Marine environment optical characteristic inversion method and device based on multi-source satellite remote sensing data

Abstract

The invention provides a marine environment optical characteristic inversion method and device based on multi-source satellite remote sensing data. The method comprises the following steps: respectively acquiring various marine environment characteristic parameters based on various satellite remote sensing data; according to the data characteristics of each marine environment characteristic parameter, a corresponding method is selected to pre-process each marine environment characteristic parameter, and a space-time complete environment element database is obtained; extracting various marine environment characteristic parameters at specified positions and time from the space-time complete environment element database, inputting the various marine environment characteristic parameters and satellite detection parameters into a pre-constructed marine environment optical characteristic calculation model, and performing inversion to obtain marine environment optical characteristics under specified space-time conditions; wherein the marine environment optical characteristic calculation model comprises a marine atmospheric transmittance model, a marine atmospheric path radiance model and a sea surface background radiance model. According to the scheme, the real optical characteristic change data representation of the open-sea far-field marine environment can be realized.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of environmental optical characteristics, and in particular to a method and device for inverting the optical characteristics of an ocean environment based on multi-source satellite remote sensing data. Background Art

[0002] The optical characteristics of the ocean environment include parameters such as atmospheric transmittance, atmospheric path radiation, atmospheric background radiation, and sea surface background radiation that affect the detection of optical sensors in the ocean environment. These characteristic parameters will change significantly with the spectrum, detection angle, detection altitude, longitude and latitude, and time. The changes in longitude and latitude and time will change the atmospheric and ocean environmental elements and the incident solar radiation, thereby affecting the optical characteristics of the ocean environment.

[0003] Satellites equipped with photoelectric detection payloads can periodically obtain radiation information from most sea areas, and have advantages that cannot be replaced by ground-based and shipborne measurements. However, due to differences in detection spectrum, detection altitude, and detection angle, data directly obtained by satellite remote sensing cannot represent the optical properties of the ocean environment required for practical applications, such as the brightness of the medium and long-wave sea surface background radiation and the atmospheric background radiation when approaching the sea surface at close range. In addition, factors such as cloud pollution and long satellite revisit periods will also result in no effective satellite remote sensing data to support the acquisition of optical properties at the desired time and location. In principle, the optical property model of the ocean environment can generate property data for any specified spectrum, specified altitude, and specified angle, but in the absence of real environmental element input, typical calculated data cannot represent the actual changes in the optical properties of the ocean environment.

[0004] Therefore, there is an urgent need to provide a method and device for inverting the optical characteristics of the ocean environment based on multi-source satellite remote sensing data. Summary of the invention

[0005] In order to solve the problem that the traditional ocean environment optical property model cannot represent the actual changes in the ocean environment optical property, the embodiment of the present invention provides an ocean environment optical property inversion method and device based on multi-source satellite remote sensing data.

[0006] In a first aspect, an embodiment of the present invention provides a method for inverting optical properties of an ocean environment based on multi-source satellite remote sensing data, the method comprising:

[0007] Based on a variety of satellite remote sensing data, a variety of ocean environment characteristic parameters are obtained respectively; wherein the ocean environment characteristic parameters include atmospheric temperature profile, atmospheric humidity profile, aerosol optical thickness, cloud optical parameters, ocean surface temperature, sea surface wind speed and wind direction;

[0008] According to the data characteristics of each marine environmental characteristic parameter, the corresponding method is selected to pre-process each marine environmental characteristic parameter to obtain a spatiotemporal complete environmental element database;

[0009] A variety of ocean environment characteristic parameters at specified locations and times are extracted from the complete spatiotemporal environmental element database, and are input together with satellite detection parameters into a pre-constructed ocean environment optical characteristic calculation model to invert the ocean environment optical characteristics under specified spatiotemporal conditions; wherein the ocean environment optical characteristic calculation model includes an ocean atmosphere transmittance model, an ocean atmosphere path radiation brightness model, and a sea surface background radiation brightness model.

[0010] In a second aspect, an embodiment of the present invention further provides a device for inverting optical characteristics of an ocean environment based on multi-source satellite remote sensing data, the device comprising:

[0011] An acquisition unit is used to acquire a plurality of ocean environment characteristic parameters based on a plurality of satellite remote sensing data; wherein the ocean environment characteristic parameters include atmospheric temperature profile, atmospheric humidity profile, aerosol optical thickness, cloud optical parameters, ocean surface temperature, sea surface wind speed and wind direction;

[0012] A preprocessing unit is used to select a corresponding method to preprocess each marine environment characteristic parameter according to the data characteristics of each marine environment characteristic parameter, so as to obtain a spatiotemporal complete environmental element database;

[0013] The inversion unit is used to extract a variety of ocean environment characteristic parameters at a specified location and time from the complete spatiotemporal environmental element database, and input them together with satellite detection parameters into a pre-constructed ocean environment optical characteristic calculation model to invert the ocean environment optical characteristics under the specified spatiotemporal conditions; wherein the ocean environment optical characteristic calculation model includes an ocean atmosphere transmittance model, an ocean atmosphere path radiation brightness model and a sea surface background radiation brightness model.

[0014] In a third aspect, an embodiment of the present invention further provides a computing device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method described in any embodiment of this specification is implemented.

[0015] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, enables the computer to execute the method described in any embodiment of this specification.

[0016] On the other hand, an embodiment of the present application further provides a computer program product, which includes a computer program. A processor of a computer device reads the computer program from a computer-readable storage medium, and the processor executes the computer program, so that the computer device executes any of the methods described in the above embodiments.

[0017] The embodiment of the present invention provides a method and device for inverting the optical characteristics of an ocean environment based on multi-source satellite remote sensing data. First, multiple ocean environment characteristic parameters are obtained based on the original data inversion of satellite remote sensing data. For the multiple original ocean environment characteristic parameters, combined with the data characteristics of each ocean environment characteristic parameter, a corresponding method is selected to pre-process each ocean environment characteristic parameter to complete the large-area missing of the original data caused by cloud pollution and improve the spatiotemporal resolution, so as to form a spatiotemporal complete environmental element database; then, an ocean environment optical characteristic calculation model based on these obtainable ocean environment characteristic parameters is constructed; a plurality of ocean environment characteristic parameters at a specified position and time are extracted from the spatiotemporal complete environmental element database and input into the characteristic calculation model, and the real ocean environment optical characteristic data under the specified spatiotemporal conditions is inverted and generated. In this way, by combining the real environment information perceived by satellite remote sensing with the theoretical model, the representation of the change of the real optical characteristic data of the distant sea and remote environment is realized, breaking the contradictory situation that the satellite direct measured data cannot be used for the direct representation of the optical characteristics of the ocean environment and the theoretical model simulation is not real. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0019] Figure 1 It is a flow chart of a method for inverting optical characteristics of an ocean environment based on multi-source satellite remote sensing data provided by an embodiment of the present invention;

[0020] Figure 2 It is a schematic diagram of the results before and after preprocessing of a key marine environment characteristic parameter (sea surface temperature) provided by an embodiment of the present invention;

[0021] Figure 3 It is a schematic diagram of the inversion result of medium-wave sea surface background radiation brightness under a typical spectrum band and detection angle provided by an embodiment of the present invention;

[0022] Figure 4 is a hardware architecture diagram of a computing device provided by an embodiment of the present invention;

[0023] Figure 5 It is a structural diagram of a device for inverting optical characteristics of an ocean environment based on multi-source satellite remote sensing data provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0024] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0025] The specific implementation of the above concept is described below.

[0026] Please refer to Figure 1 The embodiment of the present invention provides a method for inverting optical characteristics of an ocean environment based on multi-source satellite remote sensing data, the method comprising:

[0027] Step 100, based on a variety of satellite remote sensing data, a variety of ocean environment characteristic parameters are obtained respectively; wherein the ocean environment characteristic parameters include atmospheric temperature profile, atmospheric humidity profile, aerosol optical thickness, cloud optical parameters, sea surface temperature, sea surface wind speed and wind direction;

[0028] Step 102, according to the data characteristics of each marine environment characteristic parameter, respectively select a corresponding method to pre-process each marine environment characteristic parameter to obtain a spatiotemporal complete environmental element database;

[0029] Step 104, extracting a variety of ocean environment characteristic parameters at a specified location and time from the complete spatiotemporal environmental element database, and inputting them together with satellite detection parameters into a pre-constructed ocean environment optical characteristic calculation model, and inverting to obtain the ocean environment optical characteristics under the specified spatiotemporal conditions; wherein the ocean environment optical characteristic calculation model includes an ocean atmosphere transmittance model, an ocean atmosphere path radiation brightness model, and a sea surface background radiation brightness model.

[0030] In the embodiment of the present invention, firstly, multiple ocean environment characteristic parameters are obtained by inverting the original data of satellite remote sensing data. For the multiple original ocean environment characteristic parameters, combined with the data characteristics of each ocean environment characteristic parameter, a corresponding method is selected to pre-process each ocean environment characteristic parameter, so as to complete the large-area missing of the original data caused by cloud pollution and improve the spatiotemporal resolution, so as to form a spatiotemporal complete environmental element database; then, a marine environment optical characteristic calculation model based on these marine environment characteristic parameters is constructed; a plurality of marine environment characteristic parameters at a specified position and time are extracted from the spatiotemporal complete environmental element database and input into the characteristic calculation model, so as to invert and generate the real marine environment optical characteristic data under the specified spatiotemporal conditions. In this way, by combining the real environment information perceived by satellite remote sensing with the theoretical model, the representation of the real optical characteristic data changes of the distant sea and remote environment is realized, breaking the contradictory situation that the satellite direct measured data cannot be used for the direct representation of the optical characteristics of the marine environment and the theoretical model simulation is not real.

[0031] For step 100:

[0032] In some embodiments, the atmospheric temperature profile and the atmospheric humidity profile are inverted based on ocean hyperspectral satellite remote sensing data, the aerosol optical thickness, cloud optical parameters and ocean surface temperature are inverted based on ocean multi-band imaging satellite remote sensing data, and the sea surface wind speed and wind direction are inverted based on ocean crosswind radar satellite remote sensing data; wherein the cloud optical parameters include cloud top height, cloud top pressure, cloud optical thickness and cloud effective particle size.

[0033] In the embodiment of the present invention, since the calculation model of the optical characteristics of the ocean environment requires a large number of environmental factor inputs, including atmospheric vertical distribution factors, single-layer atmospheric factors, and sea surface environmental factors, a single payload of a single satellite cannot satisfy the simultaneous acquisition of these factors. Therefore, multiple satellite data sources are selected to support characteristic inversion.

[0034] Three types of satellite remote sensing data are used in this embodiment:

[0035] (1) Ocean hyperspectral satellite remote sensing data, which is data obtained by infrared high-resolution spectrometers carried on polar-orbiting satellites or geostationary satellites, such as the infrared spectrum data obtained by Fengyun-3 (FY-3) or Fengyun-4 (FY-4) series satellites. The original spectrum data can be used to invert the atmospheric temperature profile and atmospheric humidity profile, two types of ocean environment characteristic parameters.

[0036] (2) Ocean multi-spectral imaging satellite remote sensing data, which are data obtained by multi-spectral imagers carried on polar-orbiting satellites or geostationary satellites, such as the radiation image data obtained by the FY-3, FY-4 and Himawari-8 satellites. The raw radiation data can be used to invert several ocean environment characteristic parameters such as sea surface temperature, aerosol optical depth, cloud top height, cloud top pressure, cloud optical depth and cloud effective particle size.

[0037] (3) Ocean wind radar satellite remote sensing data, which is data obtained by wind scatterometers carried on polar-orbiting satellites, such as the backscatter echo data obtained by the Ocean No. 2 (HY-2) series satellites. The raw scattering data can be used to invert the two marine environmental characteristic parameters of near-shore surface wind speed and wind direction.

[0038] If the three types of satellite remote sensing data are relatively mature business satellites, they all have atmospheric and ocean environmental factor data inversion products (the above-listed ocean environmental characteristic parameters), and these inversion products can be used directly. If a satellite without environmental factor inversion products is selected, it is necessary to start inversion from its original data, but this part of the inversion algorithm has relatively mature solutions that can be used directly, which is not within the scope of this embodiment.

[0039] Regarding step 102:

[0040] Considering that the original ocean environment characteristic parameters directly inverted by satellites are limited by cloud pollution, spatiotemporal resolution, etc., and cannot be directly used for the inversion of ocean environment optical characteristics, it is necessary to further carry out fusion inversion to form a spatiotemporal complete environmental factor database. Spatiotemporal complete environmental factor data refers to data with high spatiotemporal resolution and no large-scale data missing caused by cloud pollution. At the same time, the problems encountered by various data sources are different, and different algorithms need to be adopted for processing. There are three specific categories.

[0041] In some embodiments, a 3D deep convolutional neural network is used to complete and preprocess the atmospheric temperature profile and the atmospheric humidity profile, respectively; a deep convolutional neural network is used to complete and preprocess the ocean surface temperature; a convolutional visual converter is used to complete and preprocess the aerosol optical thickness; and a residual dense network structure and a convolutional gated recurrent unit are used in combination to perform spatiotemporal resolution enhancement preprocessing on the ocean surface wind speed, wind direction, and cloud parameters, respectively.

[0042] For atmospheric temperature profiles, atmospheric humidity profiles, sea surface temperature, and aerosol optical thickness, geostationary satellites can be used to obtain high-resolution data with kilometer-level spatial resolution and 10-minute-level temporal resolution. However, due to the influence of cloud pollution in the marine environment, large areas of data are often invalid. Therefore, the processing requirements of such data are the completion and inversion of missing data. In the embodiment of the present invention, according to the spatiotemporal variation characteristics of different parameters, the sea surface temperature is preprocessed with missing completion using U-Net deep learning technology (convolutional neural network); the atmospheric temperature and humidity profiles are preprocessed with 3D U-Net deep learning technology (3D deep convolutional neural network); and the aerosol optical thickness is preprocessed with missing completion using a deep learning technology (convolutional visual transformer) combining SwinTransformer and CNN.

[0043] For the wind speed and direction on the ocean surface, currently only the ocean dynamics detection radar carried by polar-orbiting satellites can obtain data. Although it can penetrate clouds and is not affected by cloud pollution, the temporal resolution and spatial resolution of the data are generally very low. Therefore, the preprocessing requirement of such data is high temporal and spatial resolution data inversion. In this embodiment, the RDN (Residual Dense Network) residual dense network structure deep learning technology is used to improve the spatial resolution of satellite direct data products, and the ConvGRU-ODE (Convolutional Gated Circular Unit) deep learning technology is used to improve the temporal resolution of satellite direct data products.

[0044] At the same time, for cloud parameters, if geostationary satellites are used to obtain them, the temporal and spatial resolutions are high enough and there is no large-scale pollution missing problem. Satellite cloud product data can be used directly without preprocessing. If polar-orbiting satellites are used, there are temporal and spatial resolution issues similar to those of ocean surface wind speed and direction. The same preprocessing method can be used to obtain high temporal and spatial resolution data.

[0045] In this embodiment, different processing methods are selected to pre-process the characteristics of each marine environment characteristic parameter and the source of acquisition, so that a complete marine environment element database can be formed in time and space, thereby effectively avoiding the problem that the data directly obtained by satellite remote sensing cannot represent the marine environment optical characteristics required for practical applications and cannot represent the real marine environment optical characteristics transformation. It should be noted that the key to this embodiment is to propose different pre-processing methods for different characteristic parameters, and the process of using the above pre-processing methods for specific processing is a relatively mature technology, which will not be elaborated here.

[0046] Regarding step 104:

[0047] In some embodiments, the satellite detection parameters include detection spectrum range, detection elevation angle, detection azimuth angle, detection altitude and transmission distance.

[0048] The calculation models of the optical characteristics of the ocean environment include the ocean atmosphere transmittance model, the ocean atmosphere path radiation brightness model and the sea surface background radiation brightness model.

[0049] In some embodiments, the ocean atmosphere transmittance model is constructed as follows:

[0050] Based on the OPAC model, the modeled marine aerosol extinction coefficient spectrum and cloud droplet extinction coefficient spectrum are constructed respectively;

[0051] Using the marine aerosol extinction coefficient spectrum, calculate the optical thickness of the aerosol in the specified detection spectrum range and the extinction coefficient value of the aerosol at the specified wavelength;

[0052] According to the input optical thickness of aerosol, the optical thickness of aerosol in the specified detection spectrum range and the extinction coefficient value of aerosol at the specified wavelength, a calculation model of aerosol optical thickness at the specified wavelength and the specified segment path is constructed;

[0053] Using the cloud droplet extinction coefficient spectrum, the extinction coefficient values ​​of cloud droplets in a specified detection spectrum range and at a specified wavelength are obtained respectively;

[0054] According to the input cloud optical thickness, cloud effective particle size, and the extinction coefficient of cloud droplets in the specified detection spectrum range and at the specified wavelength, a cloud optical thickness calculation model at the specified wavelength is constructed;

[0055] According to the input atmospheric temperature profile and atmospheric humidity profile, a calculation model of atmospheric molecular optical thickness at the specified wavelength and the specified segment path is constructed;

[0056] The ocean atmosphere transmittance model is constructed based on the constructed aerosol optical thickness calculation model, cloud optical thickness calculation model, atmospheric molecule optical thickness calculation model and the detection parameters.

[0057] In the embodiment of the present invention, the specific construction process of the ocean atmosphere transmittance model is as follows:

[0058] (1) Since the aerosol optical thickness changes slowly with wavelength, the aerosol height distribution is set as an exponential distribution, and the OPAC model is used to establish a modeled marine aerosol extinction coefficient spectrum. The extinction coefficient spectrum includes the extinction coefficient values ​​of aerosols at different bands. The extinction coefficient spectrum is combined with the input aerosol optical thickness (i.e., obtained from the spatiotemporal complete environmental factor database) to construct a calculation model for the aerosol optical thickness at a specified wavelength ν:

[0059]

[0060] In the formula, τ νa is the aerosol optical density at a specified wavelength ν, τ da The optical thickness calculated using the aerosol extinction coefficient spectrum under the condition of matching the satellite remote sensing detection spectrum range is obtained by integrating the entire layer of the detected aerosol extinction coefficient, τ oa is the input satellite remote sensing observation aerosol optical thickness, k νa is the extinction coefficient value at wavelength ν in the aerosol extinction coefficient spectrum, s represents the path variable, s1 represents the starting position of the path, and s2 represents the ending position of the path.

[0061] (2) Since the cloud optical thickness varies slowly with wavelength, assuming that the cloud droplets in the cloud are uniformly distributed, and their extinction coefficient is a parameter that varies with the effective particle size of the cloud droplets, the OPAC model is used to establish a modeled cloud droplet extinction coefficient spectrum, which includes the extinction coefficient values ​​of cloud droplets at different bands. The extinction coefficient spectrum is combined with the input cloud optical thickness and cloud effective particle size (that is, obtained from the spatiotemporal complete environmental factor database) to construct a calculation model for the cloud optical thickness at a specified wavelength ν:

[0062]

[0063] In the formula, τ νc is the cloud optical thickness at a specified wavelength ν, τ oc is the optical thickness value detected by satellite remote sensing, k oc is the extinction coefficient value in the satellite remote sensing detection spectrum of the cloud droplet extinction coefficient spectrum, k νc is the extinction coefficient value at the specified wavelength ν in the cloud droplet extinction coefficient spectrum, and r is the cloud effective particle size detected by satellite remote sensing.

[0064] (3) For molecular optical thickness, in this embodiment, it is assumed that all extinction gases except water vapor are uniformly distributed gases with known concentrations. The calculation model of molecular optical thickness at a specified wavelength v is constructed using the gas concentration that produces the extinction effect and the atmospheric temperature:

[0065]

[0066] In the formula, τ νm is the molecular optical thickness at a specified wavelength ν, σ ν,i is the extinction cross section of the i-th extinction gas. The extinction cross sections of all gas molecules are obtained from the HITRAN spectral database. The extinction cross section varies with air pressure and temperature, and satellite remote sensing provides the atmospheric temperature profile that varies with air pressure. n i is the molecular number density of the i-th extinction gas, k ν,m is the total extinction coefficient of gas molecules.

[0067] (4) Based on the above-constructed calculation models of aerosol optical thickness, cloud optical thickness and molecular optical thickness, an ocean atmosphere transmittance model is constructed:

[0068]

[0069] Where, T Δν is the atmospheric transmittance under the specified atmospheric path and spectral range, ν is the wavelength variable, ν1 is the starting wavelength of the calculated spectral range, ν2 is the ending wavelength of the calculated spectral range, Δν=ν2-ν1, τ ν is the optical thickness of the transmission path at wavelength ν, which is calculated by the following formula:

[0070] τ ν =τ νa +τ νc +τ νm

[0071] Among them, τ νa is the aerosol optical thickness at wavelength ν, τ νc is the cloud optical thickness at wavelength ν, τ νm is the molecular optical thickness of the atmosphere at wavelength ν.

[0072] In some embodiments, the ocean-atmosphere radiation brightness model is constructed in the following manner:

[0073] Using the atmospheric molecular optical thickness calculation model, the atmospheric optical thickness at the specified segment path is obtained;

[0074] Based on the input aerosol optical thickness, cloud optical thickness, atmospheric optical thickness and atmospheric temperature profile, the atmospheric source function is calculated using the discrete coordinate radiative transfer model;

[0075] The ocean atmosphere path radiation brightness model is constructed according to the atmospheric source function, the atmospheric optical thickness at the specified segment path and the satellite detection parameters.

[0076] In the embodiment of the present invention, the radiation brightness model of the ocean atmosphere is as follows:

[0077]

[0078] Where, L Δν represents the atmospheric path radiation brightness of the specified path and the specified spectrum, ν represents the wavelength variable, ν1 is the starting wavelength of the calculated spectrum, ν2 is the ending wavelength of the calculated spectrum, s is the path variable, s1 is the starting position of the path, s2 is the ending position of the path, τ ν (s, s2) is the atmospheric optical thickness of the segment path s-s2, kν is the total atmospheric extinction coefficient, which is obtained by summing the extinction coefficients of gas molecules, aerosols and cloud droplets. ν is the atmospheric source function.

[0079] In the embodiment of the present invention, when s1 is outside the atmosphere and the transmission path between s1 and s2 has no intersection with the earth (that is, the detection line of sight has no intersection with the sea surface), L Δν It is transformed into a calculation model for the atmospheric background radiation brightness; τ ν (s, s2) is calculated by the atmospheric optical thickness calculation model. The atmospheric source function is calculated by the discrete coordinate radiative transfer model (DISORT) model, with the aerosol optical thickness, cloud optical thickness, atmospheric optical thickness and atmospheric temperature profile obtained by satellite remote sensing detection as input parameters.

[0080] In some embodiments, the ocean surface background radiation brightness model is constructed as follows:

[0081] According to the solar radiation illuminance spectrum at the top of the atmosphere and the ocean atmosphere transmittance model, the direct solar radiation illuminance reaching the ocean surface at a specified wavelength is obtained;

[0082] Based on the direct solar radiation illuminance and the effective solid angle of solar radiation, a calculation model for the direct solar radiation brightness reaching the ocean surface at a specified wavelength is constructed;

[0083] Calculating the atmospheric downwelling radiation flux reaching the ocean surface at a specified wavelength according to the atmospheric path radiation model;

[0084] Based on the input ocean surface temperature and Planck's formula, the blackbody radiation brightness of the ocean surface at the specified wavelength is obtained;

[0085] The sea surface background radiation brightness model is constructed based on the solar direct radiation brightness calculation model, the atmospheric downward radiation flux, the blackbody radiation brightness and the satellite detection parameters.

[0086] In the embodiment of the present invention, the solar direct radiation brightness calculation model is as follows:

[0087] L ν,sun =E ν,sun / rad sun

[0088] Where, L ν,sun is the direct solar radiation brightness reaching the ocean surface at a specified wavelength ν, E ν,sun is the direct solar radiation irradiance reaching the ocean surface at a specified wavelength ν, which is calculated by combining the solar radiation irradiance spectrum at the top of the atmosphere (using the solar radiation irradiance spectrum data of Kurucz 2005) with the atmospheric transmittance calculation model described above. sun=6.8*10 -5 sr is the effective solid angle of solar radiation;

[0089] The sea surface background radiation brightness model is as follows:

[0090]

[0091] Where, L s (x, y) is the sea surface background radiation brightness of the detection pixel (x, y), ν is the wavelength variable, ν1 is the starting wavelength of the calculated spectrum range, ν2 is the ending wavelength of the calculated spectrum range, E ν,sky is the atmospheric downward radiation flux reaching the ocean surface at a specified wavelength ν, calculated using the atmospheric path radiation model described above, L ν,sb is the blackbody radiation brightness of the ocean surface at a specified wavelength ν, which is calculated by Planck's formula combined with the input of the satellite remote sensing ocean surface temperature. ε(θ) is the sea surface emissivity, which is calculated by the following formula: ε(θ) = 1-R(θ) = 0.98[1-(1-cosθ) 5 ], where R(θ) is the sea surface reflectivity, A is the average sea surface reflectivity, and μ is obtained by averaging the reflectivity at different θ angles. sun =cos(θ sun ) is the cosine of the solar direction angle, θ sun is the angle between the sun direction and the normal line of the sea surface tilt surface element, θ is the angle between the detection line of sight and the normal line of the sea surface tilt surface element, where the normal line of the sea surface tilt surface element is generated by the two-dimensional sea spectrum model through inverse Fourier transform, using the offshore surface wind speed and direction as input parameters, δ sun (x, y) is the bright band factor of the sea surface, when -0.26°≤θ-θ sun The bright band factor is 1 when ≤0.26°, and 0 for all other conditions.

[0092] Through the above modeling process, a model was constructed that can use satellite remote sensing ocean environment characteristic parameters to calculate ocean environment optical characteristic data, laying the foundation for a model based on satellite remote sensing inversion of optical characteristics.

[0093] When the above ocean environment optical characteristic calculation model is used to invert the optical characteristics of the ocean environment optical change at a specified time and location, firstly, the multiple ocean environment characteristic parameters at the corresponding time and location are searched in the spatiotemporal complete environmental element database constructed in step 102 by the nearest neighbor method according to the longitude and latitude and time, and the parameters are used as the input of the characteristic calculation model, and the specified satellite detection parameters are input according to the inversion requirements, including: detection spectrum range, detection pitch angle, detection azimuth, detection height and transmission distance, etc., and then the ocean atmosphere transmittance, ocean atmosphere path radiance, and sea surface background radiance under the constraints of the environmental state and detection conditions are calculated and generated. Through this process, the inversion of the real ocean environment optical characteristics supported by multi-source satellite remote sensing data is completed.

[0094] Taking the inversion of medium-wave infrared background radiation of the near-sea surface at a specified time and specified longitude and latitude in the East China Sea as an example, the specific implementation method in this embodiment is explained:

[0095] Himawari-8 was selected as the satellite remote sensing data source for the inversion of ocean surface temperature and aerosol optical thickness, FY-4 was selected as the satellite remote sensing data source for the inversion of atmospheric temperature profile and atmospheric humidity profile, and HY-2 was selected as the satellite remote sensing data source for the inversion of near-shore surface wind speed and wind direction. The remote sensing data of Himawari-8 were directly used to obtain cloud top height, cloud top pressure, cloud optical thickness, and cloud effective particle size data products.

[0096] First, the satellite detections selected above are used to obtain the original satellite data (including atmospheric temperature profile, atmospheric humidity profile, aerosol optical thickness, cloud optical parameters, sea surface temperature, sea surface wind speed and wind direction) of the entire East China Sea on January 1, 2021, and the preprocessing method in this embodiment is used to preprocess each parameter to obtain a complete spatial and temporal environmental element database, and generate cloud-free sea surface temperature, aerosol optical thickness, atmospheric temperature and humidity profile, and near-shore surface wind speed and direction data with a time resolution of 15 minutes and a spatial resolution of 4 kilometers in the East China Sea on January 1, 2021. Among them, the results of the key environmental characteristic parameter sea surface temperature before and after preprocessing in a time series can be obtained by Figure 2 Obtained by comparison.

[0097] Afterwards, from the constructed spatiotemporal complete environmental element database, a set of ocean environmental characteristic parameter data at longitude and latitude (125°E, 30°N) and time 6:20 UTC is selected according to the nearest neighbor method as the environmental element input of the ocean environmental optical characteristic calculation model; and the detection spectrum range is selected to be 3-5μm, the detector height is 50m from the sea level, the detection pitch angle is -10° (the default horizontal viewing direction is 0°, negative values ​​are considered downward and positive values ​​are considered upward), and the detection azimuth is 200° (the default north viewing direction is 0°); the sea surface background radiation model constructed in step 104 is used to calculate the sea surface background radiation brightness in this state. Figure 3 As shown, the result generated by the model calculation is the medium-wave sea surface radiation brightness image inverted at the longitude and latitude, at the time, and under the specified detection geometry conditions, which reflects the sea surface background characteristics determined by the environmental conditions at the moment.

[0098] In summary, in the embodiments of the present invention, by combining the real environment information perceived by satellite remote sensing with the theoretical model, the real optical property data of the distant sea and remote area can be provided in real time, breaking the contradictory situation that the direct measured data from the satellite cannot be used to directly characterize the optical properties of the ocean environment and the theoretical model simulation is not real, and supporting the design of key indicators and application modes of optical sensors for sea detection.

[0099] like Figure 4 , Figure 5 As shown, an embodiment of the present invention provides an apparatus for inverting optical characteristics of an ocean environment based on multi-source satellite remote sensing data. The apparatus embodiment can be implemented by software, or by hardware or a combination of software and hardware. Figure 4 As shown in FIG. 1 , a hardware architecture diagram of a computing device in which an ocean environment optical property inversion device based on multi-source satellite remote sensing data provided by an embodiment of the present invention is located is shown in FIG. Figure 5 In addition to the processor, memory, network interface, and non-volatile memory shown in the figure, the computing device in which the device is located in the embodiment may also generally include other hardware, such as a forwarding chip responsible for processing messages, etc. Taking software implementation as an example, Figure 5 As shown, as a device in a logical sense, the CPU of the computing device in which it is located reads the corresponding computer program in the non-volatile memory into the memory and runs it. This embodiment provides an inversion device for optical characteristics of ocean environment based on multi-source satellite remote sensing data, and the device includes:

[0100] The acquisition unit 501 is used to respectively acquire a plurality of ocean environment characteristic parameters based on a plurality of satellite remote sensing data; wherein the ocean environment characteristic parameters include an atmospheric temperature profile, an atmospheric humidity profile, an aerosol optical thickness, a cloud optical parameter, an ocean surface temperature, and a sea surface wind speed and direction;

[0101] A preprocessing unit 502 is used to select a corresponding method to preprocess each marine environment characteristic parameter according to the data characteristics of each marine environment characteristic parameter, so as to obtain a spatiotemporal complete environmental element database;

[0102] The inversion unit 503 is used to extract a variety of ocean environment characteristic parameters at a specified location and time from the complete spatiotemporal environmental element database, and input them together with satellite detection parameters into a pre-constructed ocean environment optical characteristic calculation model to invert the ocean environment optical characteristics under the specified spatiotemporal conditions; wherein the ocean environment optical characteristic calculation model includes an ocean atmosphere transmittance model, an ocean atmosphere path radiation brightness model and a sea surface background radiation brightness model.

[0103] In the embodiment of the present invention, the acquisition unit 501 can be used to execute step 100 in the above method embodiment, the preprocessing unit 502 can be used to execute step 102 in the above method embodiment, and the inversion unit 503 can be used to execute step 104 in the above method embodiment.

[0104] In one embodiment of the present invention, in the acquisition unit 501, the atmospheric temperature profile and the atmospheric humidity profile are inverted based on ocean hyperspectral satellite remote sensing data, the aerosol optical thickness, cloud optical parameters and ocean surface temperature are inverted based on ocean multi-band imaging satellite remote sensing data, and the sea surface wind speed and wind direction are inverted based on ocean crosswind radar satellite remote sensing data; wherein the cloud optical parameters include cloud top height, cloud top pressure, cloud optical thickness and cloud effective particle size.

[0105] In one embodiment of the present invention, in the inversion unit 503, the satellite detection parameters include detection spectrum range, detection elevation angle, detection azimuth angle, detection altitude and transmission distance.

[0106] In one embodiment of the present invention, in the preprocessing unit 502, a 3D deep convolutional neural network is used to complete and preprocess the atmospheric temperature profile and the atmospheric humidity profile respectively; a deep convolutional neural network is used to complete and preprocess the ocean surface temperature; a convolutional visual converter is used to complete and preprocess the aerosol optical thickness; and a residual dense network structure and a convolutional gated recurrent unit are combined to perform spatiotemporal resolution enhancement preprocessing on the ocean surface wind speed and wind direction respectively.

[0107] In one embodiment of the present invention, in the inversion unit 503, the ocean atmosphere transmittance model is constructed in the following manner:

[0108] Based on the OPAC model, the modeled marine aerosol extinction coefficient spectrum and cloud droplet extinction coefficient spectrum are constructed respectively;

[0109] Using the marine aerosol extinction coefficient spectrum, calculate the optical thickness of the aerosol in the specified detection spectrum range and the extinction coefficient value of the aerosol at the specified wavelength;

[0110] According to the input optical thickness of aerosol, the optical thickness of aerosol in the specified detection spectrum range and the extinction coefficient value of aerosol at the specified wavelength, a calculation model of aerosol optical thickness at the specified wavelength and the specified segment path is constructed;

[0111] Using the cloud droplet extinction coefficient spectrum, the extinction coefficient values ​​of cloud droplets in a specified detection spectrum range and at a specified wavelength are obtained respectively;

[0112] According to the input cloud optical thickness, cloud effective particle size, and the extinction coefficient of cloud droplets in the specified detection spectrum range and at the specified wavelength, a cloud optical thickness calculation model at the specified wavelength is constructed;

[0113] According to the input atmospheric temperature profile and atmospheric humidity profile, a calculation model of atmospheric molecular optical thickness at the specified wavelength and the specified segment path is constructed;

[0114] The ocean atmosphere transmittance model is constructed based on the constructed aerosol optical thickness calculation model, cloud optical thickness calculation model, atmospheric molecule optical thickness calculation model and the detection parameters.

[0115] In one embodiment of the present invention, in the inversion unit 503, the ocean atmosphere path radiance model is constructed in the following manner:

[0116] Using the atmospheric molecular optical thickness calculation model, the atmospheric optical thickness at the specified segment path is obtained;

[0117] Based on the input aerosol optical thickness, cloud optical thickness, atmospheric optical thickness and atmospheric temperature, the atmospheric source function is calculated using the discrete coordinate radiative transfer model;

[0118] The ocean atmosphere path radiation brightness model is constructed according to the atmospheric source function, the atmospheric optical thickness at the specified segment path and the satellite detection parameters.

[0119] In one embodiment of the present invention, in the inversion unit 503, the sea surface background radiation brightness model is constructed in the following manner:

[0120] According to the solar radiation illuminance spectrum at the top of the atmosphere and the ocean atmosphere transmittance model, the direct solar radiation illuminance reaching the ocean surface at a specified wavelength is obtained;

[0121] Based on the direct solar radiation illuminance and the effective solid angle of solar radiation, a calculation model for the direct solar radiation brightness reaching the ocean surface at a specified wavelength is constructed;

[0122] Calculating the atmospheric downwelling radiation flux reaching the ocean surface at a specified wavelength according to the atmospheric path radiation model;

[0123] Based on the input ocean surface temperature and Planck's formula, the blackbody radiation brightness of the ocean surface at the specified wavelength is obtained;

[0124] The sea surface background radiation brightness model is constructed based on the solar direct radiation brightness calculation model, the atmospheric downward radiation flux, the blackbody radiation brightness and the satellite detection parameters.

[0125] It is to be understood that the structure illustrated in the embodiment of the present invention does not constitute a specific limitation on a device for inverting optical properties of an ocean environment based on multi-source satellite remote sensing data. In other embodiments of the present invention, a device for inverting optical properties of an ocean environment based on multi-source satellite remote sensing data may include more or fewer components than shown in the figure, or combine some components, or split some components, or arrange the components differently. The components shown in the figure may be implemented in hardware, software, or a combination of software and hardware.

[0126] The information interaction, execution process and other contents between the modules in the above-mentioned device are based on the same concept as the embodiment of the method of the present invention. For the specific contents, please refer to the description in the embodiment of the method of the present invention, and no further description is given here.

[0127] An embodiment of the present invention further provides a computing device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, a method for inverting the optical characteristics of an ocean environment based on multi-source satellite remote sensing data in any embodiment of the present invention is implemented.

[0128] An embodiment of the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the processor executes a method for inverting the optical characteristics of an ocean environment based on multi-source satellite remote sensing data in any embodiment of the present invention.

[0129] Specifically, a system or device equipped with a storage medium can be provided, on which software program code that implements the functions of any of the above-mentioned embodiments is stored, and a computer (or CPU or MPU) of the system or device can be enabled to read and execute the program code stored in the storage medium.

[0130] In this case, the program code itself read from the storage medium can realize the function of any one of the above-mentioned embodiments, and thus the program code and the storage medium storing the program code constitute a part of the present invention.

[0131] The storage medium embodiments for providing the program code include a floppy disk, a hard disk, a magneto-optical disk, an optical disk (such as CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD+RW), a magnetic tape, a non-volatile memory card, and a ROM. Alternatively, the program code can be downloaded from a server computer by a communication network.

[0132] In addition, it should be clear that the functions of any of the above embodiments can be implemented not only by executing the program code read by the computer, but also by enabling an operating system operating on the computer to complete part or all of the actual operations based on instructions from the program code.

[0133] In addition, it can be understood that the program code read from the storage medium is written to a memory provided in an expansion board inserted into the computer or to a memory provided in an expansion module connected to the computer, and then based on the instructions of the program code, a CPU installed on the expansion board or expansion module is enabled to perform part or all of the actual operations, thereby realizing the functions of any of the above-mentioned embodiments.

[0134] An embodiment of the present application also provides a computer-readable storage medium, on which is stored at least one instruction, at least one program, code set or instruction set, and the at least one instruction, at least one program, code set or instruction set is loaded and executed by a processor to implement a method for inverting the optical properties of an ocean environment based on multi-source satellite remote sensing data provided by the above-mentioned method embodiments.

[0135] It should be noted that, in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0136] A person of ordinary skill in the art can understand that all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiments; and the aforementioned storage medium includes: ROM, RAM, magnetic disk or optical disk, etc., various media that can store program codes.

[0137] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for inverting the optical characteristics of the ocean environment based on multi-source satellite remote sensing data, characterized in that: include: Based on a variety of satellite remote sensing data, a variety of ocean environment characteristic parameters are obtained respectively; wherein the ocean environment characteristic parameters include atmospheric temperature profile, atmospheric humidity profile, aerosol optical thickness, cloud optical parameters, ocean surface temperature, sea surface wind speed and wind direction; According to the data characteristics of each marine environmental characteristic parameter, the corresponding method is selected to pre-process each marine environmental characteristic parameter to obtain a spatiotemporal complete environmental element database; A variety of ocean environment characteristic parameters at specified locations and times are extracted from the complete spatiotemporal environmental element database, and are input together with satellite detection parameters into a pre-constructed ocean environment optical characteristic calculation model to invert the ocean environment optical characteristics under specified spatiotemporal conditions; wherein the ocean environment optical characteristic calculation model includes an ocean atmosphere transmittance model, an ocean atmosphere path radiation brightness model, and a sea surface background radiation brightness model.

2. The method according to claim 1, characterized in that The atmospheric temperature profile and the atmospheric humidity profile are inverted based on ocean hyperspectral satellite remote sensing data, the aerosol optical thickness, cloud optical parameters and ocean surface temperature are inverted based on ocean multi-band imaging satellite remote sensing data, and the sea surface wind speed and wind direction are inverted based on ocean crosswind radar satellite remote sensing data; wherein the cloud optical parameters include cloud top height, cloud top pressure, cloud optical thickness and cloud effective particle size.

3. The method according to claim 1, characterized in that The satellite detection parameters include detection spectrum range, detection pitch angle, detection azimuth angle, detection altitude and transmission distance.

4. The method according to claim 1, characterized in that: According to the data characteristics of each marine environment characteristic parameter, a corresponding method is selected to pre-process each marine environment characteristic parameter, including: A 3D deep convolutional neural network is used to complete and preprocess the atmospheric temperature profile and atmospheric humidity profile respectively; a deep convolutional neural network is used to complete and preprocess the ocean surface temperature; a convolutional visual converter is used to complete and preprocess the aerosol optical thickness; The residual dense network structure and convolutional gated recurrent unit are combined to perform spatiotemporal resolution enhancement preprocessing on the ocean surface wind speed and direction, respectively.

5. The method according to claim 1, characterized in that The ocean atmosphere transmittance model is constructed in the following way: Based on the OPAC model, the modeled marine aerosol extinction coefficient spectrum and cloud droplet extinction coefficient spectrum are constructed respectively; Using the marine aerosol extinction coefficient spectrum, calculate the optical thickness of the aerosol in the specified detection spectrum range and the extinction coefficient value of the aerosol at the specified wavelength; According to the input optical thickness of aerosol, the optical thickness of aerosol in the specified detection spectrum range and the extinction coefficient value of aerosol at the specified wavelength, a calculation model of aerosol optical thickness at the specified wavelength and the specified segment path is constructed; Using the cloud droplet extinction coefficient spectrum, the extinction coefficient values ​​of cloud droplets in a specified detection spectrum range and at a specified wavelength are obtained respectively; According to the input cloud optical thickness, cloud effective particle size, and the extinction coefficient of cloud droplets in the specified detection spectrum range and at the specified wavelength, a cloud optical thickness calculation model at the specified wavelength is constructed; According to the input atmospheric temperature profile and atmospheric humidity profile, a calculation model of atmospheric molecular optical thickness at the specified wavelength and the specified segment path is constructed; The ocean atmosphere transmittance model is constructed based on the constructed aerosol optical thickness calculation model, cloud optical thickness calculation model, atmospheric molecule optical thickness calculation model and the detection parameters.

6. The method according to claim 5, characterized in that The ocean-atmosphere radiation brightness model is constructed in the following way: Using the atmospheric molecular optical thickness calculation model, the atmospheric optical thickness at the specified segment path is obtained; Based on the input aerosol optical thickness, cloud optical thickness, atmospheric optical thickness and atmospheric temperature profile, the atmospheric source function is calculated using the discrete coordinate radiative transfer model; The ocean atmosphere path radiation brightness model is constructed according to the atmospheric source function, the atmospheric optical thickness at the specified segment path and the satellite detection parameters.

7. The method according to claim 6, characterized in that The sea surface background radiation brightness model is constructed as follows: According to the solar radiation illuminance spectrum at the top of the atmosphere and the ocean atmosphere transmittance model, the direct solar radiation illuminance reaching the ocean surface at a specified wavelength is obtained; Based on the direct solar radiation illuminance and the effective solid angle of solar radiation, a calculation model for the direct solar radiation brightness reaching the ocean surface at a specified wavelength is constructed; Calculating the atmospheric downwelling radiation flux reaching the ocean surface at a specified wavelength according to the atmospheric path radiation model; Based on the input ocean surface temperature and Planck's formula, the blackbody radiation brightness of the ocean surface at the specified wavelength is obtained; The sea surface background radiation brightness model is constructed based on the solar direct radiation brightness calculation model, the atmospheric downward radiation flux, the blackbody radiation brightness and the satellite detection parameters.

8. A device for inverting the optical characteristics of ocean environment based on multi-source satellite remote sensing data, characterized in that: include: An acquisition unit is used to acquire a plurality of ocean environment characteristic parameters based on a plurality of satellite remote sensing data; wherein the ocean environment characteristic parameters include atmospheric temperature profile, atmospheric humidity profile, aerosol optical thickness, cloud optical parameters, ocean surface temperature, sea surface wind speed and wind direction; A preprocessing unit is used to select a corresponding method to preprocess each marine environment characteristic parameter according to the data characteristics of each marine environment characteristic parameter, so as to obtain a spatiotemporal complete environmental element database; The inversion unit is used to extract a variety of ocean environment characteristic parameters at a specified location and time from the complete spatiotemporal environmental element database, and input them together with satellite detection parameters into a pre-constructed ocean environment optical characteristic calculation model to invert the ocean environment optical characteristics under the specified spatiotemporal conditions; wherein the ocean environment optical characteristic calculation model includes an ocean atmosphere transmittance model, an ocean atmosphere path radiation brightness model and a sea surface background radiation brightness model.

9. A computing device, comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to execute the method according to any one of claims 1 to 7.

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