CN109632106A - A kind of Remote Sensing temperature angles of product effect correction method - Google Patents
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Abstract
A kind of Remote Sensing temperature angles of product effect correction method, comprising: the brightness temperature of 31,32 wave band of pixel is calculated using MOD021KM data；Obtain pixel atmosphere lower bound temperature Tair, the total vapour content CWV of atmosphere, sensor view zenith angle θ v；Obtain pixel sensor observed direction general Split window algorithms coefficient C, A1, A2, A3, B1, B2, B3；Determine the zenith emissivity (ε of pixel0)；Calculate the gradient (α) and slope aspect of pixelCalculate local angle of reflection (θ0)；Obtain average emitted rate of the pure pixel of earth's surface difference cover type between 65 ° of sensor observation angle ﹣ Dao 65 ° of ﹢Data set；It is poor with respect to the emissivity of zenith direction to obtain different view zenith anglesData set；Assuming that pixel is in expression formula of the observed direction with respect to the variation of zenith direction emissivity；Determine the emissivity expression formula in observed direction of pixel；Calculate surface temperature (Ts).The present invention combines existing research, data and method, provides a kind of pixel grade emissivity directionality model that universality is strong, can be used in MODIS temperature angles of product effect calibration.
Description
Technical field
The present invention relates to thermal infrared remote sensing Surface Temperature Retrieval fields, more particularly to one kind to be based on a variety of MODIS earth's surface temperature
The earth's surface direction emissivity of degree emissivity product determines method, and its application in correction MODIS temperature angles of product effect.
Background technique
Surface temperature is commonly used in the estimation models such as earth atmosphere interfacial energy revenue and expenditure and numerous ecologies, weather, the hydrology
Indispensable parameter.With the progress of mankind's science and technology, the raising of productivity, carbon in atmosphere discharge amount is greatly increased, and is exacerbated
Greenhouse effects, global warming, which becomes from a concept, can perceive the fact that obtain, and global warming causes the two poles of the earth glacier
Melt, sea level rise, and extreme climate takes place frequently.Surface temperature is human research's global warming rule, predicts global warming trend
Important evidence, result of study are to formulate carbon emission policy, reach the most important theories basis of international climate agreement, therefore precise measurement
Surface temperature is particularly significant.
The appearance of remote sensing technology becomes possibility so that obtaining the surface temperature in the whole world or regional scale, and common temperature is anti-
Algorithm requires the priori knowledge of earth's surface emissivity in addition to temperature emissivity separation algorithm, single-channel algorithm, Split window algorithms.Ground
The method that table emissivity determines has very much, for example, determining earth's surface emissivity (Valor E, Caselles according to NDVI
V.Mapping land surface emissivity from NDVI:application to European,African,
and South American areas[J].Remote Sensing of Environment,1996,57(3):167-
184.) emissivity (Becker F.Temperature-independent spectral, is determined according to TISI index
indices in thermal infrared bands[J].Remote Sensing of Environment,1990,32
(1): 17-33.), earth's surface emissivity (Kealy P S, Hook S J.Separating is determined using α remnants' method
temperature and emissivity in thermal infrared multispectral scanner data:
implications for recovering land surface temperatures[J].IEEE Transactions on
Geoscience&Remote Sensing,2002,31(6):1155-1164.).Earth's surface emissivity directionality and earth's surface it is strong different
The presence of matter increases the accurate difficulty for obtaining pixel grade emissivity.Intermediate resolution imaging spectral radiometer (MODIS:
Moderate resolution imaging pectroradiometer) 11_L2 series of temperatures product do not consider emissivity
Directionality, based on use based on classification emissivity static emissivity determine the method disadvantage weak there is also universality.And emit
The every variation 0.01 of rate, is 0.5K or more to the error that temperature retrieval generates.
In order to improve the precision of MODIS11_L2 temperature product, need to obtain the emissivity directionality on earth's surface grid cell size
Changing rule.Currently, establishing emissivity angular effect model mainly has pure empirical method, semiempirical kernel-driven model method and physics
Modelling.Pure empirical model is fitted the emissivity changing rule of earth's surface just like a cosine function is used, and shortcoming is ground
The strong heterogeneity of table makes the model have certain limitation (A.J.Land surface temperatures derived
from the advanced very high resolution radiometer and the along-track
scanning radiometer.II:Experimental results and validation of AVHRR
algorithms[J].Journal of Geophysical Research Atmospheres,1993,99(D6):13025-
13058.)；Semiempirical method is representative experience kernel-driven model, and Vinnikov etc. proposes each to different of surface temperature
Property indicated using emissivity core and sun core, but, model is obtained using the training of six SURFRAD station datas,
SURFRAD website represents limited ground mulching situation so that the model have certain limitation (Vinnikov K Y,
Yu Y,Goldberg M D,et al.Angular anisotropy of satellite observations of land
surface temperature[J].Geophysical Research Letters,2012,39(23):23802.)；Except this
Except there are also some geometric optical models and radiative transfer model, these models are advised for the radiation transmission of accurate simulation earth's surface
Rule, need accurately determine earth's surface numerous parameters, and most parameters establish a capital really it is very difficult, so these models generally exist
Earth's surface or laboratory selection representative sample carry out training pattern, and universality is also bad.
Summary of the invention
The technical problem to be solved by the present invention is to have the limitation in space for prior art correction temperature angular effect
Property and influence of the landform to heat radiation the problem of being not affected by attention, in conjunction with existing research, data and method are proposed a kind of general
The strong pixel grade emissivity directionality model of adaptive, and be applied in MODIS temperature angles of product effect calibration.
In order to solve the above technical problem, the present invention provides Remote Sensing temperature angles of product effect correction method, packet
It includes:
Step 1: calculating the brightness temperature (T31, T32) of 31,32 wave band of pixel MODIS；
Step 2: obtaining pixel atmosphere lower bound temperature (Tair), the total vapour content of atmosphere (CWV), sensor observe zenith
Angle (θ v)；
Step 3: using pixel atmosphere lower bound temperature (Tair), the total vapour content of atmosphere (CWV), sensor zenith observing
Angle (θ v) obtains pixel sensor observed direction general Split window algorithms coefficient C, A from Split window algorithms Coefficient Look-up Table1, A2, A3,
B1, B2, B3；
Step 4: determining the zenith emissivity (ε of pixel0)；
Step 5: calculating the gradient (α) and slope aspect of pixel
Step 6: calculating local angle of reflection (θ0)；
Step 7: obtaining 131 of the pure pixel of earth's surface difference cover type between 65 ° of sensor observation angle ﹣ Dao 65 ° of ﹢
The average emitted rate of each angle of observation angleData set；
Step 8: result in step 7 is all subtractedAcquire transmitting of the different view zenith angles with respect to zenith direction
Rate is poorData set；
Step 9: pixel is assumed in observed direction with respect to the expression formula of zenith direction emissivity variation are as follows:
V ε (θ)=a1θ+a2θ2+a3θ3+...+anθn
Determine the coefficient a in multinomial1, a2, a3... anAnd the value of n；
Step 10: determining the emissivity expression formula in observed direction of pixel；
Step 11: determining the emissivity of observed direction, in conjunction with brightness temperature, Split window algorithms coefficient calculates surface temperature
(Ts)。
In the above-mentioned methods, pixel is calculated using MOD021KM data and Planck function approximate formula in step 1
The brightness temperature (T31, T32) of 31,32 wave band of MODIS,
T31=1304.413871/ln (1+729.541636/b31)
T32=1196.978785/ln (1+474.684780/b32).
In the above-mentioned methods, in step 2, pixel atmosphere lower bound temperature (T is obtained using MOD07_L2 dataair), atmosphere
Total vapour content (CWV), and sensor zenith observing angle θ v is obtained from MOD021KM data.
In the above-mentioned methods, in step 4, pixel ten is calculated using MOD21A2 2001 to 2010 Nian Gongshi annual datas
Year history monthly average emissivity regard result as earth's surface zenith emissivity data set, is obtained according to pixel and determine pixel in month
Zenith emissivity (ε0)。
In the above-mentioned methods, in steps of 5, using aspect in NASA GLOBE 1KM dem data and ArcMap and
The gradient (α) and slope aspect of slope function calculating pixel
In the above-mentioned methods, in step 6, local angle of reflection is calculated using following formula
cosθ0=acos (cos α cos θ v+sin α sin θ v cos (φs- φ)),
Wherein, φ in formulas, θ v is sensor observed azimuth and view zenith angle respectively.
In the above-mentioned methods, in step 7, using 2006 to 2010 MODIS ground mulching categorical datas
MOD12Q1 and MODIS earth's surface emissivity data MOD11B1, ground mulching data rise scale by polymerization and are and emissivity data
Identical resolution ratio obtains 131 of the pure pixel of earth's surface difference cover type between 65 ° of sensor observation angle ﹣ Dao 65 ° of ﹢
The average emitted rate of each angle of observation angleData set.
In the above-mentioned methods, in step 9, according to the ground mulching type of pixel, using correspondingData set is quasi-
Close the coefficient a determined in multinomial1, a2, a3... an, the value of n is determined using leaving-one method.
In the above-mentioned methods, in step 10, in conjunction with step 4 result determine pixel the emissivity in observed direction table
Up to formula are as follows:
ε (θ)=ε (0)+V ε (θ)=ε (0)+a1θ+a2θ2+a3θ3+...+anθn。
In the above-mentioned methods, in a step 11, according to result θ in step 60Substitute into step 10 in emissivity expression formula from
And determine the emissivity ε (θ of observed direction0), in conjunction with brightness temperature, Split window algorithms coefficient calculates surface temperature using following formula
(Ts):
Remote Sensing temperature angles of product effect correction method of the invention combines existing research, data and method, mentions
A kind of pixel grade emissivity directionality model that universality is strong has been supplied, and can be applied to MODIS temperature angles of product effect
In correction.After capable of being effectively corrected by means of the present invention to angular effect, the measurement of surface temperature is improved
Precision.
Detailed description of the invention
Fig. 1 is the techniqueflow chart of Remote Sensing temperature angles of product effect correction method of the invention.
Fig. 2 is using MODIS021KM data, using the comparison diagram of method temperature angular effect correction front and back of the invention.
Fig. 3 is the coverage area of MOD12Q1 and MOD11B1 data in step 7.
Specific embodiment
According to an embodiment of the invention, the present invention provides a kind of Remote Sensing temperature angles of product effect correction method,
Its techniqueflow chart is as shown in Figure 1.Specifically, Remote Sensing temperature angles of product effect correction method of the invention, including with
Lower step:
Step 1: calculating the bright of pixel MODIS31,32 wave band using MOD021KM data and Planck function approximate formula
Temperature T31 and T32 are spent,
T31=1304.413871/ln (1+729.541636/b31)；
T32=1196.978785/ln (1+474.684780/b32)；(formula 1)
Step 2: obtaining pixel atmosphere lower bound temperature T using MOD07_L2 dataair, the total vapour content CWV of atmosphere；From
Sensor zenith observing angle θ v is obtained in MOD021KM data；
Step 3: using Tair, it is logical that CWV, θ v obtain the pixel sensor observed direction from Split window algorithms Coefficient Look-up Table
With Split window algorithms coefficient C, A1, A2, A3, B1, B2, B3；
Step 4: using MOD21A2 emissivity product, 2001-2010 Nian Gongshi annual data is selected by data quality control
Calculating 10 years history monthly average emissivity of the pixel are selected to be obtained using the result as earth's surface zenith emissivity data set according to pixel
It takes and determines its zenith emissivity ε month0；
Step 5: using aspect and slope function in NOAA GLOBE 1km digital elevation (DEM) data and ArcMap
Calculate the gradient α and slope aspect of the pixel
Step 6: calculating local angle of reflection θ using following formula0；
cosθ0=acos (cos α cos θ v+sin α sin θ v cos (φs-φ))；(formula 2)
φs, θ v is sensor observed azimuth and zenith angle respectively；
Step 7: using MODIS ground mulching categorical data MOD12Q1 (2006-2010) and MODIS earth's surface emissivity number
It is the coverage area of the MOD12Q1 and MOD11B1 data in the step, ground mulching number according to MOD11B1 (2006-2010), Fig. 3
Scale is risen as resolution ratio identical with emissivity data according to by polymerizeing, and obtains the pure pixel of earth's surface difference cover type in sensor
The average emitted rate of 131 each angles of observation angle between 65 ° of observation angle ﹣ to 65 ° of ﹢Data set；
Step 8: result in step 7 is all subtractedObtain emissivity of the different view zenith angles with respect to zenith direction
DifferenceData set；
Step 9: the pixel is assumed in observed direction with respect to the expression formula of zenith direction emissivity variation are as follows:
V ε (θ)=a1θ+a2θ2+a3θ3+...+anθn；(formula 3)
According to the ground mulching type of pixel, using correspondingData set is fitted the coefficient a determined in multinomial1,
a2, a3... an；In order to avoid overfitting, use leaving-one method (Leave-One-Out Cross Validation, LOO-CV)
Determine the value of n；
Step 10: the emissivity expression formula in observed direction of the pixel is determined in conjunction with the result of step 4 are as follows:
ε (θ)=ε (0)+V ε (θ)=ε (0)+a1θ+a2θ2+a3θ3+...+anθn；(formula 4)
Step 11: according to result θ in step 60Substitute into (formula 4) so that it is determined that the observed direction earth's surface emissivity ε (θ0),
In conjunction with the bright temperature in step 1, the Split window algorithms coefficient in step 3 calculates surface temperature Ts
The present invention have chosen 2010 16:45 on July 26, (when UTC) contain a width of four SURFRAD observation website
Image inverting temperature carrys out the validity of the method for inspection.Such as Fig. 2, wherein (a) be angular effect correction before MODIS11_L2 temperature
Degree, the temperature after (b) correcting.Existing conclusion proves that MODIS temperature is relatively low, relatively low especially in arid and semi-arid lands
It can reach 3-5K.In general, temperature is improved after angular effect correction, this illustrates temperature essence after angular effect correction
Degree is improved.From the point of view of from details, after angular effect correction, the details of earth's surface, which has shown, to be come out, the reality of this and surface temperature
Border distribution is consistent.
Temperature retrieval after angular effect elimination is as a result, pixel of the selection at SURFRAD website, uses SURDRAD
Uplink and downlink long-wave radiation calculates earth's surface true temperature at website, and examines the temperature after the elimination of MODIS angular effect, specifically
As a result see table 1:.
Table 1
Examine that temperature verifies from deviation (Bias) and root-mean-square error (RMSE) two indices as a result, at four websites
It has chosen 1555 samples to be used to verify, it is found that deviation (Bias) is reduced to -0.82K, root-mean-square error (RMSE) from -1.47K
It is reduced to 1.55K from 2.13K, this all reflects the validity of method.
Remote Sensing temperature angles of product effect correction method of the invention combines existing research, data and method, mentions
A kind of pixel grade emissivity directionality model that universality is strong has been supplied, and can be applied to MODIS temperature angles of product effect
In correction.After capable of being effectively corrected by means of the present invention to angular effect, the measurement of surface temperature is improved
Precision.
Above embodiments, only a specific embodiment of the invention, to illustrate technical solution of the present invention, rather than to it
Limitation, scope of protection of the present invention is not limited thereto, although the present invention is described in detail referring to the foregoing embodiments,
Those skilled in the art should understand that: anyone skilled in the art the invention discloses technology model
In enclosing, still it can modify to technical solution documented by previous embodiment or variation can be readily occurred in, or to it
Middle some technical characteristics are equivalently replaced；And these modifications, variation or replacement, do not make the essence of corresponding technical solution de-
Spirit and scope from technical solution of the embodiment of the present invention, should be covered by the protection scope of the present invention.Therefore, of the invention
Protection scope should be subject to the protection scope in claims.
Claims (10)
1. a kind of Remote Sensing temperature angles of product effect correction method characterized by comprising
Step 1: calculating the brightness temperature (T31, T32) of 31,32 wave band of pixel MODIS；
Step 2: obtaining the pixel atmosphere lower bound temperature (Tair), the total vapour content of atmosphere (CWV), sensor observe zenith
Angle (θ v)；
Step 3: using pixel atmosphere lower bound temperature (Tair), the total vapour content of atmosphere (CWV), sensor zenith observing angle (θ
V) the pixel sensor observed direction general Split window algorithms coefficient C, A are obtained from Split window algorithms Coefficient Look-up Table1, A2, A3,
B1, B2, B3；
Step 4: determining the zenith emissivity (ε of the pixel0)；
Step 5: calculating the gradient (α) and slope aspect of the pixel
Step 6: calculating local angle of reflection (θ0)；
Step 7: obtaining 131 observations of the pure pixel of earth's surface difference cover type between 65 ° of sensor observation angle ﹣ Dao 65 ° of ﹢
The average emitted rate of each angle of angleData set；
Step 8: result in step 7 is all subtractedIt is poor with respect to the emissivity of zenith direction to acquire different view zenith anglesData set；
Step 9: the pixel is assumed in observed direction with respect to the expression formula of zenith direction emissivity variation are as follows:
V ε (θ)=a1θ+a2θ2+a3θ3+...+anθn
It usesData set determines the coefficient a in multinomial1, a2, a3... anAnd the value of n；
Step 10: determining the emissivity expression formula in the observed direction of the pixel；
Step 11: determining the emissivity of the observed direction, in conjunction with brightness temperature, Split window algorithms coefficient calculates surface temperature (Ts)。
2. the method according to claim 1, wherein using MOD021KM data and Planck function in step 1
Number approximate formula calculates the brightness temperature (T31, T32) of 31,32 wave band of pixel MODIS,
T31=1304.413871/ln (1+729.541636/b31)
T32=1196.978785/ln (1+474.684780/b32).
3. the method according to claim 1, wherein in step 2, obtaining the picture using MOD07_L2 data
First atmosphere lower bound temperature (Tair), the total vapour content of atmosphere (CWV), and sensor zenith is obtained from MOD021KM data
View angle θ v.
4. the method according to claim 1, wherein in step 4, using MOD21A22001 to 2010 years
Totally ten annual datas calculate 10 years history monthly average emissivity of the pixel, using result as earth's surface zenith emissivity data set, root
Zenith emissivity (the ε for determining the pixel month is obtained according to the pixel0)。
5. the method according to claim 1, wherein in steps of 5, using NOAA GLOBE 1KM dem data
With the gradient (α) and slope aspect of pixel described in aspect and slope function calculating in ArcMap software
6. the method according to claim 1, wherein in step 6, calculating local angle of reflection using following formula
cosθ0=acos (cos α cos θ v+sin α sin θ v cos (φs- φ)),
Wherein, φ in formulas, θ v is sensor observed azimuth and view zenith angle respectively.
7. the method according to claim 1, wherein in step 7, using 2006 to 2010 MODIS
Ground mulching categorical data MOD12Q1 and MODIS earth's surface emissivity data MOD11B1, ground mulching data rise ruler by polymerization
Degree is resolution ratio identical with emissivity data, obtains the pure pixel of earth's surface difference cover type and arrives for 65 ° in sensor observation angle ﹣
The average emitted rate of 131 each angles of observation angle between 65 ° of ﹢Data set.
8. the method according to claim 1, wherein in step 9, according to the ground mulching class of the pixel
Type, using correspondingData set is fitted the coefficient a determined in multinomial1, a2, a3... an, determine n's using leaving-one method
Value.
9. the method according to claim 1, wherein in step 10, in conjunction with the ε of step 40As a result the picture is determined
The emissivity expression formula in the observed direction of member are as follows:
ε (θ)=ε (0)+V ε (θ)=ε (0)+a1θ+a2θ2+a3θ3+...+anθn。
10. the method according to claim 1, wherein in a step 11, according to result θ in step 60Substitute into step
So that it is determined that emissivity ε (the θ of the observed direction in expression formula in 90), in conjunction with brightness temperature, Split window algorithms coefficient is used
Following formula calculates surface temperature (Ts):
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| CN110222301A (en) * | 2019-06-03 | 2019-09-10 | 中国科学院遥感与数字地球研究所 | Earth's surface solar shortwave radiation calculation method under the conditions of a kind of haze |
| CN111157120A (en) * | 2020-01-10 | 2020-05-15 | 北京航空航天大学 | Surface temperature simulation method with space continuity |
| CN112487346A (en) * | 2020-10-26 | 2021-03-12 | 中国农业科学院农业资源与农业区划研究所 | Mountain land surface temperature remote sensing retrieval method |
| CN112487346B (en) * | 2020-10-26 | 2021-07-23 | 中国农业科学院农业资源与农业区划研究所 | Mountain land surface temperature remote sensing retrieval method |
| CN113588093A (en) * | 2021-08-10 | 2021-11-02 | 中国科学院地理科学与资源研究所 | Earth surface temperature estimation method in zenith observation direction |
| CN113588093B (en) * | 2021-08-10 | 2022-09-06 | 中国科学院地理科学与资源研究所 | Zenith observation direction earth surface temperature estimation method |
| CN114323291A (en) * | 2022-01-06 | 2022-04-12 | 中国地质大学（北京） | Method for calculating angle effect of satellite observation urban surface temperature |
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