CN117110216A

CN117110216A - Aerosol optical thickness remote sensing inversion method and device and electronic equipment

Info

Publication number: CN117110216A
Application number: CN202311353173.7A
Authority: CN
Inventors: 杨富坤; 张晗; 王宇翔; 陈彦红; 宋毅
Original assignee: Aerospace Hongtu Information Technology Co Ltd
Current assignee: Aerospace Hongtu Information Technology Co Ltd
Priority date: 2023-10-19
Filing date: 2023-10-19
Publication date: 2023-11-24
Anticipated expiration: 2043-10-19
Also published as: CN117110216B

Abstract

The invention provides a remote sensing inversion method, a remote sensing inversion device and electronic equipment for aerosol optical thickness, which relate to the technical field of remote sensing, wherein a lookup table is firstly established when the remote sensing inversion of the aerosol optical thickness is carried out, then a MERSI II blue band surface reflectivity database under the conditions of month scale, different azimuth angles and different scattering angles is constructed based on MODIS surface reflectivity products, historical MERSI II data and AERONET data, then apparent reflectivity calculated data are obtained through calculation, and then matched apparent reflectivity calculated data matched with apparent reflectivity actual data are obtained, and the corresponding aerosol optical thickness data is obtained through table look-up in the lookup table. Therefore, the earth surface information under the month scale, different azimuth angles and different scattering angles can be effectively extracted, and the underestimation of earth surface reflectivity is avoided, so that a stable earth surface reflectivity library is provided, and the inversion accuracy of the aerosol optical thickness is further improved.

Description

Aerosol optical thickness remote sensing inversion method and device and electronic equipment

Technical Field

The invention relates to the technical field of remote sensing, in particular to an aerosol optical thickness remote sensing inversion method, an aerosol optical thickness remote sensing inversion device and electronic equipment.

Background

The satellite inversion aerosol is an efficient and reliable aerosol monitoring means, and has important significance for researching and controlling aerosol pollution. Because the inversion result of the aerosol optical thickness is biased due to the influence of the surface reflectivity, removing the influence of the surface reflectivity is one of the key problems of inversion of the aerosol optical thickness, and the accuracy and reliability of the inversion result can be improved.

There are currently a few commercialized algorithms widely used in aerosol optical thickness inversion, mainly including Dark pixel algorithm (Dark Target) and Deep Blue algorithm (Deep Blue). The dark pixel algorithm is an aerosol optical thickness inversion algorithm developed by NASA Goddard Space Flight Center, and the aerosol optical thickness is estimated by utilizing the earth surface reflectivity relation existing between a visible light wave band and an infrared wave band; the algorithm is based on satellite remote sensing data and ground measurement data for many years, has higher precision and stability, but can not invert the high-brightness earth surface areas such as deserts, cities and the like. The deep blue algorithm can remove the earth's surface contribution using stronger atmospheric reflection and weaker earth's surface reflection features at the blue light; the algorithm needs prior surface information, and then inverts the aerosol optical thickness according to satellite signals, so that the problem of missing inversion of a dark pixel algorithm on a highlight area can be effectively solved.

As defined by the deep blue algorithm idea, prior earth surface information is needed, when earth surface information is constructed, the traditional method adopts the minimum reflectivity synthesis technology (Minimum Reflectivity Technique, MRT), a certain number of images with different time are mainly considered in the synthesis process, the minimum value is searched for as a target value in the pixels at the same position, and estimation of the earth surface information can be reduced in practice, so that the inversion accuracy of the aerosol optical thickness is affected.

Disclosure of Invention

The invention aims to provide an aerosol optical thickness remote sensing inversion method, an aerosol optical thickness remote sensing inversion device and electronic equipment, so as to improve inversion accuracy of aerosol optical thickness.

In a first aspect, an embodiment of the present invention provides an aerosol optical thickness remote sensing inversion method, including:

according to the radiation transmission model, a lookup table of Cheng Fushe reflectivity, hemispherical reflectivity and atmospheric transmittance under set parameters is established; the set parameters comprise a solar zenith angle, an observation zenith angle, a relative azimuth angle between the sun and a satellite and an aerosol optical thickness;

constructing a MERSI II blue band surface reflectivity library under the moon scale, different azimuth angles and different scattering angles based on a medium resolution imaging spectrometer MODIS surface reflectivity product, historical MERSI II data and aerosol automatic monitoring network AERONET data;

According to Cheng Fushe reflectivity, hemispherical reflectivity and atmospheric transmittance in the lookup table and surface reflectivity data in the MERSI II blue band surface reflectivity library, calculating by using a radiation transmission equation to obtain apparent reflectivity calculation data;

and performing numerical comparison on the apparent reflectivity calculation data and the apparent reflectivity actual data obtained by calculation based on the current MERSI II data to obtain matched apparent reflectivity calculation data matched with the apparent reflectivity actual data, and looking up a table in the lookup table to obtain corresponding aerosol optical thickness data.

Further, the AERONET data comprises AERONET aerosol optical thickness data; the method for constructing the MERSI II blue band surface reflectivity library based on the medium resolution imaging spectrometer MODIS surface reflectivity product, historical MERSI II data and aerosol automatic monitoring network AERONET data comprises the following steps of:

performing monthly statistics on historical data of the MODIS surface reflectivity product, and selecting pixels meeting each angle condition from the corresponding multi-view images of each month according to a plurality of preset angle conditions; the historical data comprises blue wave band data with the resolution of 500 meters and red wave band data with the resolution of 250 meters, and the angle condition comprises that an azimuth angle and a scattering angle are respectively in corresponding angle ranges;

For each angle condition of each month, determining the coincidence number of each pixel which accords with the angle condition under the blue wave band data and the red wave band data respectively, and determining the blue wave band surface reflectivity and the red wave band surface reflectivity of the pixel under the angle condition of each month according to the corresponding coincidence number of each pixel to obtain a 500 m resolution MODIS blue wave band surface reflectivity library and a 250 m resolution MODIS red wave band surface reflectivity library;

constructing a first conversion relation according to the 500-meter resolution MODIS blue wave band surface reflectivity library and the 250-meter resolution MODIS red wave band surface reflectivity library to obtain a 250-meter resolution MODIS blue wave band surface reflectivity library;

converting the historical MERSI II data into historical MERSI II blue band apparent reflectance data;

according to the historical MERSI II blue wave band apparent reflectivity data and AERONET aerosol optical thickness data of the corresponding position, calculating to obtain 250 m resolution MERSI II blue wave Duan Ri scale earth surface reflectivity point data by utilizing a radiation transmission equation;

extracting 250 m resolution MERSI II blue waves Duan Yue scale surface reflectivity point data according to the 250 m resolution MERSI II blue waves Duan Ri scale surface reflectivity point data;

And constructing a second conversion relation according to the data of the surface reflectivity points of the size of the 250 m resolution MERSI II blue wave Duan Yue and the surface reflectivity library of the 250 m resolution MODIS blue wave band, and obtaining the surface reflectivity library of the 250 m resolution MERSI II blue wave band.

Further, according to the corresponding coincidence number of each pixel, determining the blue band surface reflectivity and the red band surface reflectivity of the pixel under the condition of the angle of the month, including:

when the coincidence number is smaller than or equal to 1, determining that the corresponding wave band earth surface reflectivity of the pixel under the condition of the angle of the month does not exist;

when the number of the coincidence is equal to 2, determining that the surface reflectivity of the pixel in the corresponding wave band under the angle condition of the month is the average value of the two surface reflectivities which are in accordance with the angle condition;

and when the coincidence number is more than 2 and is smaller than or equal to N/2-1, determining that the corresponding band surface reflectivity of the pixel under the angle condition of the month is the average value of the second small surface reflectivity and the third small surface reflectivity which are in accordance with the angle condition.

Further, the first conversion relation includes:

；

wherein,representing different months M and different relative azimuth angles +.A. in the 250M resolution MODIS red band surface reflectivity library >Different scattering angles->The surface reflectivity of the MODIS blue wave band,representing different months M and different relative azimuth angles +.A. in the 250M resolution MODIS red band surface reflectivity library>Different scattering angles->The ground surface reflectivity of MODIS red wave band is respectively, < ->、/>Representing different months M, different relative angles +.>Different scattering angles->The lower conversion coefficient.

Further, the converting the historical MERSI II data to historical MERSI II blue band apparent reflectance data includes:

converting DN value of each pixel in the historical MERSI II data into corresponding apparent reflectivity in the historical MERSI II blue band apparent reflectivity data by the following formula：

；

Wherein,、/>、/>respectively, a given scaling factor,/->Represents the distance between the day and the earth, < >>Representing the sun zenith angle cosine.

carrying out monthly statistics on blue wave band data with the resolution of 500 meters in the MODIS surface reflectivity product, and selecting pixels meeting each angle condition from the corresponding multi-view images per month according to a plurality of preset angle conditions; wherein the angle condition comprises that the azimuth angle and the scattering angle are respectively in corresponding angle ranges;

For each angle condition of each month, determining the coincidence number of each pixel in accordance with the angle condition, and determining the blue wave band surface reflectivity of the pixel under the angle condition of each month according to the coincidence number of each pixel to obtain a 500 m resolution MODIS blue wave band surface reflectivity library;

downsampling and monthly scale extraction are carried out on the data of the earth surface reflectivity points with the resolution of 250 meters and the resolution of MERSI II blue waves Duan Ri, so as to obtain data of the earth surface reflectivity points with the resolution of 500 meters and the resolution of MERSI II blue waves Duan Yue;

and constructing a second conversion relation according to the 500-meter resolution MERSI II blue wave Duan Yue scale earth surface reflectivity point data and the 500-meter resolution MODIS blue wave band earth surface reflectivity library to obtain the 500-meter resolution MERSI II blue wave band earth surface reflectivity library.

Further, the MODIS surface reflectance product includes blue band data of 500 m resolution MOD 09.

In a second aspect, an embodiment of the present invention further provides an aerosol optical thickness remote sensing inversion apparatus, including:

the establishing module is used for establishing a lookup table of Cheng Fushe reflectivity, hemispherical reflectivity and atmospheric transmittance under set parameters according to the radiation transmission model; the set parameters comprise a solar zenith angle, an observation zenith angle, a relative azimuth angle between the sun and a satellite and an aerosol optical thickness;

the construction module is used for constructing a MERSI II blue band surface reflectivity library under the moon scale, different azimuth angles and different scattering angles based on a medium resolution imaging spectrometer MODIS surface reflectivity product, historical MERSI II data and aerosol automatic monitoring network AERONET data;

the calculation module is used for calculating apparent reflectivity calculation data by utilizing a radiation transmission equation according to Cheng Fushe reflectivity, hemispherical reflectivity and atmospheric transmittance in the lookup table and the surface reflectivity data in the MERSI II blue band surface reflectivity library;

the inversion module is used for carrying out numerical comparison on the apparent reflectivity calculation data and the apparent reflectivity actual data obtained based on the current MERSI II data to obtain matched apparent reflectivity calculation data matched with the apparent reflectivity actual data, and looking up a table in the lookup table to obtain corresponding aerosol optical thickness data.

In a third aspect, an embodiment of the present invention further provides an electronic device, including a memory, and a processor, where the memory stores a computer program that can run on the processor, and when the processor executes the computer program, the aerosol optical thickness remote sensing inversion method in the first aspect is implemented.

In a fourth aspect, an embodiment of the present invention further provides a computer readable storage medium, where a computer program is stored, where the computer program is executed by a processor to perform the aerosol optical thickness remote sensing inversion method according to the first aspect.

According to the aerosol optical thickness remote sensing inversion method, the aerosol optical thickness remote sensing inversion device and the electronic equipment, when aerosol optical thickness remote sensing inversion is carried out, a lookup table of Cheng Fushe reflectivity, hemispherical reflectivity and atmospheric transmittance under set parameters is established according to a radiation transmission model; the set parameters comprise solar zenith angle, observation zenith angle, relative azimuth angle between the sun and the satellite and aerosol optical thickness; then constructing a MERSI II blue band surface reflectivity library under the moon scale, different azimuth angles and different scattering angles based on a medium resolution imaging spectrometer MODIS surface reflectivity product, historical MERSI II data and aerosol automatic monitoring network AERONET data; according to Cheng Fushe reflectivity, hemispherical reflectivity and atmospheric transmissivity in the lookup table and surface reflectivity data in a MERSI II blue band surface reflectivity library, calculating by using a radiation transmission equation to obtain apparent reflectivity calculation data; and further, comparing the apparent reflectivity calculated data with the apparent reflectivity actual data calculated based on the current MERSI II data in a numerical mode to obtain matched apparent reflectivity calculated data matched with the apparent reflectivity actual data, and looking up a table in a lookup table to obtain corresponding aerosol optical thickness data. Therefore, the multi-angle reflectivity conversion technology is adopted when the aerosol optical thickness remote sensing inversion is carried out, so that the earth surface information under the month scale, different azimuth angles and different scattering angles can be effectively extracted, the earth surface reflectivity is prevented from being underestimated, a stable earth surface reflectivity library is provided, and the inversion precision of the aerosol optical thickness is further improved.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.

FIG. 1 is a schematic flow chart of an aerosol optical thickness remote sensing inversion method provided by an embodiment of the invention;

FIG. 2 is a schematic flow chart of another aerosol optical thickness remote sensing inversion method according to an embodiment of the present invention;

FIG. 3 is a schematic structural diagram of an aerosol optical thickness remote sensing inversion device according to an embodiment of the present invention;

fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.

Detailed Description

The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

The intensity and wavelength characteristics of the surface reflectivity are related to the optical properties of the aerosol, so that the surface reflectivity can interfere with and affect the inversion of the aerosol optical thickness. The intensity and wavelength characteristics of the surface reflectivity can change along with the change of factors such as the surface type, vegetation coverage, surface state and the like, so that the influence of the surface reflectivity has different influences on aerosol optical thickness inversion of different surface types. In some cases, the intensity of the surface reflectivity may even exceed the signal intensity of the aerosol optical thickness, so the effect of the surface reflectivity needs to be removed to accurately invert the aerosol optical thickness.

The FY3D (Fengyun No. three D) satellite-mounted medium resolution imaging spectrometer type II (MERSI II) can effectively monitor aerosol. Although the band configuration of the MERSI II instrument has the conditions of realizing the dark pixel algorithm, the defects existing in the dark pixel algorithm cannot be overcome. To obtain a wider and stable coverage of the aerosol optical thickness, inversion of the aerosol optical thickness can be achieved using the blue band wavelength of the MERSI II instrument. Based on the above, the aerosol optical thickness remote sensing inversion method, the aerosol optical thickness remote sensing inversion device and the electronic equipment provided by the embodiment of the invention aim at the problems existing in the construction of the existing surface reflectivity, and perform land aerosol optical thickness remote sensing inversion of FY3D satellite data based on a Multi-angle reflectivity conversion technology (Multi-angle Reflectivity Transform Technology, MRTT), so that a stable surface reflectivity library can be provided, and further the aerosol optical thickness inversion precision is improved.

For the convenience of understanding the present embodiment, the aerosol optical thickness remote sensing inversion method disclosed in the embodiment of the present invention is first described in detail.

The embodiment of the invention provides an aerosol optical thickness remote sensing inversion method which can be executed by electronic equipment with data processing capability and can be applied to land aerosol optical thickness remote sensing inversion of different satellite data. Referring to a schematic flow chart of an aerosol optical thickness remote sensing inversion method shown in fig. 1, the method mainly includes the following steps S102 to S108:

step S102, a lookup table of Cheng Fushe reflectivity, hemispherical reflectivity and atmospheric transmittance under set parameters is established according to the radiation transmission model.

The set parameters comprise solar zenith angle, observation zenith angle, relative azimuth angle between the sun and the satellite and aerosol optical thickness. Through the lookup table, the Cheng Fushe reflectivity, hemispherical reflectivity, the atmospheric transmittance of the solar zenith angle and the atmospheric transmittance of the observed zenith angle under different solar zenith angles, observed zenith angles, relative azimuth angles and aerosol optical thicknesses can be found.

In particular implementations, look-Up tables (LUTs) may be constructed using, for example, a 6S radiation delivery model (or a 6SV radiation delivery model, etc.). The main set observation geometries include: 9 solar zenith angles (0-80 degrees apart by 10 degrees), 9 observation zenith angles (0-80 degrees apart by 10 degrees), and relative azimuth angles between 10 sun and satellite (0-180 degrees apart by 20 degrees); aerosol optical thickness: 20 (0.05, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.8, 1.0, 1.2, 1.4, 1.6, 1.8, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5); the aerosol mode adopts uniform continental aerosol.

Step S104, constructing a MERSI II blue band surface reflectivity library under the moon scale, different azimuth angles and different scattering angles based on the MODIS surface reflectivity product of the medium resolution imaging spectrometer, the historical MERSI II data and the aerosol automatic monitoring network AERONET data.

Alternatively, the MODIS (Moderate-resolution Imaging Spectroradiometer imaging spectrometer) surface reflectance product may include blue band data at a resolution of MOD09 of 500 meters. AERONET (Aerosol Robotic Network, aerosol automatic monitoring network) data may include AERONET aerosol optical thickness data. Considering that the resolution of MERSI II data is 250 meters and the resolution of blue band data in the MODIS surface reflectance product is 500 meters, the resolution of both needs to be unified first.

To ensure accuracy, the resolution of blue band data in the MODIS surface reflectivity product may be adjusted to be the same as the resolution of MERSI II data, based on which, in some possible embodiments, the above step S104 may be implemented by the following substep a1 to substep a 7:

a sub-step a1, carrying out monthly statistics on historical data of MODIS surface reflectivity products, and selecting pixels meeting each angle condition from the corresponding multi-view images of each month aiming at a plurality of preset angle conditions; the historical data comprise blue wave band data with the resolution of 500 meters and red wave band data with the resolution of 250 meters, and the angle condition comprises that an azimuth angle and a scattering angle are respectively in corresponding angle ranges;

Considering that the MODIS surface reflectance product further includes red band data with a resolution of 250 meters, which is the same as the resolution of MERSI II data, resolution adjustment can be performed on blue band data with a resolution of 500 meters based on the red band data. Therefore, the blue wave band data and the red wave band data in the MODIS surface reflectivity product are respectively subjected to monthly statistics and pixel selection under different angle conditions. Wherein the size of the picture element corresponds to the resolution, e.g. at a resolution of 500 meters, the size of the picture element is 500 meters; at a resolution of 250 meters, the size of the picture elements is 250 meters.

In specific implementation, the relative azimuth angle can be divided into two types, and the relative azimuth angle is more than or equal to 90 DEG and is called a forward relative azimuth angle #) The azimuth angle is smaller than 90 DEG and is called backward relative azimuth angle (+)>). Based on the relative azimuth angles of the front and back directions, the scattering angle (++>) Divided into intervals of 45 deg.. Each of the thus divided sets of relative azimuth and scatter angle ranges corresponds to an angular condition. It should be noted that the relative azimuth angle and the scattering angle may be divided according to actual requirements, for example, in other embodiments, the relative azimuth angle may be equally divided into four types, and the scattering angle may be divided into 30 ° and one interval, etc. The monthly statistics herein refers to pixel selection under different angle conditions for all data of the same month in the historical data, for example, for MOD is surface reflectivity product data MOD09 in 2013 to 2022, taking 1 month as an example, pixel selection under different angle conditions is performed for all data of 1 month in 2013 to 2022 respectively.

And a2, for each angle condition of each month, determining the coincidence number of each pixel which accords with the angle condition under the blue wave band data and the red wave band data respectively, and determining the blue wave band surface reflectivity and the red wave band surface reflectivity of each pixel under the angle condition of each month according to the corresponding coincidence number of each pixel to obtain a 500 m resolution MODIS blue wave band surface reflectivity library and a 250 m resolution MODIS red wave band surface reflectivity library.

The calculation mode of the earth surface reflectivity corresponds to the coincidence number, and when the coincidence number is smaller than or equal to 1, the earth surface reflectivity of the pixel in the corresponding wave band under the angle condition of the month is determined to be absent; when the number of the earth surface reflectivities is equal to 2, determining that the earth surface reflectivities of the corresponding wave bands of the pixel under the angle condition of the month are the average value of the two earth surface reflectivities which are in accordance with the angle condition; when the number of the corresponding wave bands is more than 2 and is less than or equal to N/2-1, determining that the surface reflectivity of the pixel in the corresponding wave band under the angle condition of the month is the average value of the second small surface reflectivity and the third small surface reflectivity which are in accordance with the angle condition.

It should be noted that, the corresponding relation between the calculation mode of the surface reflectivity and the number of the surface reflectivity can be set according to the actual requirement, and the calculation mode of the surface reflectivity can also be set according to the actual requirement, which is not limited by the embodiment of the present invention.

And a sub-step a3, constructing a first conversion relation according to the MODIS blue wave band surface reflectivity library with the resolution of 500 meters and the MODIS red wave band surface reflectivity library with the resolution of 250 meters to obtain the MODIS blue wave band surface reflectivity library with the resolution of 250 meters.

For different months M and different relative angles of positionDifferent scattering angles->MODIS red band surface reflectance under the condition +.>And blue band surface reflectivity->And constructing a conversion relation in turn.

In some possible embodiments, the first conversion relationship comprises:

；

wherein,representing different months M and different relative angles in a surface reflectivity library of a MODIS red wave band with a resolution of 250 meters +.>Different scattering angles->Surface reflectivity of MODIS blue band, < ->Representing different months M and different relative angles in a surface reflectivity library of a MODIS red wave band with a resolution of 250 meters +.>Different scattering angles->The ground surface reflectivity of MODIS red wave band is respectively, < ->、/>Representing different months M, different relative angles +.>Different scattering angles->The lower conversion coefficient.

Substep a4, converting the historical MERSI II data into historical MERSI II blue band apparent reflectance data.

MERSI II per track observation is cut, for example, to 5 min/scene, and the data storage format may be HDF5 format. The conversion of DN (Digital Number) values to apparent reflectance TOA (Top-of-Atmosphere) is required in combination with scaling coefficients before quantitative application.

In some possible embodiments, DN values for each pixel in the historical MERSI II data may be converted to corresponding apparent reflectivities in the historical MERSI II blue band apparent reflectivity data by the following equation：

；

Wherein,、/>、/>respectively, represent a given scaling factor,/>represents the distance between the day and the earth, < >>Representing the sun zenith angle cosine.

And a sub-step a5, according to the historical MERSI II blue wave band apparent reflectivity data and AERONET aerosol optical thickness data of the corresponding position, calculating to obtain the surface reflectivity point data of the 250 m resolution MERSI II blue wave Duan Ri scale by using a radiation transmission equation.

The MODIS and the MERSI II are different sensors, and the spectral response functions of the MODIS and the MERSI II are different, so that the conversion relation between the MODIS and the MERSI II needs to be constructed to eliminate the spectral difference between the sensors. The conversion relation between MODIS blue wave band surface reflectivity and MERSI II blue wave band surface reflectivity of the corresponding positions can be matched, and the conversion relation between MODIS and MERSI II is constructed, so that the data of the Duan Ri-scale surface reflectivity point of the MERSI II blue wave is needed to be obtained first, the data of the Duan Yue-scale surface reflectivity point of the MERSI II blue wave is obtained, and then the data of the Duan Yue-scale surface reflectivity point of the MERSI II blue wave is matched with an MODIS blue wave band surface reflectivity library under the lunar scale, and the conversion relation is constructed. MERSI II blue Duan Ri scale surface reflectance point data can be obtained by: and extracting apparent reflectivity information of the Mersi II blue wave band by utilizing longitude and latitude information of the AERONET foundation site, calculating real earth surface reflectivity of the Mersi II blue wave band by utilizing a radiation transmission equation in combination with AERONET aerosol optical thickness data of a corresponding position, and constructing a blue wave band earth surface reflectivity point data set (namely, mersi II blue wave Duan Ri scale earth surface reflectivity point data) under the daily scale of different azimuth angles and scattering angles.

And a sub-step a6, extracting the surface reflectivity point data of the 250 m resolution MERSI II blue wave Duan Yue scale according to the surface reflectivity point data of the Duan Ri scale of the 250 m resolution MERSI II blue wave.

The specific manner is similar to the extraction of the above-mentioned surface reflectivity library of the 500 m resolution MODIS blue wave band or the surface reflectivity library of the 250 m resolution MODIS red wave band, and will not be repeated here.

And a sub-step a7, constructing a second conversion relation according to the data of the surface reflectivity point of the Duan Yue-scale of the 250-meter resolution MERSI II blue wave and the surface reflectivity library of the 250-meter resolution MODIS blue wave band, and obtaining the surface reflectivity library of the 250-meter resolution MERSI II blue wave band.

The method can enable the data of the surface reflectivity of the scale Duan Yue of the MERSI II blue wave with the resolution of 250 meters to be matched with the surface reflectivity library of the surface reflectivity of the MODIS blue wave band with the resolution of 250 meters at the corresponding position, and the relation between the MODIS and the MERSI II is constructed:

；

according to the conversion relation, different M,And->Under the condition, the MODIS blue light wave band surface reflectivity library is converted into the MERSI II blue light wave band surface reflectivity library.

It should be noted that, there is no sequence of execution between the sub-steps a 1-a 3 and the sub-steps a 4-a 6, both of which are located before the sub-step a7, for example, in other embodiments, the sub-steps a 4-a 6 may be executed first, then the sub-steps a 1-a 3 may be executed, and finally the sub-step a7 may be executed.

In order to reduce the calculation amount and increase the processing speed, the resolution of the MERSI II data may be adjusted to be the same as the resolution of the blue band data in the MODIS surface reflectivity product, and therefore, in other possible embodiments, the above step S104 may be further implemented by the following substep b1 to substep b 6:

step b1, carrying out monthly statistics on blue wave band data with the resolution of 500 meters in the MODIS surface reflectivity product, and selecting pixels meeting each angle condition from the corresponding multi-view images of each month according to a plurality of preset angle conditions; wherein the angular condition includes that the azimuth angle and the scatter angle are in respective angular ranges.

And b2, for each angle condition of each month, determining the coincidence number of each pixel in accordance with the angle condition, and determining the blue wave band ground surface reflectivity of each pixel under the angle condition of each month according to the coincidence number of each pixel to obtain a 500 m resolution MODIS blue wave band ground surface reflectivity library.

Substep b3, converting the historical MERSI II data into historical MERSI II blue band apparent reflectance data.

And b4, calculating to obtain the surface reflectivity point data of the blue wave Duan Ri scale of the MERSI II with the resolution of 250 meters by using a radiation transmission equation according to the historical apparent reflectivity data of the blue wave of MERSI II and the AERONET aerosol optical thickness data of the corresponding position.

And b5, performing downsampling and monthly scale extraction on the data of the earth surface reflectivity points of the scale Duan Ri of the 250 m resolution MERSI II blue waves to obtain the data of the earth surface reflectivity points of the scale Duan Yue of the 500 m resolution MERSI II blue waves.

And b6, constructing a second conversion relation according to the 500-meter resolution MERSI II blue wave Duan Yue scale earth surface reflectivity point data and the 500-meter resolution MODIS blue wave band earth surface reflectivity library to obtain the 500-meter resolution MERSI II blue wave band earth surface reflectivity library.

Details of the above sub-steps b1 to b6 may refer to corresponding details of the above sub-steps a1 to a7, and will not be described herein. It should be noted that, there is no sequence of execution between the sub-steps b 1-b 2 and b 3-b 5, both of which are located before the sub-step b6, for example, in other embodiments, the sub-steps b 3-b 5 may be executed first, then the sub-steps b 1-b 2 may be executed, and finally the sub-step b6 may be executed.

Step S106, according to Cheng Fushe reflectivity, hemispherical reflectivity and atmospheric transmittance in the lookup table and surface reflectivity data in the MERSI II blue band surface reflectivity library, calculating by using a radiation transmission equation to obtain apparent reflectivity calculation data.

The specific implementation manner of step S106 may refer to the related art, and will not be described herein.

Step S108, comparing the apparent reflectivity calculation data with the actual apparent reflectivity data calculated based on the current MERSI II data to obtain matched apparent reflectivity calculation data matched with the actual apparent reflectivity data, and looking up a look-up table to obtain corresponding aerosol optical thickness data.

In particular, the matching apparent reflectance calculation data may be determined according to a matching error between the apparent reflectance calculation data and the apparent reflectance actual data, for example, a group of apparent reflectance calculation data with a minimum matching error is used as the matching apparent reflectance calculation data. It should be noted that, in other embodiments, the matching apparent reflectance calculation data may be determined in other manners, which is not limited by the embodiment of the present invention.

According to the aerosol optical thickness remote sensing inversion method provided by the embodiment of the invention, when aerosol optical thickness remote sensing inversion is carried out, a lookup table of Cheng Fushe reflectivity, hemispherical reflectivity and atmospheric transmittance under set parameters is established according to a radiation transmission model; the set parameters comprise solar zenith angle, observation zenith angle, relative azimuth angle between the sun and the satellite and aerosol optical thickness; then constructing a MERSI II blue band surface reflectivity library under the moon scale, different azimuth angles and different scattering angles based on a medium resolution imaging spectrometer MODIS surface reflectivity product, historical MERSI II data and aerosol automatic monitoring network AERONET data; according to Cheng Fushe reflectivity, hemispherical reflectivity and atmospheric transmissivity in the lookup table and surface reflectivity data in a MERSI II blue band surface reflectivity library, calculating by using a radiation transmission equation to obtain apparent reflectivity calculation data; and further, comparing the apparent reflectivity calculated data with the apparent reflectivity actual data calculated based on the current MERSI II data in a numerical mode to obtain matched apparent reflectivity calculated data matched with the apparent reflectivity actual data, and looking up a table in a lookup table to obtain corresponding aerosol optical thickness data. Therefore, the multi-angle reflectivity conversion technology is adopted when the aerosol optical thickness remote sensing inversion is carried out, so that the earth surface information under the month scale, different azimuth angles and different scattering angles can be effectively extracted, the earth surface reflectivity is prevented from being underestimated, a stable earth surface reflectivity library is provided, and the inversion precision of the aerosol optical thickness is further improved.

For ease of understanding, the aerosol optical thickness remote sensing inversion method is described below by taking an example in which the MODIS surface reflectivity product includes blue band data with a resolution MOD09 of 500 meters and red band data with a resolution of 250 meters, the resolution of MERSI II data is 250 meters, and the resolution of the blue band data in the MODIS surface reflectivity product is adjusted to 250 meters.

The aerosol optical thickness remote sensing inversion method mainly comprises the following steps: 1) Establishing a lookup table (LUT) according to the radiation transmission model; 2) Based on MODIS earth surface reflectivity products, FY3D MERSI II data and Aerosol Robotic Network (AERONET) aerosol automatic monitoring network data, constructing and converting MERSI II blue band earth surface reflectivity libraries under different month scale azimuth angles and scattering angle conditions; 3) Selecting a proper pixel, and calculating apparent reflectivity by using a radiation transmission equation; 4) And (3) optimally matching the actual observed apparent reflectivity with the calculated apparent reflectivity, and inverting the optical thickness of the aerosol.

Assuming a lambertian surface and a level-uniform atmosphere (i.e., uniform atmosphere level, uniform surface lambertian), apparent reflectance of the atmospheric layer roofIt can be noted that:

（1）

wherein L is radiation received by the detector; e (E) _S Solar radiation that is the top of the atmospheric layer;is the zenith angle of the sun (+)>) Cosine values of (a) are provided.

The reflectivity received by the sensor MERSI II lambda band is as follows:

（2）

wherein thetav is the zenith angle of the observation,is the relative azimuth; the left side of the equal sign is satellite observation itemSatellite observation reflectivity), the first and second terms on the right of the equal sign are the range radiation term and the earth surface reflection term, respectively (++>Is the surface reflectivity). Wherein the three unknowns comprise Cheng Fushe reflectivityHemispherical reflectivitySAnd atmospheric transmittance->All in relation to atmospheric conditions, can be obtained by simulation of step 1) under defined observation and aerosol conditions; another earth surface reflectivity term with unknown number as ground objectObtainable from step 2).

More detailed:

step 1) establishing a lookup table according to a 6S radiation transmission model:

mainly set the observation geometry: 9 solar zenith angles (0-80 degrees apart by 10 degrees), 9 observation zenith angles (0-80 degrees apart by 10 degrees), and relative azimuth angles between 10 sun and satellite (0-180 degrees apart by 20 degrees); aerosol optical thickness: 20 (0.05, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.8, 1.0, 1.2, 1.4, 1.6, 1.8, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5); the aerosol mode adopts uniform continental aerosol. A look-up table is constructed using a 6S radiation transmission model.

And 2) constructing a monthly scale earth surface reflectivity library based on a multi-angle reflectivity conversion technology MRTT. The MRTT comprises two conversions, namely, MODIS red and blue wave band surface reflectivity conversion and MODIS and MERSI II blue wave band surface reflectivity conversion:

(1) Extracting an MODIS red and blue band surface reflectivity library:

and selecting MODIS earth surface reflectivity product data MOD09 in 2013-2022, and carrying out statistics on earth surface reflectivity of a blue light wave band with 500 meters resolution and earth surface reflectivity of a red light wave band with 250 meters resolution under different azimuth angles and scattering angles according to months. The relative azimuth angle is greater than or equal to 90 DEG and is called forward relative azimuth angle) The azimuth angle is smaller than 90 DEG and is called backward relative azimuth angle (+)>). Based on the relative azimuth angles of the front and back directions, the scattering angle (++>) Divided into intervals of 45 deg.. Taking the forward relative azimuth angle with the azimuth angle being greater than or equal to 90 degrees and the earth surface reflectivity of the 500 m resolution blue light wave band with the scattering angle being 0-45 degrees as an example, assuming that N scenery images can be extracted each month (for example, 3 scenery images are extracted each month in 10 years, then N=10×3=30), extracting pixels with the azimuth angle being greater than or equal to 90 degrees and the scattering angle being in the range of 0-45 degrees, calculating each pixel, firstly sorting the earth surface reflectivity value of each pixel from small to large, and then setting a judging rule (N is the number of single pixel meeting the rule each month):

When n is less than or equal to 1, namely the number of the pixels meeting the condition in 10 years is not more than 1, removing the point;

when n=2, taking the average value of the two as the surface reflectivity of the point;

when N is more than or equal to 3 and less than or equal to N/2-1, taking the average value of the second and third small results as the surface reflectivity of the point.

Different months M (m=1, 2,3 …) are extracted according to the above manner, respectively, and different relative angles are obtained(n=f is forward direction and n=b is backward direction), different dispersionsAngle of attack->MODIS red band surface reflectivity under (i=0-45°, 45-90 DEG …)And blue band surface reflectivity->。

(2) Constructing a conversion relation of the surface reflectivity of the MODIS red and blue wave bands:

for different months M and different relative angles of positionDifferent scattering angles->MODIS red band surface reflectance under the condition +.>And blue band surface reflectivity->Sequentially constructing a conversion relation:

（3）

wherein,and->Representing different months M, different relative angles +.>Different scattering angles->The lower conversion coefficient. By conversion, different M and +.>And->Under the condition of 250 m resolution MODIS blue light wave band surface reflectivity library. />

(3) MERSI II blue band apparent reflectance conversion:

MERSI II per track observation was cut to 5 min/scene, with the data storage format being HDF5 format. The conversion of DN (Digital Number) values to apparent reflectance TOA (Top-of-Atmosphere) is required in combination with scaling coefficients before quantitative application. DN value information of FY3D MERSI II L1 blue light wave band is converted into apparent reflectivity of the blue wave band by utilizing scaling coefficient ：

（4）

MERSI II per track observation was cut to 5 min/scene, with the data storage format being HDF5 format.、、/>Scaling factors given in the dataset, +.>Attribute data sets taken from the data files for the distance between the day and the earth; and [ mu ] represents the cosine of the zenith angle of the sun, and zenith angle information can be obtained from MERSI II geometric positioning data.

(4) Constructing a conversion relation between MODIS and MERSI II blue band surface reflectivity:

MODIS and MERSI II are different sensors, and the spectral response functions of the two sensors are different to eliminate the sensorsThe conversion relation between MODIS and MERSI II needs to be constructed according to the spectrum difference. Extracting apparent reflectivity information of a MERSI II blue band by using longitude and latitude information of a global AERONET foundation site in 2017-2022, calculating real earth surface reflectivity of the MERSI II blue band by using a radiation transmission equation in combination with AERONET aerosol optical thickness data of a corresponding position, constructing an earth surface reflectivity point data set of the blue band under the daily scale of different azimuth angles and scattering angles, and extracting different M, M and M similar to a method for extracting MODIS red and blue band earth surface reflectivity library,And->And under the condition of MERSI II blue band surface reflectivity point data set. Matching the MODIS blue light wave band surface reflectivity library at the corresponding position, and constructing the relation between MODIS and MERSI II:

（5）

Step 3) calculating apparent reflectance using the radiation transmission equation (equation 2), wherein step 1) can calculate the aerosol optical thickness sum for different observation geometries and aerosol conditions、/>AndSrelation of three parameters, step 2) can construct the surface reflectivity +.>Thus the simulated apparent reflectivity can be solved>。

Step 4) requires converting the satellite observation DN to the actual apparent reflectivity using equation (4) according to the scaling factorThe method comprises the steps of carrying out a first treatment on the surface of the The simulated apparent reflectivity calculated in step 3) is +.>Apparent reflectivity +.>And comparing, and selecting optimal matching to invert the optical thickness of the aerosol.

The detailed technical route of the method is shown in fig. 2, and mainly comprises two parts of surface reflectivity library construction and aerosol optical thickness inversion.

As shown in fig. 2, in the process of constructing the earth surface reflectivity library, for FY3D MERSI II satellite data, based on radiation calibration (i.e., calibration coefficients), the apparent satellite reflectivity is obtained through conversion (i.e., sub-step a 4); then, the apparent reflectivity of the satellite is matched with the AERONET site data, the 6S radiation transmission model (comprising a radiation transmission equation) is utilized, the point data of the surface reflectivity of the 250 m MERSI blue wave Duan Ri scale is calculated (i.e. sub-step a 5), and then the point data of the surface reflectivity of the 250 m MERSI blue wave Duan Yue scale is extracted (i.e. sub-step a 6). For MODIS surface reflectivity data, firstly, red and blue waves Duan Yue scale surface reflectivity extraction (namely, sub-step a 1-sub-step a 2) is carried out, and then, red and blue waves Duan Yue scale surface reflectivity conversion is carried out, so that a 250 m MODIS blue wave Duan Yue scale surface reflectivity library, namely, a 250 m resolution MODIS blue wave band surface reflectivity library (namely, sub-step a 3) is obtained. After obtaining the data of the surface reflectivity point of the Duan Yue scale of the 250 m MERSI blue wave and the surface reflectivity library of the Duan Yue scale of the 250 m MODIS blue wave, the data of the surface reflectivity library of the MODIS and the surface reflectivity library of the MERSI are matched and converted, and the surface reflectivity library of the 250 m MERSI blue wave band, namely the surface reflectivity library of the 250 m resolution MERSI II blue wave band is obtained (namely a substep a 7). Thus, the construction of the surface reflectivity library is completed.

As shown in fig. 2, in performing aerosol optical thickness inversion, a look-up table is built by a 6S radiation transmission model (i.e., step S102 described above); based on the lookup table and the 250 m MERSI blue band reflectance library, calculating by using a radiation transmission equation to obtain simulated apparent reflectance, i.e., apparent reflectance calculation data (i.e., the above step S106); optimally matching the simulated apparent reflectivity with the apparent reflectivity of the satellite to obtain the optical thickness of the aerosol (i.e. the step S108); the satellite apparent reflectivity is obtained by converting FY3D MERSI II satellite data based on radiation calibration.

In summary, the aerosol optical thickness remote sensing inversion method provided by the embodiment of the invention has the following beneficial effects:

the embodiment of the invention utilizes the newly proposed earth surface reflectivity construction method MRTT, can effectively extract earth surface information of different azimuth angles and scattering angles of a month scale, avoids underestimation of earth surface reflectivity, provides a stable earth surface reflectivity library, and further improves the inversion precision of aerosol optical thickness.

Compared with the prior art, the method provided by the embodiment of the invention considers the influence of geometric and time changes on actual surface changes when the surface reflectivity is extracted, so that the underestimation of the surface reflectivity can be avoided, and the stable surface reflectivity can be provided.

Corresponding to the aerosol optical thickness remote sensing inversion method, the embodiment of the invention also provides an aerosol optical thickness remote sensing inversion device, referring to a schematic structural diagram of the aerosol optical thickness remote sensing inversion device shown in fig. 3, the device comprises:

the establishing module 301 is configured to establish a lookup table of Cheng Fushe reflectivity, hemispherical reflectivity and atmospheric transmittance under a set parameter according to the radiation transmission model; the set parameters comprise a solar zenith angle, an observation zenith angle, a relative azimuth angle between the sun and a satellite and an aerosol optical thickness;

the construction module 302 is configured to construct a MERSI II blue band earth surface reflectivity library with a month scale, different azimuth angles and different scattering angles based on the intermediate resolution imaging spectrometer MODIS earth surface reflectivity product, historical MERSI II data and aerosol automatic monitoring network AERONET data;

a calculation module 303, configured to calculate apparent reflectance calculation data according to Cheng Fushe reflectance, hemispherical reflectance and atmospheric transmittance in the lookup table, and surface reflectance data in the MERSI II blue band surface reflectance library by using a radiation transmission equation;

the inversion module 304 is configured to perform numerical comparison on the apparent reflectance calculation data and the apparent reflectance actual data calculated based on the current MERSI II data, obtain matched apparent reflectance calculation data matched with the apparent reflectance actual data, and look up a table in the lookup table to obtain corresponding aerosol optical thickness data.

In some possible embodiments, the AERONET data comprises AERONET aerosol optical thickness data; the above-mentioned construction module 302 is specifically configured to:

Further, the above construction module 302 is further configured to:

Further, the first conversion relation includes:

；

wherein,representing different months M in the surface reflectivity library of the MODIS red wave band with the resolution of 250 meters,Different relative azimuth angles->Different scattering angles->The surface reflectivity of the MODIS blue wave band,representing different months M and different relative azimuth angles +.A. in the 250M resolution MODIS red band surface reflectivity library>Different scattering angles->The ground surface reflectivity of MODIS red wave band is respectively, < ->、/>Representing different months M, different relative angles +.>Different scattering angles->The lower conversion coefficient.

Further, the above construction module 302 is further configured to:

；/>

In other possible embodiments, the AERONET data comprises AERONET aerosol optical thickness data; the above-mentioned construction module 302 is specifically configured to:

Further, the MODIS surface reflectivity product comprises blue wave band data with a resolution MOD09 of 500 meters.

The aerosol optical thickness remote sensing inversion device provided in this embodiment has the same implementation principle and technical effects as those of the aerosol optical thickness remote sensing inversion method embodiment, and for the sake of brief description, reference may be made to corresponding contents in the aerosol optical thickness remote sensing inversion method embodiment where the aerosol optical thickness remote sensing inversion device embodiment is not mentioned.

As shown in fig. 4, an electronic device 400 provided in an embodiment of the present invention includes: the aerosol optical thickness remote sensing inversion method comprises a processor 401, a memory 402 and a bus, wherein the memory 402 stores a computer program capable of running on the processor 401, and when the electronic device 400 runs, the processor 401 and the memory 402 are communicated through the bus, and the processor 401 executes the computer program to realize the aerosol optical thickness remote sensing inversion method.

Specifically, the memory 402 and the processor 401 described above can be general-purpose memories and processors, and are not particularly limited herein.

Embodiments of the present invention also provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the aerosol optical thickness remote sensing inversion method described in the previous method embodiments. The computer-readable storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a RAM, a magnetic disk, or an optical disk, etc., which can store program codes.

Any particular values in all examples shown and described herein are to be construed as merely illustrative and not a limitation, and thus other examples of exemplary embodiments may have different values.

The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

In the several embodiments provided by the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. The above-described apparatus embodiments are merely illustrative, for example, the division of the units is merely a logical function division, and there may be other manners of division in actual implementation, and for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. In addition, the coupling or direct coupling or communication connection shown or discussed with each other may be through some communication interface, device or unit indirect coupling or communication connection, which may be in electrical, mechanical or other form.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.

Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.

Claims

1. An aerosol optical thickness remote sensing inversion method is characterized by comprising the following steps:

2. The aerosol optical thickness remote sensing inversion method of claim 1, wherein the AERONET data comprises AERONET aerosol optical thickness data; the method for constructing the MERSI II blue band surface reflectivity library based on the medium resolution imaging spectrometer MODIS surface reflectivity product, historical MERSI II data and aerosol automatic monitoring network AERONET data comprises the following steps of:

3. The aerosol optical thickness remote sensing inversion method according to claim 2, wherein determining the blue band surface reflectivity and the red band surface reflectivity of each pixel under the angle condition of the month according to the corresponding coincidence number of the pixel comprises:

4. The aerosol optical thickness remote sensing inversion method of claim 2, wherein the first transformation relationship comprises:

；

Wherein,representing different months M and different relative azimuth angles +.A. in the 250M resolution MODIS red band surface reflectivity library>Different scattering angles->Surface reflectivity of MODIS blue band, < ->Representing different months M and different relative azimuth angles +.A. in the 250M resolution MODIS red band surface reflectivity library>Different scattering angles->The ground surface reflectivity of MODIS red wave band is respectively, < ->、/>Representing different months M, different relative angles +.>Different scattering angles->The lower conversion coefficient.

5. The aerosol optical thickness remote sensing inversion method of claim 2, wherein said converting said historical MERSI II data into historical MERSI II blue band apparent reflectance data comprises:

；

6. The aerosol optical thickness remote sensing inversion method of claim 1, wherein the AERONET data comprises AERONET aerosol optical thickness data; the method for constructing the MERSI II blue band surface reflectivity library based on the medium resolution imaging spectrometer MODIS surface reflectivity product, historical MERSI II data and aerosol automatic monitoring network AERONET data comprises the following steps of:

7. The aerosol optical thickness remote sensing inversion method according to any one of claims 1-6, wherein said MODIS surface reflectivity product comprises blue band data of 500 meter resolution MOD 09.

8. An aerosol optical thickness remote sensing inversion device, comprising:

9. An electronic device comprising a memory, a processor, the memory having stored thereon a computer program executable on the processor, wherein the processor, when executing the computer program, implements the aerosol optical thickness remote sensing inversion method of any of claims 1-7.

10. A computer readable storage medium having stored thereon a computer program, which when executed by a processor performs the aerosol optical thickness remote sensing inversion method of any of claims 1-7.