CN110705089A - Fine-mode aerosol parameter inversion method - Google Patents

Fine-mode aerosol parameter inversion method Download PDF

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CN110705089A
CN110705089A CN201910921707.9A CN201910921707A CN110705089A CN 110705089 A CN110705089 A CN 110705089A CN 201910921707 A CN201910921707 A CN 201910921707A CN 110705089 A CN110705089 A CN 110705089A
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李正强
葛邦宇
侯伟真
谢一凇
许华
张莹
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Institute of Remote Sensing and Digital Earth of CAS
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Abstract

The invention discloses a fine-mode aerosol parameter inversion method, which utilizes the characteristic that the reflectivity of a polarized earth surface is basically not changed along with a wave band from visible light to near infrared wave band; the characteristic of small change of the reflectivity of the polarized earth surface is combined; and (3) inverting the polarized remote sensing data of the POLDER sensor to obtain the optical thickness of the fine-mode aerosol. The method can effectively invert the fine-mode aerosol parameters and the polarization earth surface reflectivity at the same time, and the inverted fine-mode aerosol optical thickness has higher spatial coverage, higher spatial resolution and higher precision. The method can be used for small-scale fine-mode aerosol research, and the coverage and precision of bright earth surfaces (cities, deserts and the like) are increased.

Description

Fine-mode aerosol parameter inversion method
Technical Field
The invention relates to the field of atmospheric pollution treatment, in particular to an atmospheric aerosol observation technology.
Background
Particles of atmospheric aerosolThe diameters are typically from a few nanometers to tens of micrometers, and in order to better evaluate their global radiation balance, climate change, atmospheric environment, and human health, aerosols are generally classified by particle size into fine and coarse mode aerosols. The radius of the fine mode aerosol is generally 0.1-0.2 microns, and the main source is artificial discharge. The radius of the coarse mode aerosol is typically greater than 1 micron, mainly from natural emissions. According to the fifth assessment report by the inter-government commission on climate change (IPCC), fine mode aerosols have a greater impact on climate change due to their large absorption properties. In addition, the fine mode aerosol is used for estimating the surface fine particulate matter PM2.5Is an important parameter. However, there is a great uncertainty in its quantitative estimation due to the high temporal and spatial variability properties of the aerosol. Particularly, as the number and activities of human beings are continuously increased, the emission of fine-modal aerosol is increased and the influence is increased. Therefore, it is increasingly important to obtain fine-modal aerosol products with high temporal resolution, high spatial resolution, and high precision, to reduce their own uncertainty and impact on other factors. However, currently, the inversion surface of the fine-mode aerosol still faces numerous challenges.
The fine-mode aerosol inversion mainly comprises two types of ground and satellite observation, the ground inversion has the characteristic of high precision and is generally regarded as a true value, the ground inversion can be used for verifying a product of the satellite inversion, but the space coverage is insufficient, and the space distribution characteristic of the fine-mode aerosol cannot be comprehensively reflected. On the contrary, the method for inverting the fine-mode aerosol by using the satellite remote sensing data has the characteristics of wide observation range, less terrain constraint, short acquisition time and the like. However, due to the complexity of land surface types, the space coverage, the space resolution and the precision of the terrestrial fine-mode aerosol product obtained by satellite remote sensing data have certain problems. For example, inverting the acquired fine-modal aerosol product using a single angle intensity sensor moderatio imaging spectroradiometer (MODIS), relevant validation studies have shown that its fine-modal aerosol product is relatively less accurate and its use is not recommended by its official party. The reason is that the intensity signal at a single angle is not sufficient to distinguish fine mode aerosol from coarse mode aerosol information, and the surface signal accounts for a relatively large proportion of the total signal. In contrast, the polarized signal is only sensitive to the fine-mode aerosol within a certain scattering angle range, and the proportion of the polarized surface signal is smaller than or equal to that of the atmospheric signal, which are very beneficial for inverting the fine-mode aerosol by using the polarized signal. However, at present, only the earth reflection POLarization measurement instrument POLDER (POLARIZATION and Direction of the earth's reflexes) can provide long-time-series multi-angle polarized satellite remote sensing data, and Deuze et al utilize a surface POLarization reflectivity model (BPDF) to invert fine-mode aerosol products, and the algorithm is also a POLDER official algorithm. The released fine particle aerosol product is widely applied to various related fields, but the product has low spatial resolution and cannot be applied to small-scale aerosol research, and secondly, the product has serious deficiency conditions in cities, deserts, ice and snow and other bright earth surfaces and water bodies and other areas, and has relatively low precision. A number of scholars have inverted terrestrial space-fine modal aerosols based on the polar data, but are basically similar to the official algorithm, i.e. using BPDF to estimate the polarized earth reflectivity. Since the BPDF is a statistical model and the polarization earth surface reflectivity cannot be well estimated on some specific earth surfaces, the problems of low spatial resolution, product loss on specific earth surfaces, low precision and the like of the currently inverted fine-mode aerosol exist, and therefore, a new technical scheme for inverting the fine-mode aerosol is urgently needed to be developed.
Disclosure of Invention
The invention aims to provide a fine mode aerosol parameter inversion method which has higher spatial resolution, wider spatial coverage and higher precision of the obtained fine mode aerosol optical thickness than the PLODER official secondary product; the specific technical scheme is as follows:
the method comprises the following steps:
1) importing polarization remote sensing data of a POLDER sensor, selecting data of apparent polarization reflectivity of at least two wavelengths, and extracting a solar zenith angle, a solar azimuth angle, an observation zenith angle, a relative azimuth angle, a cloud mask, an amphibious mask and an elevation from a data file to be used as data to be processed;
2) shielding data of a cloud layer and a region covered by a water surface by using cloud mask data and land and water mask data, and calculating a scattering angle of each inversion data unit through a solar zenith angle, an observation zenith angle and a relative azimuth angle according to a formula (1); taking only data with scattering angles ranging from 80 ° to 120 ° as inversion data;
cosΘ＝-cosθscosθv-sinθssinθvcosφ (1)
wherein theta is the scattering angle thetasAt the zenith angle of the sun, thetavPhi is a relative azimuth angle for observing a zenith angle;
3) processing the inversion data by using an wxw window internal pixel as an inversion unit and using a lookup table for forward simulation of a 6SV radiation transmission model to obtain a preprocessing lookup table;
4) performing linear interpolation in the preprocessing lookup table according to the observation geometric angle corresponding to each effective pixel in the inversion unit to obtain process radiation, upward atmospheric transmittance and downward atmospheric transmittance;
5) carrying out atmospheric correction on each effective pixel by using a formula (2) in combination with the polarization apparent reflectivity of each effective pixel to obtain the polarization earth surface reflectivity of different wave bands;
Figure BDA0002217791130000021
in the formula, lambda is the wave band,
Figure BDA0002217791130000022
in order to polarize the apparent reflectance of light,
Figure BDA0002217791130000023
in order to be the range radiation,
Figure BDA0002217791130000024
for the downward atmospheric transmission rate,
Figure BDA0002217791130000025
the upward air transmission rate is higher than that of the air,
Figure BDA0002217791130000026
is the polarized surface reflectance;
6) calculating the ratio of the polarized earth surface reflectivities of the two wave bands according to a formula (3);
Figure BDA0002217791130000031
in the formula, λ1Is a first band, λ2In the second wavelength band, the first wavelength band,
Figure BDA0002217791130000032
the ratio of the polarized earth surface reflectivity of the first wave band and the second wave band is obtained;
7) calculating the error of the ratio of the polarized earth surface reflectivity and the square root of 1 according to a formula (4), and selecting the effective fine-mode aerosol optical thickness and the polarized earth surface reflectivity when each aerosol model under an effective scattering angle enables the difference value of the polarized earth surface reflectivities of the two wave bands to be minimum;
Figure BDA0002217791130000033
8) respectively calculating the average values of the effective fine-mode aerosol optical thickness and the polarized earth surface reflectivity of the effective pixel according to formulas (5) and (6); in formula (5), N is the effective fine mode aerosol optical thickness
Figure BDA0002217791130000034
δmean_wThe average value of the optical thickness of the effective fine particle aerosol of the effective pixel;
Figure BDA0002217791130000035
in the formula (6), N is effective polarizationThe number of the earth surface reflectivity is,
Figure BDA0002217791130000037
the effective polarization earth surface reflectivity average value of the second wave band of the effective pixel;
9) calculating a cost function eta of the inversion window unit according to formula (7), and selecting the value of eta which is the minimum
Figure BDA0002217791130000038
And its corresponding aerosol optical thickness delta under aerosol modelmean_wRadius REObtaining an inversion result;
Figure BDA0002217791130000039
where STD represents the variance, w x w represents the selected window size,
Figure BDA00022177911300000310
is the polarized earth surface reflectivity of 865nm wave band in the effective pixel.
Further, the wavelengths of the first and second bands are two of 490nm, 670nm and 865nm, respectively.
Further, the wavelength of the first waveband is 670 nm; the wavelength of the second waveband is 865 nm.
Further, the spatial resolution of the inversion is made to be consistent with the sensor resolution.
Further, the value of w is 3.
The method can effectively invert the fine-mode aerosol parameters and the polarization earth surface reflectivity at the same time, and the inverted fine-mode aerosol optical thickness has higher spatial coverage, higher spatial resolution and higher precision. The method can be used for research on small-scale fine mode aerosol, and the coverage and precision of bright earth surfaces (cities, deserts and the like) are increased.
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FIG. 1 is a comparison graph of the fine-mode aerosol parameter inversion method of embodiment 1 of the present invention and the effect of the prior art;
FIG. 2 is a comparison graph of the fine mode aerosol parameter inversion method of embodiment 2 of the present invention and the effect of the prior art;
FIG. 3 is a comparison of the fine mode aerosol parameter inversion method of embodiment 3 of the present invention and the prior art effect in FIG. 1;
fig. 4 is a comparison between the fine-mode aerosol parameter inversion method of embodiment 3 of the present invention and the prior art, and fig. 2.
In the figure: (a) the method comprises the following steps Satellite image true color picture; (b) the method comprises the following steps The method of the invention produces a result of the optical thickness of the fine-mode aerosol; (c) the method comprises the following steps Official fine mode aerosol optical thickness results.
Detailed Description
The present invention will now be more fully described with reference to the following examples. This invention may, however, be embodied in many different forms and should not be construed as limited to the exemplary embodiments set forth herein.
For ease of description, spatially relative terms, such as "upper," "lower," "left," "right," and the like, may be used herein to describe one element or feature's relationship to another element or feature as illustrated in the figures. It will be understood that the spatial terms are intended to encompass different orientations of the device in use or operation in addition to the orientation depicted in the figures. For example, if the device in the figures is turned over, elements described as "below" other elements or features would then be oriented "above" the other elements or features. Thus, the exemplary term "lower" can encompass both an upper and a lower orientation. The device may be otherwise oriented (rotated 90 degrees or at other orientations) and the spatially relative descriptors used herein interpreted accordingly.
In order to realize the invention, the invention discloses a high-spatial-resolution fine-modal aerosol parameter inversion method based on polarization data, which is applied to polarization remote sensing data of a POLDER sensor, and the specific implementation scheme is as follows:
in order to realize the invention, the method is applied to polarization remote sensing data of a POLDER sensor, wherein the POLDER sensor comprises 9 wave bands (443, 490, 565, 670, 763, 765, 865, 910 and 1020nm), and the 490, 670 and 865nm 3 wave bands comprise polarization channels. The POLDER 1 level data is a binary file and comprises a header file and a data file, wherein the header file comprises information of sensors and data processing, and the data file comprises sensor observation and auxiliary data information. The sensor observation information comprises multi-angle intensity observation data of 9 wave bands and multi-angle polarization observation data of 3 wave bands. The auxiliary data comprise data of a solar zenith angle, an observation zenith angle, a relative azimuth angle, a cloud mask, a land-water mask, an elevation and the like. Aiming at POLDER sensor data, the data used by the invention comprise 670 and 865nm multi-angle polarization observation data, and solar zenith angle, observation zenith angle, relative azimuth angle, cloud mask, land and water mask and elevation auxiliary data. The specific embodiment of the invention is as follows:
(1) simulating different wave bands, different observation geometries, different elevations, different aerosol models and different aerosol optical thicknesses (AOD) according to a forward simulation lookup table of a 6SV radiation transmission modelf) The specific parameters of the lookup table of parameter combinations are shown in table one.
Table one, lookup table parameter settings
(2) The method takes a 3 multiplied by 3 window as a unit, and input data comprise 670 and 865nm effective multi-angle apparent polarization reflectivity observed by each pixel in the window, and a corresponding solar zenith angle, an observation zenith angle, a relative azimuth angle, a cloud mask, a height range mask and an amphibious mask. Data in the 470nm band may also be combined with data in the 670nm or 865nm band.
(3) The input data is quality controlled using the sea-land mask, the cloud mask and the scattering angle Θ, which is calculated by equation (1). Only image elements on land and clear sky and satisfying Θ between 80 ° and 120 ° can be used for fine mode aerosol parametric inversion.
cosΘ＝-cosθscosθv-sinθssinθvcosφ (1)
Wherein theta is the scattering angle thetasAt the zenith angle of the sun, thetavTo observe zenith angles, phi is the relative azimuth angle.
(4) Carrying out linear interpolation on different observation geometric angles of the effective pixel in a 3 multiplied by 3 window in a lookup table to obtain the scattering angle theta of the effective pixel_wCorresponding different aerosol models, different fine particle aerosol optical thicknesses delta_wAtmospheric parameters including range radiation
Figure BDA0002217791130000052
Upward atmospheric transmittance
Figure BDA0002217791130000053
And downward atmospheric transmittance
Figure BDA0002217791130000054
And combined with apparent reflectivity of polarization for each effective pixel
Figure BDA0002217791130000055
Atmosphere correction is carried out according to the formula (2), and further different aerosol optical thicknesses delta under different aerosol types of the effective pixel w are obtained_wDifferent scattering angle theta_w670 and 865nm band of polarized earth surface reflectivity
Figure BDA0002217791130000056
and
Figure BDA0002217791130000057
Figure BDA0002217791130000058
In the formula, lambda is the wave band,
Figure BDA0002217791130000059
in order to polarize the apparent reflectance of light,in order to be the range radiation,for the downward atmospheric transmission rate,
Figure BDA00022177911300000512
the upward air transmission rate is higher than that of the air,
Figure BDA0002217791130000061
is the polarized surface reflectance.
(5) Calculating different scattering angles theta under the effective pixel w according to the formula (3)_wDifferent aerosol types, different aerosol optical thicknesses δ_wPolarized surface reflectance ratio R of lower 670 and 865nm wave bandsratio。
In the formula, λ1Is 670nm band, lambda2Is a wave band of 865nm,
Figure BDA00022177911300000613
the specific value of the polarized surface reflectivities of 670nm and 865nm wave bands.
(6) According to the characteristic that the reflectivity of the polarized earth surface does not change along with the wave band from visible light to near infrared wave band, different scattering angles theta under different effective pixels are calculated according to the formula (4)_wDifferent aerosol types, different aerosol optical thicknesses δ_wLower 670 and 865nm polarized earth surface reflectivity ratio Rratio_wAnd 1 square root error.
Figure BDA0002217791130000063
(7) For each effective aerosol model, for each effective scattering angle Θ_wBy selecting the fine mode aerosol optical thickness delta_wLet DiffR _wOf minimum value, i.e. polarized surface reflectance
Figure BDA0002217791130000064
And
Figure BDA0002217791130000065
the closest; i.e. the optical thickness delta of the fine-mode aerosol_wA fine mode aerosol optical thickness as a corresponding effective aerosol type at an effective scattering angle for the pixel. Thereby obtaining the optimal fine mode aerosol parameters and polarization surface reflectivity of each effective aerosol model under each effective scattering angle of each effective pixel.
(8) Respectively calculating the fine mode aerosol optical thickness delta of each effective aerosol model under each effective pixel according to the formulas (5) and (6) aiming at each effective aerosol model of each effective pixel_wAverage value of (2) and polarized surface reflectance
Figure BDA00022177911300000614
Including the mean value delta of the optical thickness of the fine-particle aerosolmean_wAnd 865nm band of polarized earth surface reflectivity
Figure BDA0002217791130000067
Figure BDA0002217791130000068
Wherein N is the effective fine mode aerosol optical thickness
Figure BDA0002217791130000069
Number, deltamean_wThe average value of the optical thickness of the aerosol of the fine particles of the effective pixel is shown.
Figure BDA00022177911300000610
Wherein N is effective polarization earth surface reflectivity of 865nm wave band
Figure BDA00022177911300000611
The number of the first and second groups is,
Figure BDA00022177911300000612
is the average value of the surface reflectivity of the effective pixel 865nm wave band.
(9) Calculating a cost function eta according to the formula (7), selecting the one which minimizes the value of eta
Figure BDA0002217791130000071
And its corresponding aerosol optical thickness delta under aerosol modelmean_wRadius REThe space resolution can reach about 6km per pixel, namely the inversion result; with higher resolution sensors (e.g., DPC sensors, resolution of 3km per pixel), the resolution of the inversion can also be achieved for single pixel inversion.
Figure BDA0002217791130000072
In the formula, STD represents variance, 3 × 3 represents selected window size, and 4x4 or 5x5 window size can be selected;is the polarized earth surface reflectivity of 865nm wave band of the effective pixel. The inversion efficiency is best compared to the inversion results with a 3x3 window.
In order to qualitatively evaluate the spatial distribution characteristics of the inverted fine-mode aerosol optical thickness, the spatial distribution characteristics are compared with the POLDER official algorithm result.
Example 1
Fig. 1(a) is a true color image of the polar satellite image at 11/15/2011 in eastern china, (b) is the optical thickness result of the fine mode aerosol according to the method of the present invention, and (c) is the optical thickness result of the official fine mode aerosol. The land surface type of the area is mainly vegetation, cultivated land and city, and as can be seen from the figure, the official inversion resolution is about 18km per pixel; the optical thickness of the fine-mode aerosol inverted by the method is consistent with the spatial distribution of official results on the whole, but the method has higher spatial coverage, and particularly compensates the condition that a large amount of products are lost in the area of an official algorithm in coastal areas with gathered population and developed economy. In addition, the optical thickness spatial resolution of the fine-mode aerosol is higher, the detail change is more obvious, and the research of the small and medium-scale fine-mode aerosol is more facilitated.
Example 2
Fig. 2(a) is a true color image of the polar satellite image at 11/18/2011 in northern west of china and india, (b) is the optical thickness result of the fine mode aerosol of the present invention, and (c) is the optical thickness result of the official fine mode aerosol. The regional surface type mainly comprises deserts, mountains and cultivated lands, and the official inversion resolution ratio is about 18km per pixel as is obvious from the figure; the space coverage of the inverted fine-modal aerosol optical thickness in desert, mountain and coastal areas is obviously higher than that of an official algorithm, the condition that the official algorithm has a large number of product defects in the surface type area is made up, and particularly in Qinghai-Tibet plateau areas with complex terrain and high aerosol inversion difficulty is solved. In addition, the fine mode aerosol optical thickness product of the algorithm successfully captures the condition of heavy pollution on plain of India constant river, which is low in Qinghai-Tibet plateau, and is more obvious in detail change.
Example 3
In order to quantitatively evaluate the precision of the inverted fine-mode aerosol optical thickness, foundation AERONET site results respectively located in different types of tables are selected for verification. Fig. 3 is a result of verification between the fine-mode aerosol optical thickness inverted by the method and the official algorithm in 2010-2012 based on the POLDER data and the ground-based site, respectively, and it can be seen from the result that the fine-mode aerosol optical thickness inverted by the method is better than the official algorithm result no matter the inverted number N, the correlation R, the root mean square error RMSE or the ratio Gfrac falling within the error range, which indicates that the algorithm of the invention is obviously better than the official algorithm. Fig. 4 shows verification results of the method and the official algorithm of the present invention based on the POLDER data in 2010-2012 and 3 with a SACOL site base station, the SACOL site is located in the northwest semiarid area in China, the vegetation coverage is low, the inversion difficulty of the fine-mode aerosol is high, from the verification results, the optical thickness result of the fine-mode aerosol inverted by the present invention is obviously more than the official result, and the inversion accuracy and the foundation observation result are closer, which indicates that the algorithm of the present invention has higher applicability in the semiarid area.
In general, whether the qualitative comparison with the result of the official algorithm or the quantitative verification of the result of the foundation AERONET site shows that the algorithm has higher spatial coverage, higher spatial resolution and higher precision than the optical thickness of the fine-mode aerosol inverted by the official algorithm, and the defects of the official algorithm product are overcome.
The above examples are only for illustrating the present invention, and besides, there are many different embodiments, which can be conceived by those skilled in the art after understanding the idea of the present invention, and therefore, they are not listed here.

Claims (5)

1. A method for inverting parameters of a fine-mode aerosol is characterized by comprising the following steps:
1) importing polarization remote sensing data of a POLDER sensor, selecting data of at least two apparent polarization reflectances with wavelengths in a range from visible light to near infrared, and extracting a solar zenith angle, an observation zenith angle, a relative azimuth angle, a cloud mask, a land-water mask and an elevation from a data file as data to be processed;
2) shielding data of a cloud layer and a region covered by a water surface by using cloud mask data and land and water mask data, and calculating a scattering angle of each inversion data unit through a solar zenith angle, an observation zenith angle and a relative azimuth angle according to a formula (1); taking only data with scattering angles ranging between 80 and 120 ° as inversion data;
cosΘ＝-cosθscosθv-sinθssinθvcosφ (1)
in the formula, theta is a scattering angle, thetas is a solar zenith angle, thetav is an observation zenith angle, and phi is a relative azimuth angle;
3) processing the inversion data by using a forward simulation lookup table of a 6SV radiation transmission model by taking an wxw pixel as an inversion unit to obtain a preprocessing lookup table;
4) performing linear interpolation in the preprocessing lookup table according to the observation geometric angle corresponding to each effective pixel in the inversion unit to obtain process radiation, upward atmospheric transmittance and downward atmospheric transmittance;
5) carrying out atmospheric correction on each effective pixel according to a formula (2) by combining the polarization apparent reflectivity of each effective pixel to obtain the polarization earth surface reflectivity of different wave bands;
Figure FDA0002217791120000011
in the formula, lambda is the wave band,
Figure FDA0002217791120000012
in order to polarize the apparent reflectance of light,
Figure FDA0002217791120000013
in order to be the range radiation,
Figure FDA0002217791120000014
for the downward atmospheric transmission rate,
Figure FDA0002217791120000015
the upward air transmission rate is higher than that of the air,
Figure FDA0002217791120000016
is the polarized surface reflectance;
6) calculating the ratio of the polarized earth surface reflectivities of the two wave bands according to a formula (3);
Figure FDA0002217791120000017
in the formula, λ1Is a first band, λ2In the second wavelength band, the first wavelength band,the ratio of the polarized earth surface reflectivity of the first wave band and the second wave band is obtained;
7) calculating the error of the square root of the ratio of the reflectivity of the polarized earth surface and 1 according to the formula (4);
8) selecting the polarized earth surface reflectivity of two wave bands from each aerosol model corresponding to each effective scattering angle according to the scattering angle
Figure FDA0002217791120000022
Minimum differential fine mode aerosol optical thickness
Figure FDA0002217791120000023
Figure FDA0002217791120000024
Figure FDA0002217791120000025
In formula (5), N is the effective fine mode aerosol optical thickness
Figure FDA0002217791120000026
Number, deltamean_wThe average value of the optical thickness of the effective fine particle aerosol of the effective pixel;
in the formula (6), N is the number of effective polarized earth surface reflectivities,
Figure FDA0002217791120000027
the effective polarization earth surface reflectivity average value of the second wave band of the effective pixel;
9) calculating a cost function eta of the window according to the formula (7), and selecting the one which minimizes the eta value
Figure FDA0002217791120000028
And its corresponding aerosol optical thickness delta under aerosol modelmean_wRadius REAs a result of the inversion;
where STD represents the variance, w x w represents the selected window size,
Figure FDA00022177911200000210
is the polarized earth surface reflectivity of 865nm wave band in the effective pixel.
2. The method of fine mode aerosol parametric inversion of claim 1, wherein the wavelengths of the first and second bands are two of 490nm, 670nm and 865nm, respectively.
3. The method of fine mode aerosol parametric inversion of claim 2, wherein the wavelengths of the first and second bands are 670nm and 865nm, respectively.
4. The fine-mode aerosol parametric inversion method of claim 1, wherein the spatial resolution of the inversion is consistent with the sensor resolution.
5. The method of fine mode aerosol parametric inversion of claim 1, wherein W has a value of 3.
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116660106A (en) * 2023-07-21 2023-08-29 中国科学院空天信息创新研究院 Aerosol parameter iterative inversion method for collaborative satellite-borne scalar and polarization observation data

Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7337065B2 (en) * 2001-01-23 2008-02-26 Spectral Sciences, Inc. Methods for atmospheric correction of solar-wavelength hyperspectral imagery over land
US20090213120A1 (en) * 2005-04-25 2009-08-27 X-Rite, Inc. Method And System For Enhanced Formulation And Visualization Rendering
WO2009108795A1 (en) * 2008-02-26 2009-09-03 Battelle Memorial Institute Biological and chemical microscopic targeting
US20120281085A1 (en) * 2011-05-04 2012-11-08 Raytheon Company In-scene determination of aerosol parameters from imagery
CN103927455A (en) * 2014-04-24 2014-07-16 中国科学院遥感与数字地球研究所 Land aerosol optical property retrieval method based on Gaofen-1 satellite
CN106225693A (en) * 2016-08-29 2016-12-14 中国科学院遥感与数字地球研究所 A kind of fine particle aerosol optical thickness and aerosol type Simultaneous Inversion method
CN109781593A (en) * 2019-01-17 2019-05-21 南京泛在地理信息产业研究院有限公司 A kind of aerosol quadratic inversion method based on PARASOL multi-angle polarization data
CN110186822A (en) * 2019-05-13 2019-08-30 中国科学院遥感与数字地球研究所 A kind of aerosol optical depth remote sensing inversion method
CN110186823A (en) * 2019-06-26 2019-08-30 中国科学院遥感与数字地球研究所 A kind of aerosol optical depth inversion method

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7337065B2 (en) * 2001-01-23 2008-02-26 Spectral Sciences, Inc. Methods for atmospheric correction of solar-wavelength hyperspectral imagery over land
US20090213120A1 (en) * 2005-04-25 2009-08-27 X-Rite, Inc. Method And System For Enhanced Formulation And Visualization Rendering
WO2009108795A1 (en) * 2008-02-26 2009-09-03 Battelle Memorial Institute Biological and chemical microscopic targeting
US20120281085A1 (en) * 2011-05-04 2012-11-08 Raytheon Company In-scene determination of aerosol parameters from imagery
CN103927455A (en) * 2014-04-24 2014-07-16 中国科学院遥感与数字地球研究所 Land aerosol optical property retrieval method based on Gaofen-1 satellite
CN106225693A (en) * 2016-08-29 2016-12-14 中国科学院遥感与数字地球研究所 A kind of fine particle aerosol optical thickness and aerosol type Simultaneous Inversion method
CN109781593A (en) * 2019-01-17 2019-05-21 南京泛在地理信息产业研究院有限公司 A kind of aerosol quadratic inversion method based on PARASOL multi-angle polarization data
CN110186822A (en) * 2019-05-13 2019-08-30 中国科学院遥感与数字地球研究所 A kind of aerosol optical depth remote sensing inversion method
CN110186823A (en) * 2019-06-26 2019-08-30 中国科学院遥感与数字地球研究所 A kind of aerosol optical depth inversion method

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
GUANGLIANG FU,ET AL.: "Retrieval of aerosol microphysical and optical properties over land using a multimode approach", 《ATMOSPHERIC MEASUREMENT TECHNIQUES》 *
ZHENGQIANG LI,ET AL.: "Directional Polarimetric Camera (DPC): Monitoring aerosol spectral optical properties over land from satellite observation", 《JOURNAL OF QUANTITATIVE SPECTROSCOPY & RADIATIVE TRANSFER》 *
张洋: "基于多角度标量和偏振卫星数据的气溶胶光学参数反演研究", 《中国博士学位论文全文数据库 工程科技I辑》 *
李树等: "基于多角度偏振信息反演海洋上空卷云云顶高度", 《红外与毫米波学报》 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116660106A (en) * 2023-07-21 2023-08-29 中国科学院空天信息创新研究院 Aerosol parameter iterative inversion method for collaborative satellite-borne scalar and polarization observation data
CN116660106B (en) * 2023-07-21 2023-10-17 中国科学院空天信息创新研究院 Aerosol parameter iterative inversion method for collaborative satellite-borne scalar and polarization observation data

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