A method and system for retrieving ground surface and aerosol parameters based on lidar

Abstract

The application provides a ground surface and aerosol parameter inversion method and system based on a laser radar, and the method comprises the following steps: based on a signal model of a single-photon laser radar, a theoretical mapping relationship of apparent surface reflectivity about ground surface reflectivity and aerosol optical thickness is established; based on a background noise model of the single-photon laser radar, a theoretical mapping relationship of atmospheric top reflectivity about the ground surface reflectivity and the aerosol optical thickness is established; according to signal and noise observation data of a to-be-measured region provided by the single-photon laser radar, measurement data of the apparent surface reflectivity and the atmospheric top reflectivity of the to-be-measured region are calculated; and in combination with the theoretical mapping relationship of the apparent surface reflectivity and the atmospheric top reflectivity about the ground surface reflectivity and the aerosol optical thickness and the measurement data of the apparent surface reflectivity and the atmospheric top reflectivity of the to-be-measured region, ground surface reflectivity and aerosol optical thickness parameters of the to-be-measured region are inversely derived.

Description

Technical Field

[0001] This invention belongs to the field of laser remote sensing, specifically relating to a method and system for inverting surface and aerosol parameters based on lidar. Background Technology

[0002] Surface reflectance (SR) and aerosol optical thickness (AOT) are key parameters for Earth observation. Their significance lies in quantitatively characterizing the radiative properties of light reflection at the Earth's surface and propagation through the atmospheric aerosol layer. They provide the core physical foundation for terrain identification and classification, aerosol and cloud monitoring, atmospheric correction in optical remote sensing, and remote sensing inversion, supporting environmental assessment and resource management for landform types such as deserts, plains, ice sheets, and snowfields. Over the past few decades, relying on mature land and aerosol identification algorithms, spaceborne passive optical sensors (such as multispectral cameras) have provided extensive and long-term data support for studying the Earth system. However, passive optical sensors only have a single measurement value (top atmospheric reflectance) per pixel, corresponding to two unknown parameters: surface reflectance and aerosol optical thickness. They often rely on assumptions about the spectral characteristics of aerosols and the Earth's surface to complete SR and AOT inversion, which still presents many limitations in many scenarios.

[0003] In recent years, the rapid development of active laser remote sensing technology has provided a new approach to solving this bottleneck. Active detection not only overcomes the limitations of passive optical remote sensing in vertical observation but also allows operation at night or in low-light conditions at high latitudes, providing data support for Earth observation over a wider spatiotemporal range. The application of single-photon lidar technology has brought about a major breakthrough in this field. Summary of the Invention

[0004] To overcome the limitations of existing technologies that often rely on assumptions about the spectral characteristics of aerosols and the Earth's surface to complete the inversion of SR and AOT, which still have many limitations in many scenarios, this invention provides a method and system for inverting surface and aerosol parameters based on lidar. By using track-based signal data and noise data measured by single-photon lidar, it achieves the inversion of surface reflectance and aerosol optical thickness parameters based on a single platform and a single measurement. It can realize the inversion of surface reflectance and aerosol optical thickness without spectral assumptions, thereby improving the accuracy of Earth detection in complex land and atmospheric environments.

[0005] According to one aspect of the present invention, a method for inverting surface and aerosol parameters based on lidar is provided, comprising:

[0006] Based on the signal model of single-photon lidar, a theoretical mapping relationship between apparent surface reflectivity and surface reflectivity and aerosol optical thickness is established.

[0007] Based on the background noise model of single-photon lidar, a theoretical mapping relationship between atmospheric top reflectivity and surface reflectivity and aerosol optical thickness is established.

[0008] Based on the signal and noise observation data of the area to be measured provided by the single-photon lidar, the measured data of the apparent surface reflectivity and the top atmospheric reflectivity of the area to be measured are calculated.

[0009] By combining the theoretical mapping relationship between apparent surface reflectance and surface reflectance and aerosol optical thickness, the theoretical mapping relationship between atmospheric top reflectance and surface reflectance and aerosol optical thickness, and the measured data of apparent surface reflectance and atmospheric top reflectance of the area to be measured, the parameters of surface reflectance and aerosol optical thickness of the area to be measured are obtained by inversion.

[0010] As a further implementation scheme, the steps for establishing the theoretical mapping relationship between apparent surface reflectance and surface reflectance and aerosol optical thickness are as follows:

[0011] Based on the system parameters of a single-photon lidar, a signal model for the single-photon lidar is established regarding the surface reflectivity and the one-way transmittance of direct atmospheric light.

[0012] Based on the signal model of single-photon lidar, we obtain the expression for the theoretically measured apparent surface reflectance, and the expression for the theoretically measured apparent surface reflectance with respect to the surface reflectance and the one-way transmittance of direct atmospheric light.

[0013] The atmospheric direct one-way transmittance is expressed as aerosol optical thickness, and the theoretically measured expression of apparent surface reflectance with respect to surface reflectance and atmospheric direct one-way transmittance is substituted into it to establish a theoretical mapping relationship between apparent surface reflectance and aerosol optical thickness.

[0014] As a further implementation scheme, the mathematical expression for the theoretical mapping relationship between apparent surface reflectance and surface reflectance and aerosol optical thickness is as follows:

[0015]

[0016] In the formula, r app_theo The theoretically calculated value representing the apparent surface reflectivity; f signal ( . This represents a mapping relationship based on a signal model; r s It is the surface reflectance; t o3 It is the optical thickness of ozone; t R Represents Rayleigh Optical thickness; t aRepresents the optical thickness of the aerosol; i v It is the zenith angle of the sensor.

[0017] As a further implementation scheme, the process for constructing the theoretical mapping relationship between atmospheric top reflectivity and surface reflectivity and aerosol optical thickness is as follows:

[0018] Based on the system parameters of a single-photon lidar, a background noise model for the single-photon lidar is established, considering the surface reflectivity, atmospheric path radiation reflectivity, and atmospheric diffuse transmittance.

[0019] Based on the background model of single-photon lidar, we obtain the expression for the theoretical measurement of atmospheric top reflectivity, and its expression for surface reflectivity, atmospheric path radiation reflectivity, and atmospheric diffuse transmittance.

[0020] By expressing atmospheric path radiative reflectance and atmospheric diffuse transmittance as aerosol optical thickness, and substituting them into the theoretically measured expression for atmospheric top reflectance with respect to surface reflectance, atmospheric path radiative reflectance, and atmospheric diffuse transmittance, a theoretical mapping relationship between atmospheric top reflectance and surface reflectance and aerosol optical thickness is established.

[0021] As a further implementation scheme, the mathematical expression for the theoretical mapping relationship between atmospheric top reflectivity and surface reflectivity and aerosol optical thickness is as follows:

[0022]

[0023] In the formula, r toa_theo The theoretically calculated value representing the reflectivity at the top of the atmosphere; f noise (.) indicates a mapping relationship based on the background noise model; S atm It is the spherical albedo of the atmosphere; i s It is the zenith angle of the sun; oh a It is the single-scattering albedo of the aerosol; P R ( i- ) is the Rayleigh phase function. P a ( i- ) is the aerosol scattering phase function. i- This represents the scattering angle of light as it is scattered backward from the atmosphere.

[0024] As a further implementation scheme, the calculation process for the measurement data of the apparent surface reflectance and atmospheric top reflectance of the area to be measured is as follows:

[0025] By substituting the signal observation data of the area to be measured provided by the single-photon lidar into the expression for the theoretical measurement of the apparent surface reflectivity, the measurement data of the apparent surface reflectivity of the area to be measured is obtained; at the same time, by substituting the noise observation data of the area to be measured provided by the single-photon lidar into the expression for the theoretical measurement of the reflectivity of the top of the atmosphere, the measurement data of the reflectivity of the top of the atmosphere is obtained.

[0026] As a further implementation plan, the inversion process of the surface reflectance and aerosol optical thickness parameters of the area to be measured is as follows:

[0027] The measured data of the apparent surface reflectance of the area to be measured are substituted into the theoretical mapping relationship of apparent surface reflectance with respect to surface reflectance and aerosol optical thickness. At the same time, the measured data of the atmospheric top reflectance of the area to be measured are substituted into the theoretical mapping relationship of atmospheric top reflectance with respect to surface reflectance and aerosol optical thickness. These are combined into a nonlinear bivariate equation, and the inversion results of the surface reflectance and aerosol optical thickness parameters are obtained by solving the equation.

[0028] According to another aspect of this specification, a lidar-based surface and aerosol parameter inversion system is provided, comprising:

[0029] The apparent surface reflectance mapping derivation module is used to establish a theoretical mapping relationship between apparent surface reflectance and surface reflectance and aerosol optical thickness based on the signal model of single-photon lidar.

[0030] The top atmospheric reflectivity mapping derivation module is used to establish a theoretical mapping relationship between top atmospheric reflectivity and surface reflectivity and aerosol optical thickness based on the background noise model of single-photon lidar.

[0031] The measurement data acquisition module is used to calculate the measurement data of the apparent surface reflectance and atmospheric top reflectance of the area under test based on the signal and noise observation data of the area under test provided by the single-photon lidar.

[0032] The parameter inversion module is used to combine the theoretical mapping relationship between apparent surface reflectance and surface reflectance and aerosol optical thickness, the theoretical mapping relationship between atmospheric top reflectance and surface reflectance and aerosol optical thickness, and the measured data of apparent surface reflectance and atmospheric top reflectance of the area to be measured, to invert and obtain the surface reflectance and aerosol optical thickness parameters of the area to be measured.

[0033] According to another aspect of this specification, an electronic device is provided, including a memory and a processor, the memory storing program instructions executed by the processor, the processor invoking the program instructions to perform a lidar-based method for inverting surface and aerosol parameters.

[0034] According to another aspect of this specification, a non-transitory computer-readable storage medium is provided, the non-transitory computer-readable storage medium storing computer instructions that cause the computer to execute a lidar-based method for inverting surface and aerosol parameters.

[0035] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention uses track-side signal data and noise data measured by single-photon lidar to realize the inversion of surface reflectance and aerosol optical thickness parameters based on a single platform and a single measurement. It can realize the inversion of surface reflectance and aerosol optical thickness without spectral assumptions, improve the accuracy of Earth detection in complex land and atmospheric environments, help to realize large-scale, high-resolution monitoring of surface and aerosol characteristics, and provide reliable data support for Earth observation. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0037] Figure 1 A schematic diagram of a method for inverting surface and aerosol parameters based on lidar provided in an embodiment of the present invention;

[0038] Figure 2 A schematic diagram of the process for obtaining surface reflectance and aerosol optical thickness parameters of the area to be measured based on ICESat-2 data, provided in an embodiment of the present invention;

[0039] Figure 3 Example diagram of the inversion results of obtaining surface reflectance and aerosol optical thickness parameters of the area to be measured based on ICESat-2 data provided in the embodiments of the present invention, and comparison of the results of aerosol products and land product verification data from the MODIS (Modular Dynamics Intensity Spectrometer) in the medium resolution imaging spectrometer.

[0040] Figure 4 A schematic diagram of a surface and aerosol parameter inversion system based on lidar provided in an embodiment of the present invention;

[0041] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0042] It should be noted that:

[0043] The terms “comprising” and “having”, and any variations thereof, in the specification, claims, and accompanying drawings of this invention are intended to cover a non-exclusive inclusion, such as a process, method, system, product, or apparatus that includes a series of steps or units, not necessarily limited to those explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0044] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices. The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be decomposed, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0045] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. In addition, the technical features of the various embodiments or individual embodiments provided by the present invention can be arbitrarily combined to form new technical solutions. Such combinations are not bound by the order of steps and / or structural composition patterns, but must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by the present invention.

[0046] like Figure 1 As shown, a method for inverting surface and aerosol parameters based on lidar includes:

[0047] Step 1: Based on the signal model of single-photon lidar, establish the theoretical mapping relationship between apparent surface reflectivity and surface reflectivity and aerosol optical thickness;

[0048] Step 2: Based on the background noise model of single-photon lidar, establish the theoretical mapping relationship between atmospheric top reflectivity and surface reflectivity and aerosol optical thickness;

[0049] Step 3: Based on the signal and noise observation data of the area to be measured provided by the single-photon lidar, calculate the measurement data of the apparent surface reflectivity and the top atmospheric reflectivity of the area to be measured.

[0050] Step 4: Combining the theoretical mapping relationship between apparent surface reflectance and surface reflectance and aerosol optical thickness, the theoretical mapping relationship between atmospheric top reflectance and surface reflectance and aerosol optical thickness, and the measured data of apparent surface reflectance and atmospheric top reflectance of the area to be measured, the surface reflectance and aerosol optical thickness parameters of the area to be measured are obtained by inversion.

[0051] Furthermore, in step 1, the steps for establishing the theoretical mapping relationship between apparent surface reflectance and surface reflectance and aerosol optical thickness are as follows:

[0052] Based on the system parameters of a single-photon lidar, a signal model for the single-photon lidar is established regarding the surface reflectivity and the one-way transmittance of direct atmospheric light.

[0053] Based on the signal model of single-photon lidar, we obtain the expression for the theoretically measured apparent surface reflectance, and the expression for the theoretically measured apparent surface reflectance with respect to the surface reflectance and the one-way transmittance of direct atmospheric light.

[0054] The atmospheric direct one-way transmittance is expressed as aerosol optical thickness, and the theoretically measured expression of apparent surface reflectance with respect to surface reflectance and atmospheric direct one-way transmittance is substituted into it to establish a theoretical mapping relationship between apparent surface reflectance and aerosol optical thickness.

[0055] Furthermore, the mathematical expression for the theoretical mapping relationship between apparent surface reflectance and surface reflectance and aerosol optical thickness is as follows:

[0056]

[0057] In the formula, r app_theo The theoretically calculated value representing the apparent surface reflectivity; f signal ( . This represents a mapping relationship based on a signal model; r s It is the surface reflectance; t o3 It is the optical thickness of ozone; t R Represents Rayleigh Optical thickness; t a Represents the optical thickness of the aerosol; i v It is the zenith angle of the sensor.

[0058] As a specific implementation method, the detailed derivation process of the theoretical mapping relationship between atmospheric top reflectivity and surface reflectivity and aerosol optical thickness is as follows:

[0059] Based on the signal model of single-photon lidar, for single-photon lidar with known system parameters (including laser parameters, transceiver optical system parameters, detector parameters, etc.), since the ozone layer optical thickness is stable and the atmospheric Rayleigh optical thickness can be estimated from the ground atmospheric pressure, the apparent surface reflectivity is affected by two unknown parameters: the surface reflectivity and the aerosol optical thickness. A theoretical mapping relationship can be established.

[0060] Referring to the system parameters of a single-photon lidar, the signal model of a single-photon lidar can be expressed as: the average number of photons received on the Lambertian surface. N s Mathematically, it is represented as:

[0061] (1)

[0062] In the formula, E t This is the emission energy of a single-photon lidar (with emission system efficiency already taken into account). or q It refers to the quantum efficiency of photodetectors. or r It is the efficiency of the receiver system. A r It refers to the size of the receiving telescope aperture. h It is Planck's constant. u It is the photon frequency. h u The energy representing a single photon F It is the scaling factor of the lidar system. D c It is the detector dead time correction factor. R h This refers to the flight altitude of the lidar. The above are the instrument parameters related to the single-photon lidar system. T The atmospheric direct sunlight transmittance in one pass; r s It is the surface reflectance; i g It is the angle of incidence of the laser relative to the surface, and is affected by the nadir angle of laser incidence. i v In conjunction with the ground tilt angle, when i g When less than 10°, cos i g A value greater than 0.98 can be approximated as 1.

[0063] Considering the influence of the Earth's atmosphere, the apparent surface reflectivity provided by single-photon lidar is the measurement result of laser light transmitted from the spacecraft platform to the ground surface, reflected by the ground surface, and then transmitted back to the platform from the ground surface (simply put, the apparent surface reflectivity measured by lidar represents the transmission of laser light from the platform to the ground surface × the reflection by the ground surface × the transmission from the ground surface to the platform). Based on equation (1), the theoretically measured apparent surface reflectivity can be calculated as (assuming the ground is flat, cos... i g (Default is 1):

[0064] (2)

[0065] In the formula, r app_theo The theoretically calculated value representing the apparent surface reflectivity;

[0066] In the absence of clouds, the angle of incidence i v Atmospheric direct sunlight one-way transmittance T It can be approximated as:

[0067] (3)

[0068] In the formula, t o3 It is the ozone optical thickness, which is relatively stable and is set to a constant of 0.02; t R Represents Rayleigh optics thickness, calculated from the atmospheric pressure at the site; t a Represents the optical thickness of the aerosol, used to calculate the one-way transmittance of direct atmospheric light. T The only uncertain term; i v This represents the nadir angle at which the laser is incident.

[0069] By combining equations (2) and (3), the apparent surface reflectance can be established. r app_theo With surface reflectivity r s and aerosol optical thickness t a The theoretical mapping relationship between them is as follows:

[0070] (4)

[0071] Furthermore, in step 2, the process of constructing the theoretical mapping relationship between atmospheric top reflectivity and surface reflectivity and aerosol optical thickness is as follows:

[0072] Based on the system parameters of a single-photon lidar, a background noise model for the single-photon lidar is established, considering the surface reflectivity, atmospheric path radiation reflectivity, and atmospheric diffuse transmittance.

[0073] Based on the background model of single-photon lidar, we obtain the expression for the theoretical measurement of atmospheric top reflectivity, and its expression for surface reflectivity, atmospheric path radiation reflectivity, and atmospheric diffuse transmittance.

[0074] By expressing atmospheric path radiative reflectance and atmospheric diffuse transmittance as aerosol optical thickness, and substituting them into the theoretically measured expression for atmospheric top reflectance with respect to surface reflectance, atmospheric path radiative reflectance, and atmospheric diffuse transmittance, a theoretical mapping relationship between atmospheric top reflectance and surface reflectance and aerosol optical thickness is established.

[0075] Furthermore, the mathematical expression for the theoretical mapping relationship between atmospheric top reflectivity and surface reflectivity and aerosol optical thickness is as follows:

[0076]

[0077] In the formula, r toa_theo The theoretically calculated value representing the reflectivity at the top of the atmosphere; f noise (.) indicates a mapping relationship based on the background noise model; S atm It is the spherical albedo of the atmosphere; i v It is the zenith angle of the sensor. i s It is the zenith angle of the sun; oh a It is the single-scattering albedo of the aerosol; P R ( i- ) is the Rayleigh phase function. P a ( i- ) is the aerosol scattering phase function. i- This represents the scattering angle of light as it is scattered backward from the atmosphere.

[0078] As a specific implementation method, the theoretical mapping relationship between atmospheric top reflectivity and surface reflectivity and aerosol optical thickness is established as follows:

[0079] Based on the background noise model of single-photon lidar, for a single-photon lidar with known system parameters, the solar elevation angle at the measurement time is known, the albedo of the atmospheric surface can be determined by looking up a table, and the single-scattering albedo of the aerosol can be substituted with typical values. Thus, the reflectivity at the top of the atmosphere is affected by two unknown parameters: the surface reflectivity and the optical thickness of the aerosol. A theoretical mapping relationship can be established.

[0080] For single-photon lidar, scattered and reflected solar radiation is detected and recorded as background noise. The solar radiation received by the lidar from the top of the atmosphere (background noise) includes: solar noise received by the system after atmospheric reflection, solar noise received by the system after "atmospheric transmission - surface reflection - atmospheric transmission," and the dark count noise of the detector itself. Theoretically, the formula for calculating the total noise rate of a single-photon lidar (background noise model) is:

[0081] (5)

[0082] In the formula, f t This represents the total noise rate; the parameters within the first set of parentheses are instrument parameters related to the lidar system, among which... Dl It is the filter width. i r It is half of the receiving field of view; the parameters in the second set of parentheses are the environment and target parameters, among which, It is the solar irradiance at the average distance between the Earth and the Sun. r atm Atmospheric path reflectivity t ( i () indicates the angle of incidence. i Atmospheric diffuse transmittance ,the v This refers to the sensor's zenith angle (equal to the laser incident nadir angle; the laser incident nadir angle refers to the angle at which the laser beam deviates from vertical downwards when it is emitted and points towards the ground target; the sensor's zenith angle refers to the angle at which the noise signal, reflecting off the ground, deviates from vertical upwards when the solar signal is reflected back to the sensor. However, in spaceborne lidar measurements, the laser and sensor must be pointing towards the same ground area to receive the measurement signal, so the two angles are numerically identical and share the same symbol). i s It is the zenith angle of the sun. S atm It is the spherical albedo of the atmosphere, which can be found in a lookup table; f d It is the dark counting noise of the photon counting detector.

[0083] In the formula, , This represents the measured solar irradiance; the Day value represents the day of the year.

[0084] The theoretical atmospheric top reflectivity can be derived from equation (5). r toa_theo for:

[0085] (6)

[0086] Atmospheric path reflectivity r atm The contributions from aerosols and atmospheric molecules (or Rayleigh scattering) are approximated using the single-scattering approximation as follows:

[0087] (7)

[0088] In the formula, oh a This is the single-scattering albedo of the aerosol, set to a typical value of 0.95 for simplified calculation; P R ( i - ) is the Rayleigh phase function. P a ( i - ) is the aerosol scattering phase function. i - The scattering angle, representing the backscattering of light from the atmosphere, depends on the relative position between the satellite receiving system and the sun. At this point, the aerosol optical thickness... t a To calculate atmospheric path radiative reflectivity r atm The only uncertain item.

[0089] Angle of incidence i Atmospheric diffuse transmittance t (θ) Modeled by the following formula:

[0090] (8)

[0091] In the formula, F a It is the forward scattering fraction of aerosols, defined as the integral of the forward scattering part of the aerosol scattering phase function:

[0092] (9)

[0093] Marine scene aerosol F a The typical value is 0.85. At this point, the aerosol optical thickness... t a To calculate atmospheric diffuse transmittance t The only uncertain item.

[0094] By combining equations (6), (7), and (8), the atmospheric top reflectivity can be established. r toa_theo With surface reflectivity rs and aerosol optical thickness t a The theoretical mapping relationship between them is as follows:

[0095] (10)

[0096] Furthermore, in step 3, the calculation process for the measurement data of the apparent surface reflectance of the area to be measured and the reflectance at the top of the atmosphere is as follows:

[0097] By substituting the signal observation data of the area to be measured provided by the single-photon lidar into the expression for the theoretical measurement of the apparent surface reflectivity, the measurement data of the apparent surface reflectivity of the area to be measured is obtained; at the same time, by substituting the noise observation data of the area to be measured provided by the single-photon lidar into the expression for the theoretical measurement of the reflectivity of the top of the atmosphere, the measurement data of the reflectivity of the top of the atmosphere is obtained.

[0098] As a specific implementation method, the apparent surface reflectance, i.e., the surface reflectance considering atmospheric attenuation, can be estimated based on the signal observation data detected by single-photon lidar; the atmospheric top reflectance, i.e., the combination of apparent surface reflection and atmospheric reflection, can be estimated based on noise observation data. The calculation process for the measurement data of the apparent surface reflectance and atmospheric top reflectance of the area to be measured is as follows:

[0099] Let the average ground signal photon count along the orbit provided by the single-photon lidar (signal observation data) be denoted as N s, mea The background noise rate along the track (noise observation data) is f t,mea Then, combining the intermediate term of equation (2), the apparent surface reflectance along the orbit measured by single-photon lidar... r app,mea It can be calculated as follows:

[0100] (11)

[0101] Combining the intermediate term of equation (6), the reflectivity along the top of the orbital atmosphere measured by single-photon lidar. r toa,mea It can be calculated as follows:

[0102] (12)

[0103] Furthermore, in step 4, the inversion process of the surface reflectance and aerosol optical thickness parameters of the area to be measured is as follows:

[0104] The measured data of the apparent surface reflectance of the area to be measured are substituted into the theoretical mapping relationship of apparent surface reflectance with respect to surface reflectance and aerosol optical thickness. At the same time, the measured data of the atmospheric top reflectance of the area to be measured are substituted into the theoretical mapping relationship of atmospheric top reflectance with respect to surface reflectance and aerosol optical thickness. These are combined into a nonlinear bivariate equation, and the inversion results of the surface reflectance and aerosol optical thickness parameters are obtained by solving the equation.

[0105] As a specific implementation method, the apparent surface reflectance and atmospheric top reflectance measurement data of single-photon lidar are substituted into the theoretical mapping relationship between apparent surface reflectance, atmospheric top reflectance, surface reflectance, and aerosol optical thickness parameters for simultaneous solution.

[0106] Based on steps 1 and 2, we have established the theoretical mapping relationship between apparent surface reflectance and aerosol optical thickness as shown in equation (4). r app_theo = f signal ( t a , r s ), and the theoretical mapping relationship between atmospheric top reflectivity, surface reflectivity, and aerosol optical thickness as shown in Equation (10). r toa_theo = f noise ( t a , r s Based on step 3, we have obtained the apparent surface reflectance along the orbit measured by the single-photon lidar. r app,mea and atmospheric top reflectivity r toa,mea The above results can be combined into a nonlinear bivariate equation as follows:

[0107] (13)

[0108] Solving the above nonlinear bivariate equations yields the inversion results for surface reflectivity and aerosol optical thickness parameters.

[0109] This invention also provides an embodiment for acquiring surface reflectivity and aerosol optical thickness parameters based on the ICESat-2 satellite. The embodiment uses the ground signal photon count acquired by the ATLAS (Advanced Terrain Laser Altimeter System) onboard the ICESat-2 satellite as it flew over the North China Plain. sig_count ), background noise count ( backg_c Using the data as an example, the surface reflectance of the area to be measured is retrieved. r s and aerosol optical thickness t a Parameters. ICESat-2 / ATLAS can emit six laser pulses at a repetition rate of 10 kHz. Utilizing an extremely sensitive photon counting detector, it records both ground-based laser photons and atmospheric aerosol background noise reflected into the telescope. This background noise can mask weak signals, resulting in observations similar to those of passive optical sensors. ICESat-2 / ATLAS's range resolution allows for accurate separation of surface laser signals and atmospheric aerosol background noise, making it possible to perform active and passive fusion observations on a single platform with a single measurement.

[0110] Example analysis was conducted using data from ICESat-2's first orbit over the North China Plain on February 22, 2020, to retrieve surface reflectance and aerosol optical thickness parameters. Specifically, this study utilized ICESat-2's Level 3 ATL09 product (calibrated for atmospheric delay), which provides passive background noise counts statistically analyzed at a rate of 25 Hz. backg_c ), and ground signal photon information accumulated from 400 consecutive pulses. Among them, the ground signal photon information is categorized by high confidence ( sig_count_hi ), medium confidence level ( sig_count_med ) and low confidence ( sig_count_low ) Classification. In this example, the photon count of the signal ( sig_count )for sig_count_hi , sig_count_med and sig_count_low The sum. In addition, the ATL09 product provides the corresponding solar altitude angle with a timestamp ( solar_elevation ) and emission energy ( tx_pulse_energy These are essential input data for the proposed method. Solar altitude angle and solar zenith angle. i s The correlation is as follows: Solar altitude angle = 90° - i s The ATL09 product also includes data from the Goddard Office of Modeling and Assimilation (GMAO), including meteorological analysis or short-term forecasts of temperature, pressure, and humidity fields. This study uses surface pressure (…). met_ps () serves as an auxiliary input for the signal and background noise model.

[0111] This example uses Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol and terrestrial products as validation data, available from NASA's Distributed Active Archive Center for Terrestrial Processes. Specifically, the MODIS MAIA C terrestrial aerosol optical thickness product (MCD19A2) provides 1 km resolution green band aerosol optical thickness parameters (…). Optical_Depth_055 This can be used as validation data; the MODIS two-way reflectance distribution function (BRDF) and albedo product (MCD43) provide kernel weight parameters for the isotropic scattering components in the green band. f iso (MCD43D10, BRDF_ Albedo_Parameter1_Band4 Kernel weight parameters for RossThick volume scattering components f vol (MCD43D11, BRDF_ Albedo_Parameter2_Band4 Kernel weight parameters of LiSparse-Reciprocal geometric scattering components f geo (MCD43D12, BRDF_Albedo_Parameter3_Band4 ).Will f iso , f vol and f geo Substituting the data into the RTLSR BRDF model, the BRDF-corrected surface reflectance parameters with a time resolution of 1 day and a spatial resolution of 1 kilometer can be calculated as validation data.

[0112] Table 1 lists the specific input and validation data.

[0113]

[0114] like Figure 2 As shown, the surface reflectance and aerosol optical thickness parameters of the area to be measured, obtained based on ICESat-2 data, include:

[0115] S1. Referring to the system parameters of ICESat-2, based on the signal and background noise model of single-photon lidar, theoretical mapping relationships are established between apparent surface reflectivity, top atmospheric reflectivity and surface reflectivity and aerosol optical thickness parameters, respectively.

[0116] S2. Using the track-side signal and noise observation data obtained by ICESat-2, obtain the apparent surface reflectance and top atmospheric reflectance measurement data along the track.

[0117] S3. By combining the measurement data with the theoretical mapping relationship, the surface reflectance and aerosol optical thickness parameters of the area to be measured are inverted.

[0118] S1 includes: referencing the system parameters of ICESat-2, and based on the signal and background noise model of single-photon lidar, establishing theoretical mapping relationships between apparent surface reflectivity, atmospheric top reflectivity, and surface reflectivity and aerosol optical thickness parameters.

[0119] The active signal of ICESat-2 is affected by target reflection characteristics, atmospheric attenuation, and the characteristics of the lidar instrument. The average photon count received by the ICESat-2 lidar on the Lambertian surface... N s It can be represented as:

[0120] (1-1)

[0121] In the formula, or q It refers to the quantum efficiency of photodetectors; or r It refers to the receiver system efficiency; E t This is the emission energy of the lidar system (the efficiency of the emission system has been taken into account). A r It refers to the size of the receiving telescope aperture; h It is Planck's constant; u It is the photon frequency; h u Represents the energy of a single photon. R h It is the flight altitude of the lidar; D c It is the detector dead time correction factor; F It is the scaling factor of the lidar system; T The atmospheric direct sunlight transmittance in one pass; r s It is the surface reflectance; i g It is the incident angle of the laser relative to the surface.

[0122] Considering the influence of the Earth's atmosphere, the apparent surface reflectance provided by ICESat-2 is the measurement result of laser light transmitted from the spacecraft platform to the Earth's surface, reflected by the surface, and then transmitted back to the platform. Based on equation (1), theoretically, the apparent surface reflectance measured by ICESat-2 is... r app_theo It can be calculated as follows:

[0123] (2-1)

[0124] In the absence of clouds, the angle of incidence i v Atmospheric direct sunlight one-way transmittance T It can be approximated as:

[0125] (3-1)

[0126] In the formula, t o3 It is the ozone optical thickness, which is relatively stable and can be set to a constant of 0.02; t R Represents Rayleigh optics thickness, which can be calculated from the atmospheric pressure on site; t a Represents the optical thickness of the aerosol, used to calculate the one-way transmittance of direct atmospheric light. T The only uncertain item.

[0127] By combining equations (2-1) and (3-1), the apparent surface reflectance can be established. r app_theo With surface reflectivity r s and aerosol optical thickness t a The theoretical mapping relationship between them is as follows:

[0128] (4-1)

[0129] For the ICESat-2 single-photon lidar, scattered and reflected solar radiation is detected and recorded as background noise. The solar radiation received by the lidar from the top of the atmosphere (background noise) includes: solar noise received by the system after atmospheric reflection, solar noise received by the system after "atmospheric transmission-surface reflection-atmospheric transmission," and the dark count noise of the detector itself. Theoretically, the total noise rate of ICESat-2 can be calculated as:

[0130] (5-1)

[0131] In the formula, the items in the first set of parentheses represent instrument parameters, where Dl It is the filter width. i r It is half of the receiving field of view; the items in the second set of parentheses represent environmental and target parameters, among which... It is the solar irradiance at the average distance between the Earth and the Sun, which can be expressed as ; i v It is the zenith angle of the sensor; i s It is the zenith angle of the sun; ratm Atmospheric path reflectivity; S atm It is the spherical albedo of the atmosphere, which can be found in a lookup table; f d This is the dark counting noise of the photon counting detector, for the ICESat-2 system. f d It is approximately 10 kHz.

[0132] The theoretical atmospheric top reflectivity can be derived from equation (5-1). r toa_theo for:

[0133] (6-1)

[0134] In the formula, atmospheric path reflectivity r atm The contributions from aerosols and atmospheric molecules (or Rayleigh scattering) can be approximated using the single-scattering approximation as follows:

[0135] (7-1)

[0136] In the formula, oh a This is the single-scattering albedo of the aerosol, which can be set to a typical value of 0.95 to simplify calculations; P R ( i - ) is the Rayleigh phase function. P a ( i - ) is the aerosol scattering phase function. i - The scattering angle, representing the backscattering of light from the atmosphere, depends on the relative position between the satellite receiving system and the sun. For the ICESat-2 system, i - It can be approximated as π - i s At this point, the aerosol optical thickness t a To calculate atmospheric path radiative reflectivity r atm The only uncertain item.

[0137] Angle of incidence i Atmospheric diffuse transmittance t It can be modeled by the following formula:

[0138] (8-1)

[0139] In the formula, F a It is the forward scattering fraction of aerosols, defined as the integral of the forward scattering part of the aerosol scattering phase function:

[0140] (9-1)

[0141] At this point, the aerosol optical thickness t a To calculate atmospheric diffuse transmittance t The only uncertain item.

[0142] By combining equations (6-1), (7-1), and (8-1), the atmospheric top reflectivity can be established. r toa_theo With surface reflectivity r s and aerosol optical thickness t a The theoretical mapping relationship between them is as follows:

[0143] (10-1)

[0144] S2 includes: using the measurement area along the orbital signal and noise observation data acquired by ICESat-2, to obtain measurement data of apparent surface reflectance and top atmospheric reflectance along the orbit.

[0145] Specifically, the ICESat-2 orbital average signal photon count N s It can be calculated as:

[0146] (11-1)

[0147] Combining the above equation with the system parameters of ICESat-2 and the intermediate term of equation (2-1), the apparent surface reflectance along the track measured by ICESat-2 is... r app,mea It can be calculated as follows:

[0148] (12-1)

[0149] Background noise rate along the track f t It can be represented as:

[0150] (13-1)

[0151] Combining the above equation with the system parameters of ICESat-2 and the intermediate term of equation (6-1), the reflectance along the top of the orbital atmosphere measured by ICESat-2 is... r toa,mea It can be calculated as follows:

[0152] (14-1)

[0153] S3 includes: combining measurement data with theoretical mapping relationships to realize the inversion of surface reflectance and aerosol optical thickness parameters of the area to be measured.

[0154] Based on S1, we have established the theoretical mapping relationship between apparent surface reflectance and aerosol optical thickness as shown in Equation (4-1). r app_theo = f signal ( t a , r s ), and the theoretical mapping relationship between atmospheric top reflectivity, surface reflectivity, and aerosol optical thickness as shown in equation (10-1). r toa_theo = f noise ( t a , r s According to S2, we have obtained the apparent surface reflectance along the orbit measured by ICESat-2. r app,mea and atmospheric top reflectivity r toa,mea The above results can be combined into a nonlinear bivariate equation as follows:

[0155] (15-1)

[0156] Solving the above nonlinear bivariate equations yields the inversion results for surface reflectivity and aerosol optical thickness parameters.

[0157] In this embodiment, surface reflectance and aerosol optical thickness parameters were inverted using data from ICESat-2's first orbit over the North China Plain on February 22, 2020. Figure 3 (a) shows the background noise rate (dark black solid line, to the left of the reference vertical axis) and the average signal photon count (light black dashed line, to the right of the reference vertical axis) at the corresponding latitude along the orbit. The two sets of data are calculated according to the process in S2 above, which is the measurement data of atmospheric top reflectivity and apparent surface reflectivity at the corresponding latitude along the orbit. Figure 3(b) shows the comparison between the aerosol optical thickness parameter inversion data (light black solid line) and the MODIS validation data (dark black dashed line) at the corresponding latitudes along the orbit. The aerosol optical thickness parameter results provided in the official ICESat-2 dataset ATL09 are also shown (light gray dashed line). The results show that the mean absolute percentage error (MAPE) of the official ATL09 aerosol optical thickness data compared to the MODIS validation data is 94.60%, and the root mean square error (RMSE) is 0.1410, indicating poor consistency between the two. The aerosol optical thickness parameters inverted by the above method have a MAPE of 26.76% and an RMSE of 0.0394 compared to the MODIS validation data, showing high consistency between the two. Figure 3 (c) This paper presents a comparison between the surface reflectance parameter inversion data (light black solid line) and the MODIS validation data (dark black dashed line) at the corresponding latitude along the orbit. The results show that the surface reflectance parameters obtained by the above method have a MAPE of 8.59% and an RMSE of 0.0145 compared to the MODIS validation data, indicating a high degree of consistency between the two. This invention can invert the surface reflectance and aerosol optical thickness parameters of the area under test using data obtained by single-photon lidar flying over different regions. This will help achieve large-scale, high-resolution monitoring of surface and aerosol characteristics and provide reliable data support for Earth observation.

[0158] The implementation of the various embodiments of the present invention is based on programmed processing through a system with processor functionality. Therefore, in practical engineering, the technical solutions and functions of the various embodiments of the present invention are encapsulated into various modules. Based on this reality, and building upon the above embodiments, the embodiments of the present invention provide a lidar-based surface and aerosol parameter inversion system, which is used to execute a lidar-based surface and aerosol parameter inversion method from the above method embodiments.

[0159] See Figure 4 The system includes:

[0160] The apparent surface reflectance mapping derivation module is used to establish a theoretical mapping relationship between apparent surface reflectance and surface reflectance and aerosol optical thickness based on the signal model of single-photon lidar. The atmospheric top reflectance mapping derivation module is used to establish a theoretical mapping relationship between atmospheric top reflectance and surface reflectance and aerosol optical thickness based on the background noise model of single-photon lidar. The measurement data acquisition module is used to calculate the measurement data of apparent surface reflectance and atmospheric top reflectance of the test area based on the signal and noise observation data of the test area provided by single-photon lidar. The parameter inversion module is used to combine the theoretical mapping relationship of apparent surface reflectance with surface reflectance and aerosol optical thickness, the theoretical mapping relationship of atmospheric top reflectance with surface reflectance and aerosol optical thickness, and the measurement data of apparent surface reflectance and atmospheric top reflectance of the test area to invert the surface reflectance and aerosol optical thickness parameters of the test area.

[0161] It should be noted that the system embodiments provided by the present invention are used not only to implement the methods in the above method embodiments, but also to implement the methods in other method embodiments provided by the present invention. The only difference is that corresponding functional modules are set. The principle is basically the same as that of the above system embodiments provided by the present invention. As long as those skilled in the art can improve the modules in the above system embodiments by referring to the specific technical solutions in other method embodiments and combining technical features to obtain corresponding technical means and technical solutions composed of these technical means, on the basis of the above system embodiments, and on the premise of ensuring the practicality of the technical solutions, they can obtain corresponding system-like embodiments for implementing the methods in other method-like embodiments.

[0162] The method in this embodiment of the invention is implemented using an electronic device; therefore, it is necessary to introduce the relevant electronic device. For this purpose, embodiments of the present invention provide an electronic device, such as... Figure 5 As shown, the electronic device includes: at least one processor, a communication interface, at least one memory, and a communication bus, wherein the at least one processor, the communication interface, and the at least one memory communicate with each other via the communication bus. The at least one processor invokes logical instructions stored in the at least one memory to execute all or part of the steps of the methods provided in the foregoing method embodiments.

[0163] Furthermore, when the logical instructions in at least one of the aforementioned memories are implemented as software functional units and sold or used as independent products, they are 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, is 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 (a personal computer, server, or network device) to execute all or part of the steps of the methods described in the various method embodiments of the present invention. The aforementioned storage medium includes: USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks—various media for storing program code.

[0164] The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, located in one place, or distributed across multiple network units. The purpose of this embodiment is achieved by selecting some or all of the modules according to actual needs. Those skilled in the art will understand and implement this without any inventive effort.

[0165] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0166] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure one One or more processes and / or boxes Figure one A device that provides the functions specified in one or more boxes.

[0167] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure one One or more processes and / or boxes Figure one The function specified in one or more boxes.

[0168] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure one One or more processes and / or boxes Figure one The steps of the function specified in one or more boxes.

[0169] Based on the same technical concept as the foregoing embodiments, the present invention provides a non-transitory computer-readable storage medium that stores computer instructions that cause the computer to execute a method for inverting surface and aerosol parameters based on lidar.

[0170] In summary, this invention discloses a method for simultaneously acquiring surface reflectance and aerosol optical thickness parameters based on single-photon lidar data, belonging to the field of laser remote sensing. Under the given conditions of along-orbit signal data and background noise data of the single-photon lidar measurement area, this invention inverts the surface reflectance and aerosol optical thickness parameters of the area to be measured. First, based on the signal and background noise model of the spaceborne single-photon lidar, theoretical mapping relationships are established between apparent surface reflectance, top atmospheric reflectance, and surface reflectance and aerosol optical thickness parameters. Second, using the along-orbit signal and noise observation data of the measurement area acquired by the single-photon lidar, measurement data of apparent surface reflectance and top atmospheric reflectance along the orbit are obtained. Then, combining the measurement data with the theoretical mapping relationship, the inversion of surface reflectance and aerosol optical thickness parameters of the area to be measured is finally achieved. This invention leverages the quantum-level sensitivity of single-photon lidar, making full use of its signal and noise observation data, enabling large-scale, high-resolution monitoring of surface and aerosol characteristics, providing reliable data support for Earth observation.

[0171] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the technical solutions of the embodiments of the present invention.

Claims

1. A method for inverting surface and aerosol parameters based on lidar, characterized in that, include: Based on the signal model of single-photon lidar, a theoretical mapping relationship between apparent surface reflectivity and surface reflectivity and aerosol optical thickness is established. Based on the background noise model of single-photon lidar, a theoretical mapping relationship between atmospheric top reflectivity and surface reflectivity and aerosol optical thickness is established. Substituting the signal observation data of the area to be measured provided by the single-photon lidar into the expression for theoretical measurement of apparent surface reflectivity, the measurement data of apparent surface reflectivity of the area to be measured is obtained; at the same time, substituting the noise observation data of the area to be measured provided by the single-photon lidar into the expression for theoretical measurement of atmospheric top reflectivity, the measurement data of atmospheric top reflectivity is obtained. By combining the theoretical mapping relationship between apparent surface reflectance and surface reflectance and aerosol optical thickness, the theoretical mapping relationship between atmospheric top reflectance and surface reflectance and aerosol optical thickness, and the measured data of apparent surface reflectance and atmospheric top reflectance of the area to be measured, the parameters of surface reflectance and aerosol optical thickness of the area to be measured are obtained by inversion.

2. The method for inverting surface and aerosol parameters based on lidar as described in claim 1, characterized in that, The steps for establishing the theoretical mapping relationship between apparent surface reflectance and surface reflectance and aerosol optical thickness are as follows: Based on the system parameters of a single-photon lidar, a signal model for the single-photon lidar is established regarding the surface reflectivity and the one-way transmittance of direct atmospheric light. Based on the signal model of single-photon lidar, we obtain the expression for the theoretically measured apparent surface reflectance, and the expression for the theoretically measured apparent surface reflectance with respect to the surface reflectance and the one-way transmittance of direct atmospheric light. The atmospheric direct one-way transmittance is expressed as aerosol optical thickness, and the theoretically measured apparent surface reflectance is substituted into the expression for the relationship between the surface reflectance and the atmospheric direct one-way transmittance to establish a theoretical mapping relationship between the apparent surface reflectance and the aerosol optical thickness.

3. The method for inverting surface and aerosol parameters based on lidar as described in claim 2, characterized in that, The mathematical expression for the theoretical mapping relationship between apparent surface reflectance and aerosol optical thickness is as follows: ； In the formula, ρ app_theo The theoretically calculated value representing the apparent surface reflectivity; f signal ( . This represents a mapping relationship based on a signal model; ρ s It is the surface reflectance; τ o3 It is the optical thickness of ozone; τ R Represents Rayleigh Optical thickness; τ a Represents the optical thickness of the aerosol; θ v It is the zenith angle of the sensor.

4. The method for inverting surface and aerosol parameters based on lidar as described in claim 3, characterized in that, The process of constructing the theoretical mapping relationship between atmospheric top reflectivity and surface reflectivity and aerosol optical thickness is as follows: Based on the system parameters of a single-photon lidar, a background noise model for the single-photon lidar is established, considering the surface reflectivity, atmospheric path radiation reflectivity, and atmospheric diffuse transmittance. Based on the background model of single-photon lidar, we obtain the expression for the theoretical measurement of atmospheric top reflectivity, and its expression for surface reflectivity, atmospheric path radiation reflectivity, and atmospheric diffuse transmittance. By expressing atmospheric path radiative reflectance and atmospheric diffuse transmittance as aerosol optical thickness, and substituting them into the theoretically measured expression for atmospheric top reflectance with respect to surface reflectance, atmospheric path radiative reflectance, and atmospheric diffuse transmittance, a theoretical mapping relationship between atmospheric top reflectance and surface reflectance and aerosol optical thickness is established.

5. The method for inverting surface and aerosol parameters based on lidar as described in claim 4, characterized in that, The mathematical expression for the theoretical mapping relationship between atmospheric top reflectivity and surface reflectivity and aerosol optical thickness is as follows: ； In the formula, ρ toa_theo The theoretically calculated value representing the reflectivity at the top of the atmosphere; f noise (.) indicates a mapping relationship based on the background noise model; S atm It is the spherical albedo of the atmosphere; θ s It is the zenith angle of the sun; ω a It is the single-scattering albedo of the aerosol; P R ( θ- ) is the Rayleigh phase function. P a ( θ- ) is the aerosol scattering phase function. θ- This represents the scattering angle of light as it is scattered backward from the atmosphere. It is the forward scattering fraction of aerosols.

6. The method for inverting surface and aerosol parameters based on lidar as described in claim 5, characterized in that, The inversion process of the surface reflectance and aerosol optical thickness parameters of the area to be measured is as follows: The measured data of the apparent surface reflectance of the area to be measured are substituted into the theoretical mapping relationship of apparent surface reflectance with respect to surface reflectance and aerosol optical thickness. At the same time, the measured data of the atmospheric top reflectance of the area to be measured are substituted into the theoretical mapping relationship of atmospheric top reflectance with respect to surface reflectance and aerosol optical thickness. These are combined into a nonlinear bivariate equation, and the inversion results of the surface reflectance and aerosol optical thickness parameters are obtained by solving the equation.

7. A surface and aerosol parameter inversion system based on lidar, characterized in that, include: The apparent surface reflectance mapping derivation module is used to establish a theoretical mapping relationship between apparent surface reflectance and surface reflectance and aerosol optical thickness based on the signal model of single-photon lidar. The top atmospheric reflectivity mapping derivation module is used to establish a theoretical mapping relationship between top atmospheric reflectivity and surface reflectivity and aerosol optical thickness based on the background noise model of single-photon lidar. The measurement data acquisition module is used to substitute the signal observation data of the area to be measured provided by the single-photon lidar into the expression for theoretical measurement of apparent surface reflectivity to obtain the measurement data of apparent surface reflectivity of the area to be measured; at the same time, it substitutes the noise observation data of the area to be measured provided by the single-photon lidar into the expression for theoretical measurement of atmospheric top reflectivity to obtain the measurement data of atmospheric top reflectivity. The parameter inversion module is used to combine the theoretical mapping relationship between apparent surface reflectance and surface reflectance and aerosol optical thickness, the theoretical mapping relationship between atmospheric top reflectance and surface reflectance and aerosol optical thickness, and the measured data of apparent surface reflectance and atmospheric top reflectance of the area to be measured, to invert and obtain the surface reflectance and aerosol optical thickness parameters of the area to be measured.

8. An electronic device, characterized in that, The method includes a memory and a processor, the memory storing program instructions that are executed by the processor, the processor invoking the program instructions to perform the method according to any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium, characterized in that, The non-transitory computer-readable storage medium stores computer instructions that cause the computer to perform the method described in any one of claims 1 to 6.

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