substance concentration includes salinity data of the sea area where the wind speed is to be measured, and chlorophyll concentration data. These two parts of data are basic characteristics of seawater, which are values ​​that change slowly over time, usually with a seasonal cycle. Specific values ​​can be obtained from the Argo website and MODIS chlorophyll concentration products, respectively.

[0021] By setting up a CE318 solar radiometer on flat, unobstructed land near the sea, atmospheric parameters are acquired at the moment of aerial imaging. These atmospheric parameters are then used to calculate the radiative energy received by the sea surface at the time of imaging. The sampling interval of the solar radiometer can be preset, allowing the instrument to automatically acquire atmospheric parameters according to the preset interval, thus enabling long-term, uninterrupted field acquisition of atmospheric parameters without the need for additional operations.

[0022] Furthermore, considering that existing conventional methods for observing sea surface wind speed typically use anemometers, wind vanes, buoys, ships, and coastal stations, these methods are primarily single-point measurements, thus only obtaining wind field information at the observation point, resulting in very limited sea surface wind field data. Moreover, these measurement methods are easily affected by the external environment, the deployment and retrieval of buoys and other equipment are difficult, and the measurement results suffer from uneven distribution in time and space, lack of continuity, and inability to meet the needs of wind speed calculation. Therefore, this invention uses a conventional camera via a drone platform to acquire image data of the sea surface glare area as aerial photography data. The drone platform, equipped with an imaging camera, GPS, and gyroscope, selects the solar glare angle to photograph the sea surface, while the GPS and gyroscope record the latitude and longitude information and camera attitude data at the time of imaging. Based on the time and GPS information, the shooting time and latitude and longitude can be obtained, thereby calculating the solar zenith angle θ at the time of imaging. s And solar azimuth φ s The observed zenith angle θ was calculated using GPS and gyroscope information. v and the observed azimuth angle φ vThe observed zenith angle and observed azimuth angle are the observed angles. Compared with traditional methods that rely on anemometers, wind vanes, buoys, and ships to measure sea surface wind speed, this invention does not require specialized wind speed measurement equipment, nor does it require using a ship platform to sail to the corresponding sea area for wind speed measurement or deploying buoys in the corresponding sea area. It only requires a single radiometric calibration of the camera, and then using a UAV equipped with the calibrated camera, GPS, and gyroscope to acquire images of the sea surface glare area while simultaneously obtaining imaging attitude and position information, thus completing the inversion calculation of sea surface wind speed. S2. Radiometric calibration of the aerial images to obtain the intensity of reflected radiation from the sea surface.

[0023] Since this invention uses images of sea surface glare zones taken by a drone to retrieve wind speed, the imaging equipment and auxiliary equipment carried by the drone must first be prepared and their parameters calibrated. This includes radiometric calibration of the imaging payload and acquisition of its spectral response function. By radiometrically calibrating the imaging payload, the photoelectric signals of the aerial images acquired by the payload are converted into absolute physical quantities, providing data support for subsequent calculations of sea surface reflectivity.

[0024] Please see Figure 2 Specifically, in one embodiment of the present invention, step S2, which involves radiometrically calibrating the aerial image to obtain the sea surface reflected radiation intensity, includes: S21. Perform grayscale processing on the aerial image to obtain the pixel brightness values ​​of the grayscale processed aerial image. S22. Based on a preset calibration coefficient, the pixel brightness value is converted into the sea surface reflected radiation intensity.

[0025] Radiometric calibration converts the raw DN values ​​of aerial images recorded by the camera into absolute radiance. DN (Digital Number) values ​​are pixel brightness values, recording the grayscale values ​​of ground features, i.e., the digital measurements obtained by the sensor. Pixel brightness values ​​are unitless (non-physical quantities), are integers, and their magnitude is related to the sensor's radiometric resolution, ground feature emission frequency, atmospheric transmittance, and scattering rate, reflecting the emissivity of the ground feature. Pixel brightness values ​​can be obtained by grayscale processing of aerial images, and the corresponding band of sea surface reflected radiation intensity can be obtained using formula (1): *DN+c(1) Where k and c are the preset gain and offset, respectively, and DN is the DN value of the aerial image. For band The radiance value is used as the sea surface reflected radiation intensity for that band.

[0026] In one embodiment of the present invention, after radiometrically calibrating the aerial image to obtain the sea surface reflected radiation intensity, the method further includes: inputting the sea surface reflected radiation intensity into a hybrid pixel model to obtain the average sea surface radiation intensity. Specifically, after radiometrically calibrating the image of the sea surface flare area captured by the camera, a quantitative sea surface radiation intensity image is obtained. The image of the flare center area is then pixel-blended, and finally only the value of one pixel is retained to replace the average radiation intensity information of the entire area. This pixel value is used as the reflected radiation intensity of the current sea surface in the corresponding band. This is then used for subsequent calculation of the equivalent reflectivity of the sea surface.

[0027] S3. Input the shooting time, latitude and longitude, and atmospheric parameters into the radiative transfer model to obtain the incident radiation intensity at the sea surface.

[0028] Based on the GPS data on the drone, latitude and longitude data are obtained. The shooting time of the aerial image, latitude and longitude data, and synchronous atmospheric parameters measured by CE318 in step S1 are input into the 6S radiative transfer model. The intensity of the incident radiation on the sea surface is obtained by using the spectral response function of the current shooting band preset in the camera.

[0029] Please see Figure 3 Specifically, in one embodiment of the present invention, step S3, which involves inputting aerial images, observation angles, and atmospheric parameters into a radiative transfer model to obtain the sea surface incident radiation intensity, includes: S31. Input the shooting time, latitude and longitude, and atmospheric parameters into the radiative transfer model to obtain solar downlink illuminance data and atmospheric downlink illuminance data; S32. Add the solar downward illuminance data and the atmospheric downward illuminance data, and take the sum as a unit directional angle to obtain the sea surface incident radiation intensity.

[0030] Since the downward radiation intensity received by the sea surface includes not only the direct solar radiation intensity but also the downward atmospheric scattering intensity within the hemispherical space, calculating the total incident radiation intensity at the sea surface requires adding the solar downward illuminance data and the atmospheric downward illuminance data, and then taking the value per unit azimuth angle as the sea surface incident radiation intensity. Both the solar downward illuminance data and the atmospheric downward illuminance data can be obtained using a radiative transfer model.

[0031] Please see Figure 4 In one embodiment of the present invention, the process of acquiring the solar irradiance data includes: S311. Read the spectral channel corresponding to the aerial image; S312. Integrate the preset downlink radiation intensity and corresponding spectral channel response function of each wavelength in the imaging band of the aerial image to obtain the downlink solar illuminance data.

[0032] Specifically, considering that each camera responds differently to radiant energy at different wavelengths, the downlink radiant energy calculated using the radiative transfer model is distributed across the entire spectrum. However, our camera can only image certain bands, and even within the same band, the response to different wavelengths varies. Only by obtaining the spectral response function of each band of the camera and integrating the downlink radiant intensity at each wavelength within the camera's imaging band with the corresponding spectral response function can we calculate the solar downlink illuminance data within the corresponding band. Based on this solar downlink illuminance data, we can then calculate the equivalent reflectance data of the sea surface within the corresponding band.

[0033] S4. Input the seawater material concentration data and the observation angle into the seawater directional reflection model, and obtain the sea surface wind speed based on the ratio of the sea surface reflected radiation intensity to the sea surface incident radiation intensity; wherein, the seawater directional reflection model is the OCEABRDF model.

[0034] The OCEABRDF model is a two-way reflectance distribution model for ocean systems. It describes the reflectance composition of seawater, and under low resolution conditions, within the solar spectrum, for a given set of geometric conditions and a solar zenith angle θ. s Observe the zenith angle θ v and relative azimuth angle φ (=φ s -φ v According to the OCEABRDF model, the sea surface reflectivity corresponding to band λ can be obtained. The sea surface reflectance can be summarized as the white cap reflectance. The reflectivity of the glare zone on the sea surface and the scattering reflectance in seawater The three parts are multiplied by their respective weights, as shown in formula (2): (2) Where W is the area of ​​the white cap, which can be calculated from the wind speed. ws represents wind speed in m / s.

[0035] Specifically, in one embodiment of the present invention, step S4, which involves inputting seawater substance concentration data and observation angle into a seawater direction reflection model, and obtaining sea surface wind speed based on the ratio of the sea surface reflected radiation intensity to the sea surface incident radiation intensity, includes: S41. The ratio of the reflected radiation intensity to the incident radiation intensity is taken as the reflectivity of the sea surface; S42. Input the seawater concentration data and observation angle into the seawater direction reflection model, and obtain the sea surface wind speed based on the sea surface reflectivity.

[0036] Since the sea surface reflectance obtained by the OCEABRDF model includes scattered reflectance, glare reflectance, and white cap reflectance, and the scattered reflectance is independent of wind speed, it can be calculated using other parameters. However, the white cap reflectance and glare reflectance are only related to wind speed. Therefore, the sea surface reflectance obtained by the OCEABRDF model is essentially only related to wind speed. Both the reflected radiation intensity and the incident radiation intensity are measurable data. Therefore, dividing the reflected radiation intensity obtained in step S2 by the incident radiation intensity obtained in step S3 yields the reflectance of the equivalent band of the sea surface. The sea surface reflectance can then be uniquely determined based on the measured parameters. Equating the sea surface reflectance with the result output by the OCEABRDF model, since only the wind speed is unknown in the entire calculation process, the sea surface wind speed can be obtained by inversion using formula (2).

[0037] Please see Figure 5 In one embodiment of the present invention, step S42, which involves inputting seawater concentration data and observation angle into the seawater direction reflection model, and obtaining the sea surface wind speed based on the sea surface reflectivity, includes: S421. Based on the preset effective reflectivity of marine foam and the area of ​​the white cap in seawater, obtain the white cap reflectivity of seawater: ;in, wavelength The corresponding white cap reflectance, For the area of ​​the white hat, For the effective reflectivity of marine foam, The reflectance of a single white cap; S422. Obtain the scattering reflectance of seawater based on seawater substance concentration data and observation angle; wherein, the observation angle includes the observation zenith angle and the observation azimuth angle; S423. Based on the observation angle and sea surface roughness, obtain the reflectivity of the glare area; wherein, the reflectivity of the glare area and the sea surface roughness are only variable factors of wind speed; S424. Add the white cap reflectivity, the scattered reflectivity, and the glare area reflectivity with different weights. The sea surface wind speed is obtained through inversion; among them, The reflectivity of the sea surface, Let W be the reflectance of the white cap and W be the area of ​​the white cap. Reflectivity in the glare region This represents the scattering reflectivity.

[0038] For the white cap reflectance of seawater, since the total reflectance of the white cap can be expressed as the area W of each white cap and the corresponding reflectance... ρ f ( λThe product of W and W is given. However, the area of ​​a single white hat increases with time, while its reflectivity decreases accordingly. Since the value of W considers white hats at different time periods, it is derived from W and W. ρ f ( λ The given band λ Corresponding white cap reflectance The value is too high. Therefore, the effective reflectivity of marine foam is introduced. The concept of replacing ρ f ( λ ). and will The expression is defined as shown in formula (3): (3) in, f ef =0.4 is an efficiency coefficient that is slightly related to wind speed but independent of wavelength. By incorporating the effective reflectivity of ocean foam, the calculation results of the white cap reflectivity of seawater can be made more accurate.

[0039] Regarding the scattering reflectance of seawater, due to the scattering reflectance in seawater... This portion of the reflectance is equivalent to the reflectance observed directly above the sea surface, and is the equivalent reflectance of the outgoing radiation from the seawater. This portion of the reflectance is related to the ratio R of the upward and downward radiation in the seawater. W Related. Assuming the sea surface is a Lambertian surface, the scattering reflectivity of seawater can be expressed as shown in formula (4): (4) Where n is the complex refractive index of seawater, which is related to the salinity of seawater, and a is a preset constant. The downward radiation transmittance at the air-water interface. The upward radiation transmittance of the water-air interface.

[0040] Specifically, the downward radiation transmittance at the air-water interface is calculated using the Fresnel reflectance coefficient. The result is shown in formula (5): (5) The upward radiation transmittance of the water-air interface can also be expressed using the Fresnel reflectance coefficient. The result is shown in formula (6): (6) R W(λ) This represents the ratio of upward radiation to downward radiation below the water surface. This ratio depends on the optical properties of seawater, specifically the total absorption coefficient a(λ) and the total backscattering coefficient b. b(λ)When a(λ) << 1, R W(λ) It can be approximated as shown in formula (7): (7) Furthermore, the optical properties of seawater, namely its absorption and backscattering coefficients, are usually also affected by phytoplankton and dissolved organic matter. Water bodies whose optical properties are primarily determined by phytoplankton and their byproducts are called Class I water; water bodies whose optical properties are affected not only by phytoplankton and their byproducts but also by other substances such as exogenous particles and dissolved organic matter are called Class II water. Here we only consider the case of Class I water. For Class I water, Morel (1988) decomposed the backscattering coefficient of the water body into two components, as shown in formula (8): (8) Among them, b W(λ) This represents the molecular scattering coefficient of water, which can be obtained through a lookup; b is the scattering coefficient of seawater. The ratio of the backscattering coefficient to the scattering coefficient of a water body, b and It can be obtained through calculation. Specifically, Determined by the chlorophyll concentration C and wavelength of seawater, it is expressed as shown in formula (9): (9) The scattering coefficient b of seawater is calculated as shown in formula (10): (10) The total absorption coefficient of Class I water bodies is expressed as shown in formula (11): (11) Among them, K d (λ) is the total scattering coefficient of downward radiation in the water body, which can be expressed as shown in formula (12): (12) Among them, K W (λ) represents the attenuation coefficient of pure seawater. It is a wavelength-dependent empirical parameter.

[0041] In formula (11), u(λ) is a wavelength correlation function, expressed as shown in formula (13): (13) R can be obtained from formulas (8) to (13). W(λ) The value of is then combined with formulas (5) to (6) to obtain the scattering reflectance of seawater described in formula (4).

[0042] For reflectivity in the glare zone Cox and Munk measured the surface using aerial photography, defining a multifaceted model whose wave slope varies anisotropically with changes in surface wind. We assume a coordinate system (P; X, Y, Z), where P is the observation position, Z is the sea surface height, PY represents the direction pointing towards the sun, and PX represents the direction perpendicular to the solar plane. In this coordinate system, the sea surface slope is determined by Z... X and Z Y The two components are defined as shown in formulas (13) and (14): (13) (14) Where α is the slope azimuth angle and β is the slope inclination angle, the above Z can be expressed using a spherical coordinate system. X Z Y Expressed as quantities related to the incident and exit directions, as shown in formulas (15) and (16): (15) (16) Where, θ s For the solar zenith angle, θ v To observe the zenith angle, φ s For the solar azimuth angle, φ v For the observation azimuth angle. For the anisotropic distribution of sea surface slope caused by wind speed, we consider redefining a coordinate system (P;X',Y',Z'=Z), which is obtained by rotating the original coordinate system clockwise according to the relative azimuth angle of the sun and the observation azimuth. Then the components of sea surface slope can be transformed from formulas (15) and (16) into formulas (17) and (18): (17) (18) The slope distribution of sea surface gradient can be expressed by the Gram-Charlier series as shown in formula (19): (19) in, , They are respectively The surface roughness of the ocean surface. The skewness coefficients C21 and C03 and the peak coefficients C40, C22 and C04 are defined as shown in formula (20): (20) The reflectivity of the glare zone on the sea surface can be expressed as shown in formula (21): (twenty one) Where R(n,θ) s ,θ v ,φ s ,φ v ) is the Fresnel reflection coefficient, and n is the complex refractive index of seawater.

[0043] Please see Figures 7 to 9 Based on the above inversion method, a maritime flight verification experiment was conducted in December 2022 along the coast of Huizhou, Guangdong. The sea surface wind speed was obtained using the data acquired in the experiment and compared with the real-time wind speed measured by the handheld weather station on the target ship, as shown in the table below: Table 1. Experimental data for sea surface wind speed retrieval verification image time latitude longitude Solar zenith angle Sun azimuth Measured wind speed Inverted wind speed ColorCam-1999us-20221209-14-06-49-005 14:06:49 22.5734628 114.8616721 53.13 213.15 4.5 3.9 ColorCam-1999us-20221209-13-59-05-413 13:59:05 22.5725363 114.8640435 52.18 211.26 3.62 4.1 ColorCam-1999us-20221209-14-07-36-557 14:07:36 22.5748236 114.8697605 53.24 213.35 2.3 2.5 ColorCam-1999us-20221209-14-10-11-710 14:10:11 22.5739873 114.8616696 53.56 213.96 5.97 5.2 ColorCam-1999us-20221209-14-20-05-840 14:20:05 22.5587819 114.8786685 54.87 216.28 2.15 2.6 ColorCam-1999us-20221209-14-21-01-126 14:21:01 22.5594233 114.8764511 55.01 216.49 2.44 2.6 ColorCam-1999us-20221209-14-29-36-239 14:29:36 22.5778178 114.864948 56.22 218.37 2.59 3.1 ColorCam-1999us-20221209-15-26-04-023 15:26:03 22.5742653 114.8625288 65.25 229.11 2.81 2.7 Actual measurement data shows that the wind speed inversion method described in this invention yields wind speed values ​​that are very close to the actual wind speeds. Figure 8 The aerial images in the image represent images taken at different integration times and shooting times. Figure 9 In this invention, SSE represents the sum of squared errors, RMSE represents the root mean square error, and R-squared represents the coefficient of determination. This invention addresses the shortcomings of existing methods for acquiring wind speed using remote sensing images. For example, the low resolution of scatterometers makes it difficult to measure sea surface wind field information in areas close to the coastline; the low resampling rate of satellite remote sensing prevents continuous observation of the same sea area, thus hindering the acquisition of continuous image data; and there are also drawbacks such as poor real-time performance and low spatiotemporal resolution of satellite marine remote sensing images. This invention considers that methods for measuring sea surface wind speed using satellite remote sensing technology suffer from the low resolution of scatterometers, making it difficult to accurately acquire wind field information in the coastal zone. Since major human maritime activities are concentrated in coastal areas, accurate measurement of wind field information in these areas is crucial to the production and lives of coastal residents. This invention utilizes unmanned aerial vehicles (UAVs) or manned aircraft platforms, relying on atmospheric measurement information from these platforms and ground observation stations. Therefore, it cannot measure wind speed in deep-sea areas independently of land, thus filling the gaps in satellite remote sensing measurement methods. Compared with satellite remote sensing, this method has the advantages of low cost, short cycle, easy operation, high timeliness and high resolution.

[0044] Furthermore, addressing the shortcomings of current sea surface wind speed measurement methods, such as the susceptibility of conventional methods to environmental influences, difficulties in deploying and recovering buoys and other equipment, and the lack of temporal and spatial continuity in the acquired data; and the limitations of satellite ocean remote sensing methods, such as low scatterometer resolution, difficulty in measuring sea surface wind field information in areas close to the coastline, and low resampling frequency, which prevents continuous observation, this invention proposes a wind speed inversion method. This method uses image data of sea surface glare areas acquired by an unmanned aerial vehicle (UAV) platform to invert sea surface wind speed. This method has advantages such as simple operation, low measurement cost, high speed, and short revisit period.

[0045] Furthermore, the inventors noted that with the rapid development of oceanography and satellite technology, some methods have been developed to retrieve sea surface wind speed using multi-angle images from ocean satellites. These methods currently rely on multi-angle satellite data to extract sea surface roughness, and then use the relationship between sea surface roughness and wind speed to retrieve sea surface wind speed. This method, on the one hand, depends on satellite remote sensing data, which also suffers from long revisit times and discontinuous observation. On the other hand, it does not consider the contribution of white-cap reflection and seawater's own reflectivity in the uplink radiation information of the sea surface, and ignores the influence of changes in solar intensity on ocean flare roughness, thus deviating from the quantitative requirements of remote sensing. Retrieving sea surface wind speed solely from the image level inevitably introduces considerable errors. This invention, based on the description of the OCEABRDF model in the 6S radiative transfer model, separates the component information of sea surface reflectivity, combines publicly available data on seawater chlorophyll and salinity, subtracts the scattering reflection and white-cap reflection of the sea surface flare area, and extracts the sea surface flare intensity information from the image. Based on the established relationship between the tilted wavefront probability and the sea surface wind field, as well as the relationship between solar flare intensity and the sea surface wavefront tilt probability distribution, the real-time sea surface wind speed in the image-covered area is quantitatively calculated using radiometrically calibrated images of the sea surface flare zone and a radiative transfer model.

[0046] Please see Figure 10The present invention also provides a sea surface wind speed inversion system. The sea surface wind speed inversion system 100 includes: a data acquisition module 110, a radiometric calibration module 120, an incident radiation intensity acquisition module 130, and a wind speed inversion module 140. The data acquisition module 110 is used to acquire aerial images of the sea surface glare area, atmospheric parameters, the observation angle corresponding to the aerial image, the shooting time and latitude / longitude, and seawater substance concentration data. The radiometric calibration module 120 is used to radiometrically calibrate the aerial image to obtain the sea surface reflected radiation intensity. The incident radiation intensity acquisition module 130 is used to input the shooting time, latitude / longitude, and atmospheric parameters into a radiative transfer model to obtain the sea surface incident radiation intensity. The wind speed inversion module 140 is used to input the seawater substance concentration data and the observation angle into a seawater directional reflection model, and invert the sea surface wind speed based on the ratio of the sea surface reflected radiation intensity to the sea surface incident radiation intensity; wherein, the seawater directional reflection model is the OCEABRDF model.

[0047] It should be noted that, in order to highlight the innovative aspects of this invention, this embodiment does not include modules that are not closely related to solving the technical problems proposed by this invention, but this does not mean that there are no other modules in this embodiment.

[0048] Furthermore, those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the system described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here. In the embodiments provided by this invention, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for example, the division of modules is merely a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0049] The modules described as separate components may or may not be physically separate. Similarly, the components shown as modules may or may not be physical modules; they may be located in one place or distributed across multiple network modules. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0050] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated modules described above can be implemented in hardware or as software functional units.

[0051] This embodiment also proposes an electronic device, which includes a processor and a memory coupled together. The memory stores program instructions, and when the program instructions stored in the memory are executed by the processor, the aforementioned method for inverting sea surface wind speed is implemented. The processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The memory may include random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage device. The memory can be an internal memory of the random access memory (RAM) type. The processor and memory can be integrated into one or more independent circuits or hardware, such as an application-specific integrated circuit (ASIC). It should be noted that when the computer program in the aforementioned memory is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, an electronic device, or a network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention.

[0052] This embodiment also proposes a computer-readable storage medium storing computer instructions for instructing a computer to execute the aforementioned method for retrieving sea surface wind speed. The storage medium can be an electronic medium, magnetic medium, optical medium, electromagnetic medium, infrared medium, or a semiconductor system or propagation medium. The storage medium may also include semiconductor or solid-state memory, magnetic tape, removable computer disk, random access memory (RAM), read-only memory (ROM), hard disk, and optical disc. Optical discs may include optical disc-read-only memory (CD-ROM), optical disc-read / write (CD-RW), and DVD.

[0053] In summary, the present invention discloses a method, system, device, and medium for inverting sea surface wind speed. Based on the OCEABRDF seawater directional reflection model in quantitative remote sensing, it strictly follows the physical process of radiative transfer during calculation. By accurately calculating the radiative contributions of each component of seawater in the glare zone, it achieves quantitative inversion of sea surface wind speed. It fully considers the influence of different solar illumination conditions and the radiative contributions of other seawater components when inverting sea surface wind speed based on image roughness, thus improving the quantification of sea surface wind speed inversion. It has advantages such as simple operation, low measurement cost, high speed, and short revisit period. The concept of inverting sea surface wind speed using absolute radiative intensity information is proposed for the first time. Therefore, this invention effectively overcomes the various shortcomings of existing technologies and has high industrial application value.

[0054] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. A method for inverting sea surface wind speed, characterized in that, The method includes: Aerial images of the sea surface glare area, atmospheric parameters, the observation angle, shooting time and latitude and longitude of the aerial images, and seawater substance concentration data were obtained. The intensity of reflected radiation from the sea surface was obtained from the aerial images obtained through radiometric calibration. The shooting time, latitude and longitude, and atmospheric parameters are input into the radiative transfer model to obtain the intensity of incident radiation on the sea surface; The seawater concentration data and observation angle are input into the seawater directional reflection model. Based on the ratio of the sea surface reflected radiation intensity to the sea surface incident radiation intensity, the sea surface wind speed is obtained by inversion. The seawater directional reflection model is the OCEABRDF model.

2. The method for inverting sea surface wind speed according to claim 1, characterized in that, The process of inputting the shooting time, latitude and longitude, and atmospheric parameters into the radiative transfer model to obtain the sea surface incident radiation intensity includes: The shooting time, latitude and longitude, and atmospheric parameters are input into the radiative transfer model to obtain solar downlink illuminance data and atmospheric downlink illuminance data; The solar downward illuminance data and the atmospheric downward illuminance data are added together, and the sum is taken as a unit directional angle to obtain the incident radiation intensity at the sea surface.

3. The method for inverting sea surface wind speed according to claim 1, characterized in that, The process of inputting seawater substance concentration data and observation angle into the seawater direction reflection model, and obtaining sea surface wind speed based on the ratio of the sea surface reflected radiation intensity to the sea surface incident radiation intensity, includes: The ratio of the reflected radiation intensity to the incident radiation intensity is taken as the reflectivity of the sea surface; The seawater concentration data and observation angle are input into the seawater direction reflection model, and the sea surface wind speed is obtained by inversion based on the sea surface reflectivity.

4. The method for inverting sea surface wind speed according to claim 3, characterized in that, The process of inputting seawater concentration data and observation angle into the seawater direction reflection model, and obtaining sea surface wind speed based on the sea surface reflectivity, includes: Based on the preset effective reflectivity of marine foam and the area of ​​the white cap in seawater, the white cap reflectivity of seawater is obtained: ;in, wavelength The corresponding white cap reflectance, For the area of ​​the white hat, For the effective reflectivity of marine foam, The reflectance of a single white cap; The scattering reflectance of seawater is obtained based on seawater concentration data and observation angle; wherein, the observation angle includes the observation zenith angle and the observation azimuth angle. The reflectivity of the glare zone is obtained based on the observation angle and the sea surface roughness; wherein the reflectivity of the glare zone and the sea surface roughness are only variable factors of wind speed; The white cap reflectivity, the scattered reflectivity, and the glare zone reflectivity are added together with different weights: The sea surface wind speed is obtained through inversion; among them, The reflectivity of the sea surface, Let W be the reflectance of the white cap and W be the area of ​​the white cap. Reflectivity in the glare zone This represents the scattering reflectivity.

5. The method for inverting sea surface wind speed according to claim 2, characterized in that, The process of acquiring the solar irradiance data includes: Read the spectral channels corresponding to the aerial image; By integrating the preset downlink radiant intensity and corresponding spectral channel response function of each wavelength within the imaging band of the aerial image, the downlink solar illuminance data is obtained.

6. The method for inverting sea surface wind speed according to claim 1, characterized in that, The radiometric calibration of the aerial images to obtain the intensity of reflected radiation from the sea surface includes: The aerial image is grayscale processed to obtain the pixel brightness values ​​of the grayscale processed aerial image; Based on a preset calibration coefficient, the pixel brightness value is converted into the sea surface reflected radiation intensity.

7. The method for inverting sea surface wind speed according to claim 1, characterized in that, After radiometrically calibrating the aerial image to obtain the sea surface reflected radiation intensity, the method further includes: inputting the sea surface reflected radiation intensity into a hybrid pixel model to obtain the average sea surface radiation intensity.

8. A sea surface wind speed inversion system, characterized in that, The system includes: The data acquisition module is used to acquire aerial images of the sea surface glare area, atmospheric parameters, the observation angle, shooting time and latitude and longitude of the aerial images, as well as seawater substance concentration data; A radiometric calibration module is used to radiometrically calibrate the aerial images to obtain the intensity of radiation reflected from the sea surface. The incident radiation intensity acquisition module is used to input the shooting time, latitude and longitude and atmospheric parameters into the radiation transfer model to obtain the incident radiation intensity of the sea surface; The wind speed inversion module is used to input seawater material concentration data and observation angle into the seawater directional reflection model, and obtain the sea surface wind speed based on the ratio of the sea surface reflected radiation intensity to the sea surface incident radiation intensity; wherein, the seawater directional reflection model is the OCEABRDF model.

9. A device for retrieving sea surface wind speed, characterized in that: One or more processors; A storage device for storing one or more programs, which, when executed by one or more processors, cause an electronic device to implement the sea surface wind speed inversion method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: It stores a computer program that, when executed by the computer's processor, causes the computer to perform the method for retrieving sea surface wind speed as described in any one of claims 1 to 7.

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