CN100362319C - Surficial contrast method for inverting optical thickness of aerosol at boundary layer from aeronautic high spectrum remote sensing - Google Patents
Surficial contrast method for inverting optical thickness of aerosol at boundary layer from aeronautic high spectrum remote sensing Download PDFInfo
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Abstract
The present inversion relates to a surficial contrast method for inverting the optical thickness of an aerosol at a boundary layer from an aeronautic hyperspectral remote sensor, particularly to a hyperspectral image obtained by a home-made aeronautic hyperspectral remote sensor. The contrast of two high contrast ground objects at different heights of a high altitude and the ground realizes the inversion of the optical thickness of the aerosol at the atmospheric boundary layer of a city. The method belongs to the application field of the remote sense of atmospheric environment, and mainly solves the technical problems of a calculation method which is relevant with the calculation of the optical thickness, etc. of the aerosol, system software, system hardware, etc. The method realizes the inversion of the optical thickness of the aerosol at the atmospheric boundary layer of the city by the contrast of the two high contrast ground objects on the two different heights of the high altitude and the ground and the inversion of the calculation of the optical thickness of the aerosol. The present invention has the advantages that the method is different from a normal method for calculating the optical thickness of the aerosol by a high altitude layer or a fixed ground object, and compared with a traditional remote sensing image, the image has the maximum characteristic of effective means, such as high spectral resolution, etc.
Description
Technical Field
The invention relates to a detection method for inverting boundary layer aerosol optical thickness by aviation hyperspectral remote sensing, which is applied to a hyperspectral image obtained by an aviation hyperspectral remote sensor developed by an aviation hyperspectral remote sensing research laboratory of Shanghai technical and physical research institute of Chinese academy of sciences, realizes inversion of the urban atmospheric boundary layer aerosol optical thickness by comparing two high-contrast ground objects at two different heights of the upper air and the ground surface, and belongs to the field of atmospheric environment remote sensing application.
Background
The atmospheric aerosol refers to solid or liquid particles with the radius less than tens of microns suspended in the atmosphere, plays an important role in the balance of radiation balance of the earth atmosphere and global climate, and is an important research object in atmospheric physics. On the one hand, aerosols directly influence the radiation balance of the land-gas system by scattering and absorbing solar radiation and ground radiation; on the other hand, the aerosol also participates in a plurality of physical processes of the atmosphere, such as a micro-physical mechanism of cloud formation, ozone balance and the like; disturbing the signal received by the remote sensor in an absorbing and scattering manner. Therefore, the aerosol is accurately measured and analyzed, and the method has important significance for knowing the climate change, removing the atmospheric influence in remote sensing data and improving the remote sensing quantitative application level.
The optical thickness of the aerosol is one of the most important parameters of the aerosol, is an important physical quantity for representing the turbidity of the atmosphere, and is also an important factor for determining the climate effect of the aerosol and an important parameter of an atmosphere model. The optical thickness of the aerosol can be detected by ground-based detection methods such as solar radiometers, particle counters, radiation gauges, etc. The ground-based detection method can accurately provide local aerosol information, but cannot obtain aerosol space-time distribution in a large range. The remote sensing inversion of the optical thickness of the aerosol can overcome the inherent defect of a foundation detection method, and provides possibility for people to know the aerosol change in a large range in all weather and in real time.
In recent years, remote sensing inversion of aerosol optical thickness has become a means for quickly and effectively obtaining atmospheric aerosol information, particularly, good research results have been obtained in satellite remote sensing, and a relatively mature inversion algorithm has been provided, but the inversion of aerosol is mainly realized by establishing a lookup table through 6S by adopting a dark pixel method (or a dark target method), and most of the algorithms are specific to satellite data. The dark pixel method utilizes the characteristic that most of land surfaces have low reflectivity in red (0.6 to 0.68 mu m) and blue (0.40 to 0.48 mu m) wave bands, and judges the forest as the dark pixel according to the vegetation index (NDVI) or the reflectivity of a near infrared channel (2.1 mu m) and is used for inverting the optical thickness of the aerosol. When a maotai teacher uses a dark pixel method to invert the optical thickness of polluted aerosol in Beijing and hong Kong cities in a test, the maotai teacher considers that a method for determining the surface reflectivity of vegetation dark pixel red and blue channels by means of the near-infrared channel apparent reflectivity in a fixed proportion coefficient relation mode has a large error in the Beijing area. This indicates that there is a certain difficulty in inverting the optical thickness of the aerosol in Beijing area by using the dark pixel method. The comparison method is a satellite remote sensing method adopted for early research of the land pollution aerosol. In principle, NASA in the united states can give the optical thickness of aerosol in most regions of the world by using MODIS image, but the spatial resolution is only 10km, and the satellite height is more than 700 km, so that the optical thickness of aerosol in the whole convection layer is obtained, and the aerosol is mainly concentrated in a vertical range from the ground to a city boundary layer, so that the inversion of the optical thickness of aerosol in the city boundary layer from the airborne hyperspectral image becomes a concern.
Survey in the 20 th 70 s shows that the optical characteristics of the atmosphere can be obtained by inversion from airborne remote sensing data by adopting a high-contrast earth surface method. It is assumed that the optical characteristics of the atmosphere are invariant in two regions that are relatively close in spatial location. At both ground and airborne elevations, the earth-gas system radiation transmission parameters can be calculated by optical characterization of two high contrast surfaces (light and dark) located relatively close together. To this end, we tried to invert aerosol optical thickness from the acquired hyperspectral image data with high contrast surface method using a practical modular imaging spectrometer (OMIS-I) developed by the institute of physical and technical sciences at shanghai of the chinese academy of sciences, aeronautical remote sensing.
Disclosure of Invention
In order to overcome the defects, the invention mainly aims to provide a hyperspectral image obtained by an aviation hyperspectral remote sensor developed by an aviation remote sensing research laboratory of Shanghai technical and physical research institute of Chinese academy of sciences, and the inversion of the optical thickness of aerosol of an urban atmospheric boundary layer is realized by comparing two high-contrast ground objects at high altitude and on two different heights of the ground surface;
by 1) high altitude: two ground objects with large radiation value contrast are found from the aerial hyperspectral remote sensing image; 2) Ground surface: finding the spectral reflectivity of the ground object matched with the 1); 3) And (3) comparing: and calculating the atmospheric transmittance by comparing the high altitude with the ground, and the bright target with the dark target, and calculating the aerial hyperspectral remote sensing inversion boundary layer aerosol optical thickness by calculating the aerosol optical thickness.
The technical problem to be solved by the invention is as follows: the device is used for detecting the optical thickness of the aerosol on the boundary layer by aviation hyperspectral remote sensing inversion; the method aims to solve the problem of how to move from high altitude: finding out ground objects with two radiation values with larger radiation values from the aerial hyperspectral remote sensing image; from the ground: finding out the spectral reflectivity of the ground object matched with the high altitude; from the comparison: the air transmission rate is calculated by comparing the high altitude with the ground, and the bright target and the dark target, the optical thickness of the aerosol is calculated, and other related calculation methods, system software and other technical problems are solved.
The technical scheme adopted by the invention for solving the technical problems is as follows: a detection device for inverting the optical thickness of boundary layer aerosol through aviation hyperspectral remote sensing is characterized in that a part of solar radiation signals of a sunlight simulation module 1 are transmitted to a sensor 3 through direct absorption and scattering of the atmosphere, another part of solar radiation signals of the sunlight simulation module 1 are transmitted to a ground surface module 5 through atmosphere transmission, reflection signals of the ground surface module 5 are transmitted to the sensor 3 through the atmosphere again, meanwhile, solar radiation signals reflected by the ground surface module 5 are transmitted to a ground object spectrometer 8, and wireless signal transmission is adopted between the two signals.
The reflected signal of the surface module 5 comprises: a dark surface radiation signal of low reflectivity and a light surface radiation signal of high reflectivity.
The surface module 5 reflects the signal that reaches the sensor 3 again through the atmosphere, including: solar radiation signal 61 reflected by a dark surface, the reflectivity of a bright surface being R 0 (lambda) the solar radiation signal 62 reflected to the sensor 3 once, and the solar radiation signal reaching the sensor 3 after being reflected and diffused 63 by the atmosphere and reflected and scattered between the earth surface module 5 and the atmosphere in the ascending process.
A method for detecting aerosol optical thickness of a boundary layer by aviation hyperspectral remote sensing inversion is characterized in that two high-contrast ground objects at high altitude and two different heights of the ground surface are compared and aerosol optical thickness inversion calculation is carried out, so that inversion of aerosol optical thickness of an urban atmospheric boundary layer is realized, and the method comprises the following three parts:
high altitude: finding out ground objects with two radiation values with larger radiation values from the aerial hyperspectral remote sensing image;
ground surface: finding out the spectral reflectivity of the ground object matched with high altitude;
and (3) comparison: and calculating the atmospheric transmittance and calculating the optical thickness of the aerosol by comparing the high altitude with the ground and the bright target with the dark target.
The specific calculation steps of the aerosol optical thickness tau of the method for detecting the optical thickness of the aerosol at the inversion boundary layer by aviation hyperspectral remote sensing are as follows:
step 1: calculating the total radiance received at the sensor
By the formula:
L(λ)＝L 0 (λ)+L 1 (λ)R 0 (λ)+L 2 (λ)R 0 2 (λ)+...... ①
calculating;
in the formula: l (λ) is the total radiance received at the sensor;
L 0 (λ) is the portion of solar radiation that is directly scattered and scattered by the atmosphere from the sun and reflected by dark surfaces;
R 0 (λ) is the surface reflectivity unaffected by the atmosphere;
L 1 (λ)R 0 (λ) is the reflectance of the bright surface as R 0 (λ) primary reflection to the solar radiation part of the sensor;
L 2 (λ)R 0 2 (lambda) is the portion of the solar radiation that reaches the sensor (3) after multiple reflections and scatterings between the earth's surface and the atmosphere;
step 2: thin layer approximation
For an ideal thin layer atmosphere, the following single scattering linear approximation can be made:
L(λ)＝L 0 (λ)+L 1 (λ)R 0 (λ) ②
the same reason is that
R(λ)＝R (h) (λ)+R 0 (λ)t(λ) ③
In the formula: r (λ) is the spectral reflectance received at the sensor;
R (h) (λ) is spectral reflection on the background of a black body or direct reflection through the atmosphereThe emission rate;
R 0 (λ) is the surface reflectivity unaffected by the atmosphere;
t (λ) is an atmospheric permeability coefficient;
and 3, step 3: selecting and solving linear equations
Two test ground surfaces are selected, then
R (1) (λ)＝R (h) (λ)+R 0 (1) (λ)t(λ) ④
R (2) (λ)＝R (h) (λ)+R 0 (2) (λ)t(λ) ⑤
Solving these two linear equations yields:
t(λ)＝C(λ)/C 0 (λ)⑥
wherein: c (λ) = R (1) (λ)-R (2) (λ)
C 0 (λ)＝R 0 (1) (λ)-R 0 (2) (λ)
In the formula: r (1) (λ) is the reflectivity of the bright surface received on the sensor (3);
R (2) (λ) is the reflectivity of the dark surface received on the sensor (3);
R 0 (1) (λ) is the bright surface reflectance measured directly by the surface feature spectrometer without atmospheric influence;
R 0 (2) (λ) is the dark surface reflectance measured directly by the surface spectrometer without atmospheric influence;
and 4, step 4: calculating the value of tau
According to Lambert-Beer's law, one can obtain
Where τ is the aerosol optical thickness we require.
The specific working steps of the method for detecting the aerosol optical thickness of the aviation hyperspectral remote sensing inversion boundary layer are as follows:
a) Reading hyperspectral remote sensing images
Reading an airborne aviation hyperspectral remote sensing image in a standard format;
b) Converted into radiation values
Converting the DN value into a radiation value according to two coefficients of a slope and an intercept corresponding to each wave band in the radiation calibration file and a formula radiation value = DN value slope + intercept;
a) Selection and output
Selecting a ground surface with two types of radiation values with large contrast on the graph according to the radiation values obtained in the step 1, and outputting the radiation values of the two types of ground surfaces;
b) And determining
When the radiation value of one pixel is more than 80% of other pixels in the same row or column, the channel A is executed and then enters a bright earth surface radiation value module, and the value is Rad (1) (λ)；
When the radiation value of one pixel is less than 80% of other pixels in the same row or column, the channel B is executed and enters a dark surface radiation value module with the value of Rad (2) (λ)；
a) And calculating
And (3) calculating the bright surface radiation value and the dark surface radiation value output in the step (2) according to the following formula:
R＝π*L/(μ*f)
in the formula: r is the apparent reflectance;
l is the radiation value;
mu is the cosine of the zenith angle of the sun;
f is the solar radiation flux density of the upper air boundary;
b) Obtaining the apparent reflectance
The output value of the bright earth surface radiation value module is calculated as the bright earth surface apparent reflectivity obtained on the sensor, which is R (1) (λ)；
The output value of the dark surface radiation value module is calculated as the apparent reflectivity of the dark surface obtained on the sensor, namely R (2) (λ)；
Step 4, selecting high-contrast ground surface of foundation
a) Selective surface feature spectrum
The surface feature spectrum measured by the surface feature spectrometer is a surface feature spectrum library, and the surface feature spectrum which is the same as or similar to the two types of surface features selected in the step 2 is found out from the spectrum database;
b) Obtaining the reflectance
The spectral output value of the bright earth surface ground object is calculated as the bright earth surface reflectivity which is R 0 (1) (lambda), the spectral output of the dark surface feature is calculated as the dark surface reflectance, R 0 (2) (λ)；
a) And calculating
According to formula (6)
t(λ)＝C(λ)/C 0 (λ) ⑥
Calculating;
b) Obtaining the atmospheric transmittance;
calculating the atmospheric transmittance from the bright surface apparent reflectivity and the dark surface apparent reflectivity of the airborne bright/dark surface obtained in the step (3) and the bright surface reflectivity and the dark surface reflectivity of the foundation bright/dark surface obtained in the step (4);
a) And calculating
According to formula (7)
Calculating;
b) Optical thickness of aerosol
Inputting the atmospheric transmittance calculated in the step 5 and the output value of the atmospheric transmittance module into an aerosol optical thickness module to calculate the optical thickness of the aerosol;
step 7, verifying the optical thickness of the aerosol
a) Calculating the ground distance
The synchronous ground visibility range data is calculated according to the formula
V＝3.91·H·1/τ
In the formula: v is the ground visibility range (m);
h is aerosol elevation in different seasons;
τ is the aerosol optical thickness;
b) And comparing the results
1) The output signal of the aerosol optical thickness module is transmitted to the input end of the verification module;
2) Comparing the calculated optical thickness value of the aerosol with the optical thickness value of the aerosol obtained in the step 6;
3) If the difference value of the two is less than 0.1, transmitting the output signal of the verification module to an output module, and outputting the optical thickness of the aerosol; otherwise, feeding back to the output end of the radiation value module, feeding back to the step 2 for optimization, and reselecting the earth surface.
And (4) outputting the optical thickness of the aerosol output by the module, wherein the optical thickness of the aerosol is the optical thickness value of the aerosol verified in the step (7).
The invention has the beneficial effects that: the invention compares bright/dark two high-contrast ground objects at two different heights of the high altitude and the ground surface to realize the inversion of the optical thickness of the aerosol at the boundary layer of the urban atmosphere, which is different from the conventional method of calculating the optical thickness of the aerosol through a height layer or a fixed ground object; the method is different from the traditional remote sensing image in that the method is mainly characterized by high spectral resolution and the like.
Drawings
FIG. 1 is a schematic structural diagram of a detection device according to the present invention;
FIG. 2 is a schematic diagram of a calculation process for inverting the optical thickness of an aerosol according to the present invention;
FIG. 3 is a schematic diagram showing the positions of a bright surface and a dark surface in a first embodiment of the present invention;
FIG. 4 is a schematic diagram of the apparent reflectance curves of a light surface and a dark surface at points 13 and 14, respectively, in accordance with an embodiment of the present invention;
FIG. 5 is a graph showing the calculated variation of atmospheric transmittance with wavelength according to a first embodiment of the present invention;
FIG. 6 is a schematic diagram illustrating an optical thickness of an aerosol obtained by inverting a hyperspectral remote sensing image of an airborne imaging spectrometer system OMIS according to an earth surface reflection method of the present invention;
FIG. 7 is a schematic view showing the positions of a bright surface and a dark surface in the second embodiment of the present invention;
FIG. 8 is a schematic representation of the apparent reflectance curves at points 13 and 14 for a second bright surface and a dark surface in accordance with an embodiment of the present invention;
FIG. 9 is a graph showing the calculated change of atmospheric transmittance with wavelength according to the second embodiment of the present invention;
FIG. 10 is a schematic diagram of the optical thickness of the aerosol obtained by inverting the OMIS hyperspectral remote sensing image from the airborne imaging spectrometer system according to the two earth surface reflection methods of the embodiment of the invention;
the reference numbers in the figures illustrate:
1-a sunlight simulation module;
2-solar radiation signal;
3-a sensor;
4-atmospheric transmission;
5-a surface module;
8-a surface feature spectrometer;
10-reading a hyperspectral remote sensing image;
20-radiation value;
21-channel A;
22-channel B;
31-bright surface radiance values;
32-dark surface radiation value;
40-a ground object spectrum library;
51-bright surface apparent reflectance;
52-dark surface apparent reflectance;
53-Bright Earth surface reflectance;
54-dark surface reflectance;
60-atmospheric permeability;
61-solar radiation signal reflected by dark surface;
62-Bright surface with a reflectance of R 0 (λ) a solar radiation signal reflected once to the sensor;
63-after reflection, the diffusion part is generated by atmosphere in the ascending process;
70-aerosol optical thickness;
80-verification;
90-output;
Detailed Description
The invention is further described below with reference to the drawings and examples.
Referring to the structure schematic diagram of the detection device shown in fig. 1, the detection device for inverting the optical thickness of the boundary layer aerosol by the aviation hyperspectral remote sensing is provided, a part of solar radiation signals 2 of a sunlight simulation module 1 are transmitted to a sensor 3 through direct absorption and scattering of the atmosphere, another part of solar radiation signals of the sunlight simulation module 1 are transmitted to a ground surface module 5 through atmosphere transmission 4, reflected signals of the ground surface module 5 are transmitted to the sensor 3 through the atmosphere again, meanwhile, the solar radiation signals 2 reflected by the ground surface module 5 are transmitted to a ground feature spectrometer 8, and wireless signal transmission is carried out between the two.
The detection device for inverting the optical thickness of the aerosol at the boundary layer by aviation hyperspectral remote sensing comprises a reflection signal of a ground surface module 5: dark surfaces of low reflectivity, bright surfaces of high reflectivity, and the like.
A detection apparatus for aviation high spectrum remote sensing inversion boundary layer aerosol optical thickness, its earth's surface module 5 reflection reachs the signal that reaches sensor 3 through the atmosphere again includes: the dark surface reflected solar radiation portion 61, the bright surface having a reflectivity of R 0 The lambda is reflected to the solar radiation part 62 of the sensor once, and then reaches the solar radiation signal of the sensor 3 after being reflected and scattered by the atmosphere generation diffusion part 63 and the earth surface module 5 and the atmosphere in the ascending process.
In fig. 1: the sunlight simulation module 1 is either sunlight or solar radiation, and a solar radiation signal 2 reaches the sensor 3 through the direct absorption and scattering action of the atmosphere; sensor 3Solar radiation signals and earth surface reflections received above; the solar radiation 2 reaches the earth surface module 5 after passing through the atmosphere transmission 4; the surface module 5 is various ground objects, including a dark surface with low reflectivity and a bright surface with high reflectivity; reflected by the surface module 5 to the sensor 3 again through the atmosphere, including: solar radiation 61 reflected by a dark surface, the reflectivity of a bright surface being R 0 (lambda) the solar radiation signal 62 reflected to the sensor for the first time and the solar radiation signal reaching the sensor 3 after being diffused 63 by the atmosphere and being reflected and scattered for multiple times between the earth surface module 5 and the atmosphere in the ascending process after being reflected; the solar radiation signal reflected by the earth surface module 5 directly enters the ground substance spectrometer without passing through the atmosphere8; spectral reflectance of the feature measured by the feature spectrometer 8.
Therefore, the signal received at the angle of the sensor 3 is superimposed by three parts:
part I: the scattered light of the solar radiation scattered directly to the sensor 3 via the atmosphere or the reflected light 61 of the solar radiation reflected to the sensor 3 via the dark surface is combined into a first portion L 0 (λ)；
Part II: sunlight penetrates through the atmosphere to pass through the bright surface in the descending process, and the reflectivity is R 0 (lambda) the target reflected light 62 reflected to the sensor at one time and the part 63 diffused by the atmosphere in the process of going upwards after being reflected by the ground surface are synthesized into a second part L 1 (λ)R 0 (λ)；
Part III: the third portion L of the solar radiation 64 reaching the sensor 3 after multiple reflections and scatterings between the surface module 5 and the atmosphere 2 (λ)R 0 2 (λ)+......。
Such a process can be written as:
L(λ)＝L 0 (λ)+L 1 (λ)R 0 (λ)+L 2 (λ)R 0 2 (λ)+…… ①
where L (λ) is the total radiance received at the sensor 3. For an ideal thin layer atmosphere, the following single scattering linear approximation (thin layer approximation) can be made:
L(λ)＝L 0 (λ)+L 1 (λ)R 0 (λ) ②
in the same way
R(λ)＝R (h) (λ)+R 0 (λ)t(λ) ③
Where R (λ) is the spectral reflectance received at the sensor 3; r (h) (λ) is the spectral reflectance on the background of direct reflection through the atmosphere or black body (near zero reflection); r 0 (λ) is the surface reflectivity unaffected by the atmosphere; t (λ) is an atmospheric transmittance. Two tests were selectedThe ground testing materials are as follows
R (1) (λ)＝R (h) (λ)+R 0 (1) (λ)t(λ) ④
R (2) (λ)＝R (h) (λ)+R 0 (2) (λ)t(λ) ⑤
Solving these two linear equations yields:
t(λ)＝C(λ)/C 0 (λ) ⑥
wherein C (λ) = R (1) (λ)-R (2) (λ)
C 0 (λ)＝ R 0 (1) (λ)-R 0 (2) (λ)
Note that: r (1) (λ) is the reflectance of the bright surface (or called bright surface apparent reflectance) received on the sensor 3; r (2) (λ) is the reflectance of the dark surface (or dark surface apparent reflectance) received at the sensor 3; r is 0 (1) (λ) is the bright surface reflectance measured directly by the surface spectrometer 8 unaffected by the atmosphere; r 0 (2) And (λ) is the dark surface reflectance (or so-called dark surface reflectance) measured directly by the geophysical spectrometer 8 unaffected by the atmosphere.
According to Lambert-Beer law, the method can obtain
Where τ is the aerosol optical thickness we require.
Referring to the attached figure 2, the schematic diagram of the calculation process of the inversion aerosol optical thickness of the invention is shown, and the method for detecting the optical thickness of the aerosol at the boundary layer by aviation hyperspectral remote sensing inversion is implemented by comparing two high-contrast ground objects at two different heights of the high altitude and the ground surface and inverting the aerosol optical thickness calculation, so that the inversion of the aerosol optical thickness at the urban atmospheric boundary layer is realized, and comprises three parts:
high altitude: finding ground objects with large radiation value pairs from the aerial hyperspectral remote sensing images;
ground surface: finding out the spectral reflectivity of the ground object matched with high altitude;
and (3) comparison: and calculating the atmospheric transmittance and calculating the optical thickness of the aerosol by comparing the high altitude with the ground and the bright target with the dark target.
The specific calculation steps of the aerosol optical thickness tau of the method for detecting the optical thickness of the aerosol at the inversion boundary layer by aviation hyperspectral remote sensing are as follows:
step 1: calculating the total radiance received at the sensor 3
By the formula:
L(λ)＝L 0 (λ)+L 1 (λ)R 0 (λ)+L 2 (λ)R 0 2 (λ)+...... ①
calculating;
in the formula: l (λ) is the total radiance received at the sensor 3;
L 0 (λ) is the solar radiation signal 2 scattered and scattered directly by the atmosphere and the solar radiation signal 61 reflected by the dark surface;
R 0 (λ) is the surface reflectivity unaffected by the atmosphere;
L 1 (λ)R 0 (λ) is the reflectance of the bright surface as R 0 (λ) the solar radiation signal 62 reflected once to the sensor 3;
L 2 (λ)R 0 2 (λ) is the solar radiation signal arriving at the sensor 3 after multiple reflections and scattering between the earth's surface and the atmosphere;
step 2: thin layer approximation
For an ideal thin layer atmosphere, the following linear approximation of single scattering can be made:
L(λ)＝L 0 (λ)+L 1 (λ)R 0 (λ) ②
in the same way
R(λ)＝R (h) (λ)+R 0 (λ)t(λ) ③
In the formula: r (λ) is the spectral reflectance received at the sensor 3;
R (h) (λ) is the spectral reflectance through atmospheric direct reflection or on a black body background;
R 0 (λ) is the surface reflectivity unaffected by the atmosphere;
t (λ) is an atmospheric permeability coefficient;
and 3, step 3: selecting and solving linear equations
Two test ground surfaces are selected, then
R (1) (λ)＝R (h) (λ)+R 0 (1) (λ)t(λ) ④
R (2) (λ)＝R (h) (λ)+R 0 (2) (λ)t(λ) ⑤
Solving these two linear equations yields:
t(λ)＝C(λ)/C 0 (λ) ⑥
wherein: c (λ) = R (1) (λ)-R (2) (λ)
C 0 (λ)＝R 0 (1) (λ)-R 0 (2) (λ)
In the formula: r is (1) (λ) is the reflectivity of the bright surface received on sensor 3;
R (2) (λ) is the reflectivity of the dark surface received on the sensor 3;
R 0 (1) (λ) is the bright surface reflectance measured directly by the surface spectrometer 8 unaffected by the atmosphere;
R 0 (2) (λ) is the dark surface reflectance measured directly by the geophysical spectrometer 8 unaffected by the atmosphere;
and 4, step 4: calculating the value of tau
According to Lambert-Beer's law, one can obtain
⑦
Where τ is the aerosol optical thickness we require.
The specific working steps of the method for detecting the aerosol optical thickness of the aviation hyperspectral remote sensing inversion boundary layer are as follows:
a) Reading the hyperspectral remote sensing image 10
Reading an airborne aviation hyperspectral remote sensing image 10 in a standard format;
b) Converted into an emission value of 20
Converting the DN value into a radiation value 20 according to two coefficients of a slope and an intercept corresponding to each wave band in the radiation calibration file and a formula radiation value = DN value slope + intercept;
a) Selection and output
According to the magnitude of the radiation value 20 obtained in the step 1, selecting a ground surface with two types of radiation values 20 with large contrast ratio on the graph, and outputting the radiation values 20 of the two types of ground surfaces;
b) And determining
When the radiation value of one pixel is more than 80% of other pixels in the same row or column, the pixel enters a bright earth surface radiation value 31 module after executing 21-channel A, and the value is Rad (1) (λ)；
When the radiation value of one pixel is less than 80% of other pixels in the same row or column, executing 22-channel B, and entering a dark earth surface radiation value 32 module with the value of Rad (2) (λ)；
a) And calculating
Calculating the bright surface radiation value 31 and the dark surface radiation value 32 output in the step 2 according to the following formulas:
R＝π*L/(μ*f)
in the formula: r is the apparent reflectivity;
l is the radiation value;
mu is the cosine of the zenith angle of the sun;
f is the solar radiation flux density of the upper atmosphere;
b) Obtaining the apparent reflectance
The output of the bright surface radiance 31 module is calculated as the bright surface apparent reflectance 51 at the sensor 3, R (1) (λ)；
The output of the dark surface radiation value 32 module is calculated as the apparent dark surface reflectance 52 obtained at the sensor 3, R (2) (λ)；
Step 4, selecting high-contrast ground surface of foundation
a) Selective surface feature spectrum
The surface feature spectrum measured by the surface feature spectrometer 8 is used as a surface feature spectrum library 40, and the surface feature spectrum which is the same as or similar to the two types of surface features selected in the step 2 is found from the spectrum database;
b) Obtaining the reflectance
The spectral output of the bright surface feature is calculated as the bright surface reflectance 53, R 0 (1) (λ), the spectral output of the dark surface feature is calculated as the dark surface reflectance 54, R 0 (2) (λ)；
a) And calculating
According to formula (6)
t(λ)＝C(λ)/C 0 (λ) ⑥
Calculating;
b) Obtaining an atmospheric transmittance of 60;
calculating the atmospheric transmittance 60 from the bright surface apparent reflectivity 51 and the dark surface apparent reflectivity 52 of the vehicle-mounted bright/dark surface obtained in the step 3 and from the bright surface reflectivity 53 and the dark surface reflectivity 54 of the foundation bright/dark surface obtained in the step 4;
a) And calculating
According to formula (7)
Calculating;
b) Aerosol optical thickness 70
Inputting the output values of the atmospheric transmittance 60 module and the atmospheric transmittance 60 module calculated in the step 5 into an aerosol optical thickness 70 module, and calculating the aerosol optical thickness 70;
step 7, verifying the optical thickness of the aerosol
a) Calculating the ground distance to see
The synchronous ground visibility range data is calculated according to the formula
V＝3.91·H·1/τ
In the formula: v is the ground visibility range (m);
h is the aerosol elevation in different seasons;
τ is the aerosol optical thickness;
b) And making a judgment and comparison
1) The output signal of the aerosol optical thickness 70 module is transmitted to the input of the verification 80 module;
2) Comparing the calculated aerosol optical thickness value with the aerosol optical thickness 70 obtained in step 6;
3) If the difference value of the two is less than 0.1, transmitting the output signal of the verification module 80 to an output module 90, and outputting the aerosol optical thickness 70; otherwise, feeding back to the output end of the radiation value 20 module, feeding back to the step 2 for optimization, and reselecting the earth surface.
The aerosol optical thickness 90 output by the output 90 module is the aerosol optical thickness value 70 verified in step 7.
By applying the method, high reflection difference earth surfaces (bright surfaces and dark surfaces) are respectively selected from OMIS images of an aviation hyperspectral remote sensor imaging spectrometer system researched by an aviation remote sensing research laboratory of Shanghai technical and physical institute of Chinese academy, and the calculation flow of inverting the optical thickness of the aerosol is shown in figure 2.
The working principle of the invention is as follows: the gas molecules and aerosol in the atmosphere scatter and absorb the radiation signal of the sunlight, and the target spectral response received by the sensor 3 is influenced. Due to the existence of the atmosphere, the surface module 5 receives the direct light and the sky light absorbed and scattered by the atmosphere and then reflects the direct light and the sky light, as shown in fig. 1.
The specific working steps of the embodiment of the invention are as follows:
Reading an airborne aviation hyperspectral remote sensing image 10 in a standard format provided by Shanghai technical and physical research of Chinese academy of sciences, and converting a numerical number DN (numerical number) value into a radiation value 20 according to a formula radiation value = DN value x slope + intercept and two coefficients of slope and intercept corresponding to each wave band in a radiometric calibration file;
According to the radiation value obtained in step 1, selecting two ground features with high contrast ratio on the map, and outputting the radiation value 20 of the two ground features, when the radiation value of a certain pixel is greater than 80% of other pixels in the same row or column, executing 21-channel A, and recording as bright ground surface radiation value 31 (Rad) (1) (λ)); when the radiation value of a certain pixel is less than 80% of other pixels in the same row or column, executing 22-channel B, and recording as dark surface radiation value 32 (Rad) (2) (λ))；
The bright surface radiation value 31 and the dark surface radiation value 32 of the bright surface and the dark surface output in the step 2 are calculated according to the formula
R＝π*L/(μ*f)
And (3) annotation: r is the apparent reflectance; l is the radiation value; mu is the cosine of the zenith angle of the sun; f is the solar radiation flux density of the upper air boundary;
the apparent reflectance obtained at the sensor 3 was calculated and recorded as 51-bright surface appearanceReflectivity R (1) (λ) and 52-dark surface apparent reflectance R (2) (λ)；
Step 4, selecting high-contrast ground surface of foundation
From the surface feature spectrum library 40 formed by the surface feature spectra measured by the surface feature spectrometer 8, the surface feature spectra identical or similar to the two types of surface features selected in step 2 are found, and are respectively recorded as 53-bright surface reflectance R 0 (1) (λ) and 54-dark surface reflectance R 0 (2) (λ)；
Calculating the atmospheric transmittance 60 from the apparent reflectance of the vehicle bright/dark surface obtained in step 3, the bright surface apparent reflectance 51 and the dark surface apparent reflectance 52, and the surface reflectance of the foundation bright/dark surface obtained in step 4, the bright surface reflectance 53 and the dark surface reflectance 54, according to the formula (6);
Calculating the aerosol optical thickness 70 from the calculated atmospheric transmittance 60 of step 5 according to equation (7);
step 7, verifying the optical thickness of the aerosol
The synchronous ground visibility range data is calculated according to the formula
V＝3.91·H·1/τ
Note that: v is the ground visibility range (m);
h is aerosol elevation in different seasons (776.4 m in Shanghai and winter);
τ is the aerosol optical thickness 70.
Comparing 80 the calculated aerosol optical thickness value 70 with the aerosol optical thickness value 70 obtained in the step 6, and when the difference value between the calculated aerosol optical thickness value 70 and the aerosol optical thickness value 70 is less than 0.1, executing the step 8, and outputting 90 the aerosol optical thickness value 70; otherwise, returning to the step 2 for optimization and reselecting the ground object.
The final output aerosol optical thickness 90 is the aerosol optical thickness value 70 verified in step 7.
The embodiment of the detection method of the invention is as follows:
referring to fig. 3, 4, 5 and 6, high contrast earth surfaces are respectively selected for hyperspectral images of an imaging spectrometer system OMIS in 2002, 10 months and 7 days in Shanghai, the optical thickness of aerosol is inverted according to a technical flow chart of the invention, the numerical serial number DN value of the hyperspectral images of the imaging spectrometer system OMIS is firstly converted into a radiation value through step 1, a bright surface (corresponding to a cement ground of a square) and a dark surface (corresponding to a polluted water body on Huangpu river) are selected from the radiation values, and fig. 3 is a schematic position diagram of the bright surface and the dark surface in the first embodiment; FIG. 4 is a plot of the apparent reflectance at points 13 and 14 for a light surface and a dark surface, respectively, with wavelength (nm) on the x-axis and apparent reflectance on the y-axis; then, selecting a corresponding surface feature spectral reflectivity from a surface feature spectral database, and calculating the atmospheric transmittance according to a formula (6) in step 5, wherein fig. 5 is a curve of the calculated atmospheric transmittance along with the wavelength, a dotted line is an atmospheric transmittance curve at 13 points, a solid line is an atmospheric transmittance curve at 14 points, an x axis is the wavelength (nm), and a y axis is the atmospheric transmittance; then, the optical thickness of the aerosol is obtained according to the formula (7) in step 6, and fig. 6 shows the optical thickness of the aerosol obtained by inverting the hyperspectral remote sensing image of the airborne imaging spectrometer system OMIS according to the earth surface reflection method of the invention, wherein the black line represents the optical thickness value of the aerosol at 13 points, the red line represents the optical thickness of the aerosol at 14 points, the x axis is the wavelength (nm), and the y axis is the optical thickness value of the aerosol.
The second embodiment of the detection method of the invention is as follows:
referring to fig. 7, 8, 9 and 10, in the same way, for another imaging spectrometer system OMIS hyperspectral image, a high-contrast earth surface is respectively selected, which is the same as the first embodiment, according to the technical flow chart of the invention, the aerosol optical thickness is inverted, the selected bright surface corresponds to the rupu great bridge approach bridge surface cement land, the dark surface corresponds to the polluted water body on the yellow pu river, and fig. 7 is a schematic diagram of the positions shown by the bright surface and the dark surface in the second embodiment; FIG. 8 is a plot of the apparent reflectance at points 13 and 14 for a light surface and a dark surface, with wavelength (nm) on the x-axis and apparent reflectance on the y-axis; FIG. 9 is a plot of calculated atmospheric transmittance versus wavelength, with wavelength (nanometers) on the x-axis and atmospheric transmittance on the y-axis; FIG. 10 is the optical thickness of the aerosol obtained by the surface reflection method from the airborne OMIS hyperspectral remote sensing image according to the present invention, wherein the x-axis is the wavelength (nm) and the y-axis is the optical thickness value of the aerosol.
It can be seen from the graphs shown in the two examples that the curves shown have similar trends due to the consistent criteria for selecting the bright/dark surface, the light surface being cement ground and the dark surface being water surface with more severe pollution.
Inquiring and displaying according to historical air quality data of an environmental monitoring center in Shanghai city: the air quality of Shanghai city at 2002-10-713 o is generally better, and sulfur dioxide (SO) 2 ) The concentration is 0.051mg/m 3 Nitrogen dioxide (NO) 2 ) The concentration is 0.044mg/m 3 Nitrogen oxide (NOx) concentration of 0.051mg/m 3 Inhalable Particles (PM) 10 ) The concentration is 0.124mg/m 3 The Air Pollution Index (API) is in a good grade, the air quality is equivalent to the level II of the environmental air quality Standard (GB 3095-1996), and the main pollutants are inhalable particles PM 10 And the pollution is weak. The inverted aerosol optical thickness (see table-1) is numerically acceptable.
TABLE-1: OMIS inverts aerosol optical thickness:
an experimental test of aerosol optical thickness inversion is carried out on OMIS hyperspectral image data of 10, month and 7 days in 2002 by using a surface contrast method, a preliminary inversion result is given, and the aerosol optical thickness value at a wavelength range of 502nm to 590nm is between 0.175 and 0.314. The inversion result is compared with the aerosol optical thickness result (table-2) calculated according to the meteorological visibility, and the consistency is better. The optical thickness of the aerosol at the urban boundary layer can be inverted by airborne hyperspectral image data with high spatial resolution by adopting a contrast earth surface method, but the method is still in experimental attempts.
TABLE-2 Aerosol optical thickness calculated from visibility data
| Time-piece Carving tool | (Pudong) Station Instantaneous moment Can see Distance (m) | Pudong station Ten minutes Mean energy Distance between two adjacent plates (m) | XU HUI Station Instantaneous moment of action Can see Distance (m) | Xuhui station Ten minutes Mean energy Distance of sight (m) | Bolus of Cambodia Instant of park station Can see at the time Distance (m) | Bolus of Cambodia Station ten Medicine for treating chronic hepatitis B All can see Distance (m) | Fuel tank Instant driver station Can see at the time Distance (m) | Fuel rail Driver station ten Medicine for treating chronic hepatitis B All can see Distance (m) | Aod tablet Mean value (550nm) |
| 13: 00 13: 10 13: 20 13: 30 13: 40 13: 50 14: 00 | 11050 9648 9253 12320 9735 8556 8693 | 9897 9397 9678 9585 9442 9775 8684 | 8536 10283 8217 9610 8313 8663 7390 | 9573 9273 8865 8751 8376 8485 7752 | 14917 12899 14058 14471 13846 11368 11925 | 15242 15504 16321 13295 15522 13140 12961 | 10809 12267 7145 10306 9743 9096 9931 | 10368 11102 10122 9892 9909 10231 9850 | 0.279 0.278 0.310 0.283 0.299 0.313 0.325 |
| 0.298 |
Claims (1)
1. A detection method for inverting optical thickness of boundary layer aerosol by aviation hyperspectral remote sensing is characterized by comprising the following steps: comprises two parts:
1) The calculation steps of the aerosol optical thickness tau are as follows:
a) Calculating the total radiance received at the sensor
By the formula:
L(λ)＝L 0 (λ)+L 1 (λ)R 0 (λ)+L 2 (λ)R 0 2 (λ)+…… ①
calculating;
in the formula: l (λ) is the total radiance received at the sensor;
L 0 (lambda) is a radiation signal (2) of the solar radiation signal of the solar light simulation module (1) directly scattered and scattered by the atmosphere and a solar radiation signal (61) reflected by the dark surface;
R 0 (λ) is the surface reflectivity unaffected by the atmosphere;
L 1 (λ)R 0 (λ) is the reflectance of the bright surface as R 0 (λ) a solar radiation signal (62) reflected once to the sensor (3);
L 2 (λ)R 0 2 (lambda) is a solar radiation signal transmitted to the sensor (3) after multiple reflection and scattering between the earth surface module (5) and the atmosphere;
b) Thin layer approximation
For an ideal thin layer atmosphere, the following single scattering linear approximation can be made:
L(λ)＝L 0 (λ)+L 1 (λ)R 0 (λ) ②
in the same way
R(λ)＝R (h) (λ)+R 0 (λ)t(λ) ③
In the formula: r (λ) is the spectral reflectance received at the sensor;
R (b) (λ) is the spectral reflectance through the atmosphere directly or on a black body background;
R 0 (λ) is the surface reflectivity unaffected by the atmosphere;
t (λ) is an atmospheric permeability coefficient;
c) Selecting and solving linear equations
Two test ground surfaces are selected, then
R (1) (λ)＝R (h) (λ)+R 0 (1) (λ)t(λ) ④
R (2) (λ)＝R (h) (λ)+R 0 (2) (λ)t(λ) ⑤
Solving these two linear equations yields:
t(λ)＝C(λ)/C 0 (λ) ⑥
wherein: c (λ) = R (1) (λ)-R (2) (λ)
C 0 (λ)＝R 0 (1) (λ)-R 0 (2) (λ)
In the formula: r (1) (λ) is the reflectivity of the bright surface received on the sensor (3);
R (2) (λ) is the reflectivity of the dark surface received on the sensor (3);
R 0 (1) (λ) is the bright surface reflectance measured directly by the surface spectrometer (8) unaffected by the atmosphere;
R 0 (2) (λ) is the dark surface reflectance measured directly by the surface spectrometer without atmospheric influence;
d) Calculating the optical thickness of an aerosol
According to Lambert-Beer law, the method can obtain
Wherein τ is the aerosol optical thickness we require;
2) The steps of inverting the optical thickness of the aerosol are as follows:
a) Radiometric calibration of hyperspectral remote sensing image data
a) Reading hyperspectral remote sensing image (10)
Reading an airborne aviation hyperspectral remote sensing image (10) in a standard format;
b) Conversion to radiation value (20)
Converting the DN value into a radiation value (20) according to two coefficients of a slope and an intercept corresponding to each wave band in the radiation calibration file and a formula radiation value = DN value slope + intercept;
b) Selection of airborne high contrast surfaces
a) Selection and output
Selecting a ground surface with large contrast of two radiation values (20) on the map according to the size of the radiation value (20) obtained in the step A), and outputting the radiation values (20) of the two ground surfaces;
b) And determining
When the radiation value of one pixel is greater than 80% of other pixels in the same row or column, the channel A (21) is executed and then the channel A enters a bright earth surface radiation value (31) module, and the radiation value is Rad (1) (λ)；
When the radiation value of one pixel is less than 80% of other pixels in the same row or column, the channel B (22) is executed and then the channel B enters a dark surface radiation value (32) module, and the radiation value is Rad (2) (λ)；
C) Calculating apparent reflectance
a) And calculating
Calculating the bright surface radiation value (31) and the dark surface radiation value (32) output by the step B) according to the following formulas:
R＝π*L/(μ*f)
in the formula: r is the apparent reflectivity;
l is the radiation value;
mu is the cosine of the zenith angle of the sun;
f is the solar radiation flux density of the upper atmosphere;
b) Obtaining the apparent reflectance
The output of the bright surface radiance (31) module is calculated as the bright surface apparent reflectance (51) obtained at the sensor, R (1) (λ)；
The output of the dark surface radiation value (32) module is calculated as the apparent dark surface reflectance (52) obtained at the sensor, R (2) (λ)；
D) Selection of high contrast ground surface of foundation
a) Selective surface feature spectrum
The surface feature spectrum measured by the surface feature spectrometer (8) is a surface feature spectrum database (40), and the surface feature spectra which are the same as or similar to the two types of surface features selected in the step B) are found from the spectrum database;
b) Obtaining the reflectance
The spectral output of the bright surface feature is calculated as the bright surface reflectance (53), R 0 (1) (λ), the dark surface feature spectral output is calculated as the dark surface reflectance (54), R 0 (2)(λ)；
E) Airborne and ground-based contrast atmospheric permeability calculation
a) And calculating
According to formula (6)
t(λ)＝C(λ)/C 0 (λ) ⑥
Calculating;
b) Obtaining an atmospheric transmittance (60);
calculating the atmospheric transmittance (60) from the bright surface apparent reflectance (51) and the dark surface apparent reflectance (52) of the vehicle-mounted bright/dark surface obtained in the step C) and from the bright surface reflectance (53) and the dark surface reflectance (54) of the foundation bright/dark surface obtained in the step D);
f) Calculation of boundary layer aerosol optical thickness
a) And calculating
According to formula (7)
Calculating;
b) Optical thickness of aerosol
Inputting the output value of the atmospheric transmittance (60) module calculated in the step E) and the output value of the atmospheric transmittance (60) module into an aerosol optical thickness (70) module to calculate the aerosol optical thickness (70);
g) Verifying aerosol optical thickness
a) Calculating the ground distance to see
The synchronous ground visibility range data is calculated according to the formula
V＝3.91·H·1/τ
In the formula: v is the ground visibility range (m);
h is aerosol elevation in different seasons;
τ is the aerosol optical thickness;
b) And comparing the results
1) The output signal of the aerosol optical thickness (70) module is transmitted to the input of the verification (80) module;
2) Comparing the calculated aerosol optical thickness value with the aerosol optical thickness (70) obtained in step F);
3) If the difference is < 0.1, transmitting the output signal of the verification module (80) to an output module (90) to output the aerosol optical thickness (70); otherwise, feeding back to the output end of the radiation value (20) module, feeding back to the step B), optimizing, and reselecting the earth surface;
h) Output aerosol optical thickness
And outputting (90) the optical thickness of the aerosol output by the module, wherein the optical thickness of the aerosol is the value (70) of the optical thickness of the aerosol verified in the step G).
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| CN101329173B (en) * | 2008-07-07 | 2010-06-02 | 武汉大学 | Method for correcting feculent water body atmosphere |
| CN102346247B (en) * | 2010-07-30 | 2013-08-07 | 中国科学院遥感应用研究所 | Computing method and calibration method for HJ-1B B08 effective waveband width |
| CN101936881B (en) * | 2010-09-15 | 2012-10-03 | 吉林大学 | Tomography method of using limb sounding data for inverting atmospheric ozone profiles |
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| CN102103204B (en) * | 2011-01-26 | 2013-05-22 | 环境保护部卫星环境应用中心 | Inversion method for land aerosols optical thickness based on environment satellite 1 |
| CN102539336B (en) * | 2011-02-01 | 2013-10-09 | 环境保护部卫星环境应用中心 | Method and system for estimating inhalable particles based on HJ-1 satellite |
| CN102435586B (en) * | 2011-09-16 | 2014-04-16 | 北京师范大学 | Method and system for generating earth surface albedo product |
| CN102565007B (en) * | 2011-12-20 | 2014-11-26 | 中国人民解放军63655部队 | Inversion method for transmittance of whole atmosphere |
| CN105975777B (en) * | 2016-05-04 | 2021-01-26 | 中国科学院合肥物质科学研究院 | Surface albedo remote sensing model considering influence of actual sky light distribution |
| CN106291590A (en) * | 2016-11-10 | 2017-01-04 | 中国科学院合肥物质科学研究院 | The method calculating whole atmosphere aerosol optical depth based on lidar measurement data |
| CN109001091B (en) * | 2018-07-18 | 2019-06-04 | 北京航天宏图信息技术股份有限公司 | Satellite remote-sensing monitoring method, device and the computer-readable medium of atmosphere pollution |
| CN109186474A (en) * | 2018-10-11 | 2019-01-11 | 南京信息工程大学 | A kind of aerosol optical depth inverting bias correction method based on ridge regression |
| CN111123382B (en) * | 2019-12-25 | 2020-11-13 | 中国科学院遥感与数字地球研究所 | Aerosol and surface parameter joint inversion method |
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE4309417A1 (en) * | 1992-09-04 | 1994-04-14 | Laudam Joachim Dipl Geophys | Diode laser spectrometer for measuring trace gases and aerosols, in stratosphere - has mirrors, diode laser, lens, detector and cooling arrangements mounted on part deployable from aircraft fuselage |
| CN2508243Y (en) * | 2001-11-16 | 2002-08-28 | 中国科学院安徽光学精密机械研究所 | Long-range differential absorption spectrum gas pollution monitor |
| JP2003042943A (en) * | 2001-08-01 | 2003-02-13 | Japan Atom Energy Res Inst | Spectrometry for high-speed signal |
| US20050073683A1 (en) * | 2001-10-25 | 2005-04-07 | The Regents Of The University Of California | Real-time detection method and system for identifying individual aerosol particles |
-
2005
- 2005-07-05 CN CNB2005100275255A patent/CN100362319C/en not_active Expired - Fee Related
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE4309417A1 (en) * | 1992-09-04 | 1994-04-14 | Laudam Joachim Dipl Geophys | Diode laser spectrometer for measuring trace gases and aerosols, in stratosphere - has mirrors, diode laser, lens, detector and cooling arrangements mounted on part deployable from aircraft fuselage |
| JP2003042943A (en) * | 2001-08-01 | 2003-02-13 | Japan Atom Energy Res Inst | Spectrometry for high-speed signal |
| US20050073683A1 (en) * | 2001-10-25 | 2005-04-07 | The Regents Of The University Of California | Real-time detection method and system for identifying individual aerosol particles |
| CN2508243Y (en) * | 2001-11-16 | 2002-08-28 | 中国科学院安徽光学精密机械研究所 | Long-range differential absorption spectrum gas pollution monitor |
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