CN106979911A - The method that PM 2.5 and PM 10 is estimated is carried out using satellite multispectral image data - Google Patents
The method that PM 2.5 and PM 10 is estimated is carried out using satellite multispectral image data Download PDFInfo
- Publication number
- CN106979911A CN106979911A CN201710130462.9A CN201710130462A CN106979911A CN 106979911 A CN106979911 A CN 106979911A CN 201710130462 A CN201710130462 A CN 201710130462A CN 106979911 A CN106979911 A CN 106979911A
- Authority
- CN
- China
- Prior art keywords
- satellite
- optical depth
- dark pixel
- aerosol optical
- image data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 28
- 239000000443 aerosol Substances 0.000 claims abstract description 47
- 230000003287 optical effect Effects 0.000 claims abstract description 46
- 230000005855 radiation Effects 0.000 claims abstract description 18
- 238000012544 monitoring process Methods 0.000 claims abstract description 11
- 238000012937 correction Methods 0.000 claims abstract description 10
- 241001269238 Data Species 0.000 claims abstract description 8
- 238000012216 screening Methods 0.000 claims abstract description 4
- 238000012952 Resampling Methods 0.000 claims description 11
- 238000002310 reflectometry Methods 0.000 claims description 11
- 238000001228 spectrum Methods 0.000 claims description 6
- 238000005070 sampling Methods 0.000 claims description 5
- 230000000694 effects Effects 0.000 claims description 3
- 230000008569 process Effects 0.000 claims description 3
- 239000004576 sand Substances 0.000 claims description 3
- 238000002834 transmittance Methods 0.000 claims description 3
- 230000007613 environmental effect Effects 0.000 abstract description 6
- 238000005516 engineering process Methods 0.000 abstract description 5
- 238000013441 quality evaluation Methods 0.000 abstract description 4
- 238000011156 evaluation Methods 0.000 abstract description 3
- 238000011160 research Methods 0.000 description 4
- 239000003292 glue Substances 0.000 description 3
- 239000005427 atmospheric aerosol Substances 0.000 description 2
- 230000008901 benefit Effects 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 239000003595 mist Substances 0.000 description 2
- 238000010606 normalization Methods 0.000 description 2
- 239000002245 particle Substances 0.000 description 2
- 238000003915 air pollution Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000001427 coherent effect Effects 0.000 description 1
- 230000005494 condensation Effects 0.000 description 1
- 238000009833 condensation Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000004069 differentiation Effects 0.000 description 1
- 239000006185 dispersion Substances 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 239000007788 liquid Substances 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000003595 spectral effect Effects 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
- G01N15/06—Investigating concentration of particle suspensions
Landscapes
- Chemical & Material Sciences (AREA)
- Dispersion Chemistry (AREA)
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Image Processing (AREA)
Abstract
The present invention discloses a kind of method that PM 2.5 and PM 10 estimations are carried out using satellite multispectral image data, including step：The geometric correction of satellite image, the radiation correcting of satellite image, the dark pixel screening of pretreatment of remotely-sensed data and angle information are calculated, estimation aerosol optical depth, estimation PM 2.5 and PM 10.The many source datas of contrast, the relation set up between the aerosol optical depth and surface air observation index of each dark pixel, estimate PM 2.5 and PM 10.By the evaluation method that provides of the present invention, can realize it is a wide range of, stably, the PM 2.5 and PM 10 that becomes more meticulous estimate, meet application demand of the satellite remote sensing technology in terms of a wide range of environmental monitoring especially Air Quality Evaluation.
Description
Technical field
The present invention relates to Surveying Science and Technology field, it is more particularly related to a kind of multispectral using satellite
Image data carries out the method that PM 2.5 and PM 10 is estimated.
Background technology
In recent years, the extensive long-time air pollution episode taken place frequently, has had a strong impact on the normal production and living of people, area
The pollution form of domain property is gradually highlighted, and especially in the more flourishing and densely populated large size city of economy, Regional Atmospheric Pollution is
Through the focus as research.Environmental monitoring station's Monitoring Data generally includes SO2, NO2, PM2.5, PM10 etc., wherein inhalable
The detection of grain thing, current PM2.5 and PM10 are the focuses of concern, because its diameter is respectively smaller than 2.5um and 10um, not only to people
Body causes direct harm, and other dusty gas molecules can be also adsorbed in an atmosphere, promotes the generation of chemical reaction, causes other dirty
Contaminate the generation of gas.The increase of aerosol particle quantity is one of principal element of haze weather, for aerosol optical depth
Research contribute to analyze gray haze information.Aerosol is that dispersion formed by solid-state or liquid particles is added in gas medium
System, is to influence one of determinant of Surface Energy Budget balance, refers generally to the Atmospheric particulates between 1nm~100um, mainly
Solar radiation is influenceed by way of scattering and absorbing, will also become the nuclei of condensation influences the formation and distribution of cloud and mist, so gas is molten
The research of glue has great significance to atmosphere pollution.
Data, cost mainly are obtained by the mode at ground monitoring station to PM in air 2.5 and PM 10 detections at present
Higher and efficiency is not very high, and aerosol is stronger with the variability of the time and space, although heliograph and laser measurement
Precision is very high, but is due to surface-based observing station limited amount, and monitoring is still an an open question on a large scale.From 2011
Year state-sponsored high score satellite special construction project, number Seeds of First Post-flight of the high score launched and come into operation at present four
Wide cut high-resolution multi-spectral camera, with very good room and time resolution ratio, can combine other atmospheric environment numbers
According to this and Environmental Quality Evalution standard etc., highly important meaning is played in terms of haze information monitoring.
The content of the invention
For weak point present in above-mentioned technology, the present invention provides one kind and utilizes satellite multispectral image data to carry out
The method that PM 2.5 and PM 10 are estimated, can realize it is a wide range of, stably, the PM 2.5 and PM 10 that becomes more meticulous estimate that satisfaction is defended
Application demand of the star remote sensing technology in terms of a wide range of environmental monitoring especially Air Quality Evaluation.
In order to realize that, according to object of the present invention and further advantage, the present invention is achieved through the following technical solutions：
The present invention provides a kind of method that PM 2.5 and PM 10 estimations are carried out using satellite multispectral image data, including
Following steps：
The geometric correction of satellite image：Satellite image is carried out using ground control point and supporting Law of DEM Data
Geometric correction, be satellite image carry out geocoding；
The radiation correcting of satellite image：The absolute radiometric calibration and multidate of satellite image are carried out using radiation treatment parameter
Between relative detector calibration；And the apparent reflectance value on ground is calculated according to the result of radiation correcting；
The pretreatment of remotely-sensed data：The resolution ratio of satellite image is selected, the apparent reflection is directed to according to the resolution ratio
Remotely-sensed data expressed by rate value carries out the resampling of regularization, obtains the remote sensing image data of uniform scaling；
Dark pixel screening and angle information are calculated：The remote sensing image data obtained according to resampling, calculates normalization vegetation
Index simultaneously screens dark pixel target in normalized differential vegetation index, calculates the upper corresponding observation angle letter in the dark pixel point position of sampling
Breath；
Estimate aerosol optical depth：According to remotely-sensed data multi light spectrum hands scope, geometric orientation information and the sight
Measuring angle information, builds the look-up table of aerosol optical depth；The information of each dark pixel is matched with the look-up table
The corresponding aerosol optical depth of closest item is obtained for corresponding dark pixel assignment；
Estimate PM 2.5 and PM 10：The many source datas of contrast, set up the aerosol optical depth of each dark pixel with it is near the ground
Relation between air observation index, estimates PM 2.5 and PM 10.
Preferably, the information of each dark pixel and the look-up table match to obtain the corresponding gas of closest item molten
Glue optical thickness is the process of corresponding dark pixel assignment, and the method marked using dark pixel is comprised the following steps：
Assuming that atmospheric level is homogeneous, the apparent reflectance for the upper atmosphere that satellite reception is arrived is ρTOA, then,
Wherein, ρ0The path radiation term atmospheric reflectance rate of air is represented, T represents atmospheric transmittance, ρsRepresent earth surface reflection
Rate, S represents the hemispherical reflectance of lower atmosphere layer, ρ0, T and S illustrate atmospheric condition；
μs=cos θs, μv=cos θv, θsAnd θvRepresent that the sun is preordained angle and satellite zenith angle respectively；
According to 6S models, aerosol optical depth and ρ are calculated under the conditions of certain angle0, relation between T and S parameter
And set up look-up table；
It is assumed that Reflectivity for Growing Season, obtains aerosol optical depth information；
When ground surface reflectance is small to when can ignore its effect, the observation that satellite remote-sensing image is provided is only included
The optical information of atmospheric aerosol, has direct for dark pixel, between the Reflectivity for Growing Season of red blue wave band and 2.1um wave band
Proportionate relationship is：
ρred=k1ρblue=k2ρir； (2)
With reference to above-mentioned (1), (2) two formula and multispectral satellite remote sensing date, Simultaneous Equations solve aerosol light
The unknown-values such as the Reflectivity for Growing Season of thickness and red blue wave band are learned, then are obtained：
Preferably, PM 2.5 and PM 10 are estimated, is comprised the following steps：
By the position temperature derived function on the same day, atmospheric boundary layer height is obtained；
In obtained atmospheric boundary height is calculated, according to the aerosol optical depth and corresponding many sources ground observation value
Local matching comparison is carried out, model is selected as comparison data from coefficient correlation model；
Using the data set and its corresponding PM 2.5 and the numerical value of PM 10 that the match is successful, it is fitted and is closed from quadratic polynomial
It is model and calculates its parameter；
According to the aerosol optical depth value and the quadratic polynomial fit correlation model, calculating obtains remaining region
PM 2.5 and PM 10 estimated value.
Preferably, the multi light spectrum hands scope includes：Red, green, blue, near-infrared.
Preferably, the observation angle information includes solar zenith angle, moonscope zenith angle and relative bearing.
Preferably, many source datas include the Monitoring Data of MODIS and ground control point.
The present invention at least includes following beneficial effect：
What the present invention was provided carries out the method that PM 2.5 and PM 10 is estimated, this method using satellite multispectral image data
Incorporate satellite multispectral image data radiant correction, apparent reflectance calculating, dark pixel scaling method, aerosol optical depth
Calculate and rational polynominal model of fit scheduling algorithm, can carry out it is a wide range of, stably, become more meticulous, continuously and stably haze
Key index is monitored, and calculating speed is very fast, is mainly used in the application of satellitic remote sensing such as Air Quality Evaluation, environmental evaluation field.
Further advantage, target and the feature of the present invention embodies part by following explanation, and part will also be by this
The research and practice of invention and be understood by the person skilled in the art.
Brief description of the drawings
Fig. 1 shows for the method for the present invention for carrying out PM 2.5 and PM 10 estimations using satellite multispectral image data
It is intended to.
Embodiment
The present invention is described in further detail below in conjunction with the accompanying drawings, to make those skilled in the art with reference to specification text
Word can be implemented according to this.
It should be appreciated that such as " having ", "comprising" and " comprising " term used herein are not precluded from one or many
The presence or addition of individual other elements or its combination.
As shown in figure 1, present invention offer is a kind of to carry out what PM 2.5 and PM 10 was estimated using satellite multispectral image data
Method, it comprises the following steps：
S10, the geometric correction of satellite image：Satellite is carried out using ground control point and supporting Law of DEM Data
The geometric correction of image, is that satellite image carries out geocoding；
S20, the radiation correcting of satellite image：The absolute radiometric calibration of satellite image is carried out using radiation treatment parameter and many
Relative detector calibration between phase；And the apparent reflectance value on ground is calculated according to the result of radiation correcting；
S30, the pretreatment of remotely-sensed data：The resolution ratio of satellite image is selected, is taken according to resolution ratio for apparent reflectance
The expressed remotely-sensed data of value carries out the resampling of regularization, obtains the remote sensing image data of uniform scaling；
S40, dark pixel screening and angle information are calculated：The remote sensing image data obtained according to resampling, calculates normalization
Vegetation index simultaneously screens dark pixel target in normalized differential vegetation index, calculates the dark upper corresponding observation angle in pixel point position of sampling
Information；
S50, estimates aerosol optical depth：According to remotely-sensed data multi light spectrum hands scope, geometric orientation information and sight
Measuring angle information, builds the look-up table of aerosol optical depth；The information of each dark pixel is matched with look-up table and obtains most adjacent
The corresponding aerosol optical depth of nearly item is corresponding dark pixel assignment；
S60, estimates PM 2.5 and PM 10：Many source datas are contrasted, each secretly aerosol optical depth of pixel are set up and near
Relation between ground air observation index, estimates PM 2.5 and PM 10.
In above-mentioned embodiment, the present invention is carried out using the multispectral image data of number satellite wide cut camera imaging of high score
PM 2.5 and PM 10 are estimated.
In step S10, the preferred ellipsoids of WGS 84 of Geographic Reference ellipsoid of geometric correction, the preferred longitude and latitude of geographic coordinate system is sat
Mark system.The multi light spectrum hands of satellite image is ranged preferably from including red, green, blue and near-infrared.
In step S20, the absolute of number satellite wide cut multispectral image of high score is carried out present invention preferably employs ENVI softwares
Relative detector calibration between radiation calibration and multi_temporal images data, and downloaded on China Satecom's resource application center website
Corresponding biasing and gain parameter, with reference to the information such as the sun altitude in Image-aided xml document and year day of year, pass through shadow
The DN value calculating of picture obtains apparent spoke brightness, so as to further calculate apparent reflectance value.
During step S30 resampling, number wide cut image data design resolution of high score is 16m, in atmospheric remote sensing
Field, resolution ratio is too high, may make inverting by the image of hypsography, brings larger noise, and influence aerosol optical is thick
Spend inversion result.It is 320m by image 20*20 resamplings；Because follow-up calculate needs to calculate angle according to the position of the dark pixel of correspondence
Information is spent, and after resampling, the coordinate of dark pixel can be varied from, it is necessary to the dark pixel after resampling is corresponded in artwork,
Original angle information is obtained, herein, the dark pixel position after resampling takes the position of the former image pixel of center correspondence.
In step S40, the calculating of normalized differential vegetation index can partially remove landform, cloud shade and part atmospheric conditions phase
The influence of the radiation parameter of pass etc., and number wide cut camera of high score lacks 2.1um wave band datas, therefore, present invention preferably employs
NDVI carries out the differentiation of dark pixel.Cloud, water and snow on remote sensing image etc. red spectral band luminance factor near infrared band
Reflection it is strong, the normalized differential vegetation index of the part is negative value, result of calculation is not influenceed in follow-up calculating, it is possible thereby to save
Omit the process step of cloud and mist part.Preferably, calculating the dark upper corresponding observation angle information in pixel point position of sampling is included too
Positive zenith angle, moonscope zenith angle and relative bearing.There is the region normalizing of vegetative coverage on the remote sensing image of the present invention
It is on the occasion of preferably, selection normalized differential vegetation index recognizes dark pixel for 0.45 threshold value to change vegetation index, it is ensured that
There are enough dark pixels to carry out the inverting of aerosol optical depth in image, while it is excessive to avoid dark pixel number so that meter
Calculate speed to decline, data redundancy.
In step S50, the information of each dark pixel and look-up table match obtain the corresponding aerosol of closest item
Optical thickness is the process of corresponding dark pixel assignment, and the method marked using dark pixel is comprised the following steps：
S51, if atmospheric level is homogeneous, the apparent reflectance of satellite reception to upper atmosphere is ρTOA, then,
Wherein, ρ0The path radiation term atmospheric reflectance rate of air is represented, T represents atmospheric transmittance, ρsRepresent earth surface reflection
Rate, S represents the hemispherical reflectance of lower atmosphere layer, ρ0, T and S illustrate atmospheric condition；
μs=cos θs, μv=cos θv, θsAnd θvRepresent that the sun is preordained angle and satellite zenith angle respectively；
S52, according to 6S models, calculates aerosol optical depth and ρ under the conditions of certain angle0, between T and S parameter
Relation simultaneously sets up look-up table；
S53, it is assumed that Reflectivity for Growing Season, obtains aerosol optical depth information；
S54, when ground surface reflectance is small to when can ignore its effect, the observation that satellite remote-sensing image is provided is only
Optical information including atmospheric aerosol, has straight for dark pixel, between the Reflectivity for Growing Season of red blue wave band and 2.1um wave band
The proportionate relationship connect is：
ρred=k1ρblue=k2ρir； (2)
S55, with reference to above-mentioned (1), (2) two formula and multispectral satellite remote sensing date, Simultaneous Equations solve gas molten
The unknown-values such as the Reflectivity for Growing Season of glue optical thickness and red blue wave band, then obtain：
In the embodiment, look-up table is built using ripe 6S radiative transfer models.By setting sun altitude
The angularly parameter such as the scope of information and interval, aerosol model, image time, can generate under different condition Atmospheric Characteristics and
Corresponding relation between ground parameter.The relative parameters setting of look-up table is：Atmospheric model selection is middle latitude summer, aerosol mould
Formula is set to continent type, basis of time image correspondence set of time.Look-up table items be respectively solar zenith angle, satellite zenith angle,
Relative bearing, AOD, ρ 0, T, S, the scope of first three items are determined that Section 4 is aerosol optical depth by image corresponding data,
Value between 0~2, can generally reduce the scope according to the image of determination, reduce the redundancy of look-up table data and improve precision
And efficiency, rear three item data is to calculate to obtain by 6S models.For the dark pixel screened, according to its sun altitude,
Observed altitude angle and relative bearing angle information, are matched on look-up table, and the principle of matching is preferably minimum distance method, by
Not enough in the constraints of matching, the item of the obtained distance matched in a lookup table minimum has a lot, and these have correspondence
Aerosol optical depth value, ρ 0, T and S, carry it into following equations group：
According to above-mentioned equation group, the Reflectivity for Growing Season of red blue wave band is tried to achieve respectively, then calculates red blue wave band earth surface reflection
The ratio of rate and 2 difference of two squares, with minimum 4th condition of the difference of two squares, matching obtains the corresponding unique gas of each dark pixel point
Colloidal sol optical thickness values.
In step S60, many source datas include the Monitoring Data of MODIS products and ground control point.Estimate the Hes of PM 2.5
PM 10, comprises the following steps：
S61, by the position temperature derived function on the same day, obtains atmospheric boundary layer height；
S62, in obtained atmospheric boundary height is calculated, according to aerosol optical depth and corresponding many sources ground observation value
Local matching comparison is carried out, model is selected as comparison data from coefficient correlation model；
S63, using the data set and its corresponding PM 2.5 and the numerical value of PM 10 that the match is successful, is intended from quadratic polynomial
Close relational model and calculate its parameter；
S64, according to aerosol optical depth value and quadratic polynomial fit correlation model, calculates the PM for obtaining remaining region
2.5 and PM 10 estimated value.
The present invention provides a kind of method that PM 2.5 and PM 10 estimations are carried out using satellite multispectral image data, passes through
The satellite multispectral image of the region-of-interest of acquisition (preferably comprises four wave bands：Red, green, blue and near-infrared) and it is corresponding several
What and radiation parameter, according to the relevant parameter of image, set up the search relationship table of remote sensing image and aerosol optical depth, and pin
The processing of coherent radiation correction is carried out to image data, apparent reflectance is calculated, then image is differentiated by vegetation-cover index
Dark pixel, inverting obtains its corresponding aerosol optical depth, according to aerosol optical depth and ground monitoring Data Matching pair
The result of ratio, the estimation relation between aerosol optical depth and the index such as PM 2.5 and PM 10 is fitted using quadratic polynomial,
And then the haze key index value of satellite multispectral image inverting is utilized, obtain PM 2.5 and PM 10 estimated value.The party
Method incorporates satellite multispectral image data radiant correction, apparent reflectance calculating, dark pixel scaling method, aerosol optical thickness
Degree is calculated and rational polynominal model of fit scheduling algorithm, is carried out using the data of the multispectral image of a number wide cut camera of high score
Experiment, as a result shows that the inversion accuracy of dark pixel part in image is higher；Simultaneously because satellite image scope is big, observation time connects
It is continuous stable, relative to existing ground investigation sampling means, range and efficiency that PM 2.5 and PM 10 is monitored are significantly improved, i.e.,
Can carry out it is a wide range of, stably, become more meticulous, continuously and stably haze key index monitor, calculating speed is very fast, can be applied to
The application of satellitic remote sensing such as Air Quality Evaluation, environmental evaluation field.
Although embodiment of the present invention is disclosed as above, it is not restricted in specification and embodiment listed
With.It can be applied to various suitable the field of the invention completely.Can be easily for those skilled in the art
Realize other modification.Therefore under the universal limited without departing substantially from claim and equivalency range, the present invention is not limited
In specific details and shown here as the legend with description.
Claims (6)
1. a kind of carry out the method that PM 2.5 and PM 10 are estimated using satellite multispectral image data, it is characterised in that including with
Lower step：
The geometric correction of satellite image：The several of satellite image are carried out using ground control point and supporting Law of DEM Data
What is corrected, and is that satellite image carries out geocoding；
The radiation correcting of satellite image：Between absolute radiometric calibration and multidate that satellite image is carried out using radiation treatment parameter
Relative detector calibration；And the apparent reflectance value on ground is calculated according to the result of radiation correcting；
The pretreatment of remotely-sensed data：The resolution ratio of satellite image is selected, is taken according to the resolution ratio for the apparent reflectance
The expressed remotely-sensed data of value carries out the resampling of regularization, obtains the remote sensing image data of uniform scaling；
Dark pixel screening and angle information are calculated：The remote sensing image data obtained according to resampling, calculates normalized differential vegetation index
And dark pixel target is screened in normalized differential vegetation index, calculate the dark upper corresponding observation angle information in pixel point position of sampling；
Estimate aerosol optical depth：According to remotely-sensed data multi light spectrum hands scope, geometric orientation information and the view angle
Information is spent, the look-up table of aerosol optical depth is built；The information of each dark pixel is matched with the look-up table
The corresponding aerosol optical depth of closest item is corresponding dark pixel assignment；
Estimate PM 2.5 and PM 10：The many source datas of contrast, set up the aerosol optical depth and surface air of each dark pixel
Relation between observation index, estimates PM 2.5 and PM 10.
2. carrying out the method that PM 2.5 and PM 10 is estimated using satellite multispectral image data as described in claim 1, it is special
Levy and be, the information of each dark pixel and the look-up table match obtain the corresponding aerosol optical depth of closest item
For the process of corresponding dark pixel assignment, the method marked using dark pixel is comprised the following steps：
Assuming that atmospheric level is homogeneous, the apparent reflectance for the upper atmosphere that satellite reception is arrived is ρTOA, then,
Wherein, ρ0The path radiation term atmospheric reflectance rate of air is represented, T represents atmospheric transmittance, ρsRepresent Reflectivity for Growing Season, S tables
Show the hemispherical reflectance of lower atmosphere layer, ρ0, T and S illustrate atmospheric condition；
μs=cos θs, μv=cos θv, θsAnd θvRepresent that the sun is preordained angle and satellite zenith angle respectively；
According to 6S models, aerosol optical depth and ρ are calculated under the conditions of certain angle0, relation between T and S parameter and foundation
Look-up table；
It is assumed that Reflectivity for Growing Season, obtains aerosol optical depth information；
When ground surface reflectance is small to when can ignore its effect, the observation that satellite remote-sensing image is provided only includes air
The optical information of aerosol, for dark pixel, has direct ratio between the Reflectivity for Growing Season of red blue wave band and 2.1um wave band
Relation is：
ρred=k1ρblue=k2ρir； (2)
With reference to above-mentioned (1), (2) two formula and multispectral satellite remote sensing date, Simultaneous Equations,
The unknown-values such as the Reflectivity for Growing Season of aerosol optical depth and red blue wave band are solved, then are obtained：
3. carrying out the method that PM 2.5 and PM 10 is estimated using satellite multispectral image data as described in claim 1, it is special
Levy and be, estimate PM 2.5 and PM 10, comprise the following steps：
By the position temperature derived function on the same day, atmospheric boundary layer height is obtained；
In obtained atmospheric boundary height is calculated, carried out according to the aerosol optical depth with corresponding many sources ground observation value
Local matching is compared, and model is selected as comparison data from coefficient correlation model；
Using the data set and its corresponding PM 2.5 and the numerical value of PM 10 that the match is successful, from quadratic polynomial fit correlation mould
Type simultaneously calculates its parameter；
According to the aerosol optical depth value and the quadratic polynomial fit correlation model, the PM for obtaining remaining region is calculated
2.5 and PM 10 estimated value.
4. being estimated using satellite multispectral image data progress PM 2.5 and PM 10 as any one of claim 1-3
Method, it is characterised in that the multi light spectrum hands scope includes：Red, green, blue, near-infrared.
5. being estimated using satellite multispectral image data progress PM 2.5 and PM 10 as any one of claim 1-3
Method, it is characterised in that the observation angle information include solar zenith angle, moonscope zenith angle and relative bearing
Angle.
6. being estimated using satellite multispectral image data progress PM 2.5 and PM 10 as any one of claim 1-3
Method, it is characterised in that many source datas include the Monitoring Data of MODIS and ground control point.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710130462.9A CN106979911A (en) | 2017-03-07 | 2017-03-07 | The method that PM 2.5 and PM 10 is estimated is carried out using satellite multispectral image data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710130462.9A CN106979911A (en) | 2017-03-07 | 2017-03-07 | The method that PM 2.5 and PM 10 is estimated is carried out using satellite multispectral image data |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN106979911A true CN106979911A (en) | 2017-07-25 |
Family
ID=59338883
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710130462.9A Pending CN106979911A (en) | 2017-03-07 | 2017-03-07 | The method that PM 2.5 and PM 10 is estimated is carried out using satellite multispectral image data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106979911A (en) |
Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107972887A (en) * | 2017-11-22 | 2018-05-01 | 北京航空航天大学 | The monitoring method and device of PM2.5 |
| CN108170927A (en) * | 2017-12-22 | 2018-06-15 | 深圳先进技术研究院 | A kind of PM2.5 remote sensing inversion methods based on MODIS |
| CN108955770A (en) * | 2018-07-25 | 2018-12-07 | 成都天地量子科技有限公司 | A kind of colcanism monitoring method based on multispectral satellite image |
| CN109030301A (en) * | 2018-06-05 | 2018-12-18 | 中南林业科技大学 | Aerosol optical depth inversion method based on remotely-sensed data |
| CN109900361A (en) * | 2017-12-08 | 2019-06-18 | 核工业北京地质研究院 | A method of suitable for Airborne Hyperspectral image Atmospheric radiation correction |
| CN110108609A (en) * | 2019-05-07 | 2019-08-09 | 国网湖南省电力有限公司 | A kind of PM2.5 concentration value distribution situation acquisition methods and system based on satellite multichannel |
| CN110411919A (en) * | 2019-08-02 | 2019-11-05 | 中国科学院遥感与数字地球研究所 | A kind of PM2.5 concentration remote-sensing evaluation method based on the multispectral technology of satellite |
| CN110909309A (en) * | 2019-11-21 | 2020-03-24 | 中国科学院遥感与数字地球研究所 | Method for acquiring hourly high-resolution PM2.5 data |
| CN111209533A (en) * | 2019-11-28 | 2020-05-29 | 香港理工大学深圳研究院 | Road surface fine particulate matter inversion method and device, computing equipment and storage medium |
| CN112179850A (en) * | 2020-11-09 | 2021-01-05 | 南京信息工程大学 | GF-4 AOD product high time resolution inspection based on ground actual measurement |
| CN113361309A (en) * | 2020-03-18 | 2021-09-07 | 山东交通学院 | Urban multi-haze pollution parameter monitoring method based on medium-high resolution remote sensing image |
| CN113376327A (en) * | 2021-07-08 | 2021-09-10 | 海南绿能环境工程有限公司 | Environmental monitoring information management method and system based on big data |
| CN113643244A (en) * | 2021-07-23 | 2021-11-12 | 中国资源卫星应用中心 | Rapid detection method for flare of water body of optical remote sensing satellite image |
| CN117555047A (en) * | 2023-12-07 | 2024-02-13 | 中国人民解放军国防科技大学 | Power equipment meteorological monitoring and early warning method based on artificial intelligence |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106407656A (en) * | 2016-08-29 | 2017-02-15 | 中国科学院遥感与数字地球研究所 | Retrieval method for aerosol optical thickness based on high resolution satellite image data |
-
2017
- 2017-03-07 CN CN201710130462.9A patent/CN106979911A/en active Pending
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106407656A (en) * | 2016-08-29 | 2017-02-15 | 中国科学院遥感与数字地球研究所 | Retrieval method for aerosol optical thickness based on high resolution satellite image data |
Non-Patent Citations (1)
| Title |
|---|
| 安晨霞: "HJ_1A_B星CCD数据大气遥感定量反演方法与应用", 《中国优秀硕士学位论文全文数据库—工程科技Ⅰ辑》 * |
Cited By (22)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107972887A (en) * | 2017-11-22 | 2018-05-01 | 北京航空航天大学 | The monitoring method and device of PM2.5 |
| CN107972887B (en) * | 2017-11-22 | 2019-11-08 | 北京航空航天大学 | The monitoring method and device of PM2.5 based on Cubesat satellite |
| CN109900361B (en) * | 2017-12-08 | 2020-11-20 | 核工业北京地质研究院 | Atmospheric radiation correction method suitable for aviation hyperspectral image |
| CN109900361A (en) * | 2017-12-08 | 2019-06-18 | 核工业北京地质研究院 | A method of suitable for Airborne Hyperspectral image Atmospheric radiation correction |
| CN108170927A (en) * | 2017-12-22 | 2018-06-15 | 深圳先进技术研究院 | A kind of PM2.5 remote sensing inversion methods based on MODIS |
| CN108170927B (en) * | 2017-12-22 | 2021-06-18 | 深圳先进技术研究院 | MODIS-based PM2.5 remote sensing inversion method |
| CN109030301A (en) * | 2018-06-05 | 2018-12-18 | 中南林业科技大学 | Aerosol optical depth inversion method based on remotely-sensed data |
| CN108955770A (en) * | 2018-07-25 | 2018-12-07 | 成都天地量子科技有限公司 | A kind of colcanism monitoring method based on multispectral satellite image |
| CN110108609A (en) * | 2019-05-07 | 2019-08-09 | 国网湖南省电力有限公司 | A kind of PM2.5 concentration value distribution situation acquisition methods and system based on satellite multichannel |
| CN110108609B (en) * | 2019-05-07 | 2021-11-02 | 国网湖南省电力有限公司 | Method and system for acquiring PM2.5 concentration value distribution situation based on satellite multichannel |
| CN110411919A (en) * | 2019-08-02 | 2019-11-05 | 中国科学院遥感与数字地球研究所 | A kind of PM2.5 concentration remote-sensing evaluation method based on the multispectral technology of satellite |
| CN110909309A (en) * | 2019-11-21 | 2020-03-24 | 中国科学院遥感与数字地球研究所 | Method for acquiring hourly high-resolution PM2.5 data |
| CN111209533A (en) * | 2019-11-28 | 2020-05-29 | 香港理工大学深圳研究院 | Road surface fine particulate matter inversion method and device, computing equipment and storage medium |
| CN111209533B (en) * | 2019-11-28 | 2021-08-10 | 香港理工大学深圳研究院 | Road surface fine particulate matter inversion method and device, computing equipment and storage medium |
| CN113361309B (en) * | 2020-03-18 | 2022-05-13 | 山东交通学院 | Urban area multi-haze pollution parameter monitoring method based on medium-high resolution remote sensing image |
| CN113361309A (en) * | 2020-03-18 | 2021-09-07 | 山东交通学院 | Urban multi-haze pollution parameter monitoring method based on medium-high resolution remote sensing image |
| CN112179850A (en) * | 2020-11-09 | 2021-01-05 | 南京信息工程大学 | GF-4 AOD product high time resolution inspection based on ground actual measurement |
| CN113376327A (en) * | 2021-07-08 | 2021-09-10 | 海南绿能环境工程有限公司 | Environmental monitoring information management method and system based on big data |
| CN113376327B (en) * | 2021-07-08 | 2023-01-17 | 海南海笙信息科技有限公司 | Environmental monitoring information management method and system based on big data |
| CN113643244A (en) * | 2021-07-23 | 2021-11-12 | 中国资源卫星应用中心 | Rapid detection method for flare of water body of optical remote sensing satellite image |
| CN113643244B (en) * | 2021-07-23 | 2024-05-21 | 中国资源卫星应用中心 | Quick detection method for flare of optical remote sensing satellite image water body |
| CN117555047A (en) * | 2023-12-07 | 2024-02-13 | 中国人民解放军国防科技大学 | Power equipment meteorological monitoring and early warning method based on artificial intelligence |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106979911A (en) | The method that PM 2.5 and PM 10 is estimated is carried out using satellite multispectral image data | |
| Vermote et al. | Preliminary analysis of the performance of the Landsat 8/OLI land surface reflectance product | |
| Xu et al. | Detecting layer height of smoke aerosols over vegetated land and water surfaces via oxygen absorption bands: hourly results from EPIC/DSCOVR in deep space | |
| CN112051222A (en) | River and lake water quality monitoring method based on high-resolution satellite image | |
| Hakvoort et al. | Towards airborne remote sensing of water quality in The Netherlands—validation and error analysis | |
| She et al. | Joint retrieval of aerosol optical depth and surface reflectance over land using geostationary satellite data | |
| Wong et al. | An operational MODIS aerosol retrieval algorithm at high spatial resolution, and its application over a complex urban region | |
| CN103018736A (en) | Satellite-borne remote sensor radiation calibration method based on atmospheric parameter remote sensing retrieval | |
| Bilal et al. | Validation of MODIS and VIIRS derived aerosol optical depth over complex coastal waters | |
| Cheng et al. | Simultaneous retrieval of aerosol optical properties over the Pearl River Delta, China using multi-angular, multi-spectral, and polarized measurements | |
| CN114819150B (en) | Remote sensing inversion method for primary productivity of polar region ocean in winter | |
| CN106778516A (en) | A kind of method and device that surface temperature is determined using Chinese No. three satellite remote sensing dates of wind and cloud | |
| CN116519557B (en) | Aerosol optical thickness inversion method | |
| CN106680273B (en) | High-spatial-resolution satellite earth surface reflectivity inversion method | |
| Wei et al. | Enhanced aerosol estimations from Suomi-NPP VIIRS images over heterogeneous surfaces | |
| Brunsell et al. | Validating remotely sensed land surface fluxes in heterogeneous terrain with large aperture scintillometry | |
| CN101866385A (en) | Target parcel ground surface temperature simulation and optimization method | |
| Li et al. | An improved dark object method to retrieve 500 m-resolution AOT (Aerosol Optical Thickness) image from MODIS data: A case study in the Pearl River Delta area, China | |
| CN113324915A (en) | Urban complex earth surface reflectivity estimation method supporting high-resolution aerosol optical thickness inversion | |
| CN116380846A (en) | Atmospheric correction method for highly absorptive aerosols | |
| Xiao et al. | Spatial characteristics of the difference between MISR and MODIS aerosol optical depth retrievals over mainland Southeast Asia | |
| Li et al. | Performances of atmospheric correction processors for sentinel-2 MSI imagery over typical lakes across China | |
| CN111650128B (en) | High-resolution atmospheric aerosol inversion method based on surface reflectivity library | |
| Barrado-Izagirre et al. | Jupiter's polar clouds and waves from Cassini and HST images: 1993–2006 | |
| He et al. | Direct estimation of land surface albedo from simultaneous MISR data |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20170725 |
|
| RJ01 | Rejection of invention patent application after publication |