CN109446693A - A kind of time-scale extension method of urban architecture scene thermal emission directionality intensity - Google Patents
A kind of time-scale extension method of urban architecture scene thermal emission directionality intensity Download PDFInfo
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Abstract
The present invention proposes a kind of time-scale extension method of urban architecture scene thermal emission directionality intensity, the wall including the component of urban architecture scene to be divided into roof, illumination ground, shade ground and different directions；Input building scene geometry and sun-sensor angle；According to component ratio in the building scene geometry and sun-sensor angle calculation visual field；Define wall temperature Tw；Calculate wall average brightness temperature in visual field；Defining illumination ground brightness temperature in visual field is Tig, the bright temperature in shade ground is Tsg, the bright temperature in roof is Troof；Calculate the bright temperature of inclined direction；Calculate the bright temperature of zenith direction；Calculate bright temperature direction heterogeneity intensity；Model coefficient parametrization；Calculate any time bright temperature direction heterogeneity intensity.The method achieve the accurate simulations changed over time to bright temperature directionality intensity.The model considers the particular attribute of building scene, and is suitable for remote-sensing inversion, can be applied to carry out angle correct to different moments direction temperature observation data.
Description
Technical field
The present invention relates to a kind of time-scale extension methods of urban architecture scene thermal emission directionality intensity.
Background technique
Remote sensing is in a wide range of upper effective means for obtaining surface temperature.Urban surface heat is obtained by Remote Sensing temperature
Force information, and then spatial framework, time-evolution and its driving mechanism of urban Heat Environment are disclosed, have become the master of quantitative remote sensing
Want field.However thermal infrared remote sensing can only obtain the information of one or certain several angle, can not spy upon city underlying surface and exist
The overall picture of entire 2 π episphere space heat radiation, and Thermal Infrared Remote Sensing (except fixed statellite) is typically only capable to obtain some
Or a few when discontinuity surface information, be difficult obtain city underlying surface surface temperature continuous changing condition on time dimension.
The most of heat radiation simulation models for being directed to city underlying surface constructed in recent years, still have from really for remote-sensing inversion larger
Distance, this distance, which is derived mainly from, to be changed rapidly in surface temperature itself in time dimension, has significant Diurnal Variation.With
MODIS/LST data instance, although possessing 4 surface temperature observation daily in most of areas in the whole world, however, this 4 times sights
It surveys in addition to observation angle is different, observation time is also not quite similar.For albedo inverting, the Different Effects of observation time are not
Greatly.But earth's surface geometry and physical property are not to determine surface temperature single factor, and external weather meteorology background is (each
Class is forced) also play important role.
Currently, the model that can be used to simcity thermal emission directionality time change includes Vinnikov et al.
(2012) parameterized model that the kernel-driven model and Lagouarde et al. (2008) proposed proposes.Ermida et al.
(2018) ability changed over time to both modeling vegetation thermal emission directionalities is assessed.In Vinnikov mould
In type, thermal emission directionality is represented as the sum of homogeneity component, emissivity directionality and component temperature inhomogeneity three effect.
Wherein, the component temperature difference core in Vinnikov model by solar zenith angle characterize component temperature difference, simulation thermal emission directionality with
The variation of time.But the tune by being not used in the parameterized model that similar Lagouarde et al. (2008) is proposed
Core processed, Vinnikov model underestimate thermal emission directionality.In the parameterized model that Lagouarde et al. (2008) is proposed
In, distribution of the thermal emission directionality intensity in hemispherical space is determined by two variables, is that the heterogeneity in hot spot direction is strong respectively
Spend Δ THSThe form factor changed with the heterogeneous intensity of characterization with view zenith angle.Wherein, Δ THSIt is one to change over time
Amount.Ermida et al. (2018) is by Δ THSThe function of solar zenith angle and the solar radiation of atmosphere top is expressed as to describe Δ
THSDiurnal variation and Nian Bianhua.But this relationship is not particularly suited for urban architecture scene.According to Krayenhoff and
Voogt (2016), in building scene, Δ THSThe temperature difference not only between component is related, also related with building structure, and this
The rule of segmentation is presented in relationship.Meanwhile being difficult to be inferred to the physical meaning of form factor, therefore can not be in form factor and earth's surface
Specific relationship is constructed between attribute.Substantially, parameterized model belongs to empirical model, does not account for the spy of urban architecture scene
There is attribute.Although having had already appeared the various strategies for attempting to carry out in a few days different observation moment surface temperatures time normalization
(Duan et al., 2014), but these methods not yet consider angular effect.In one word, it establishes one and both takes earth's surface into account
Temperature changes rapidly in time dimension, it is further contemplated that " the city underlying surface under close shot scale of the directional change of Remote Sensing temperature
Thermal emission directionality model ", it appears very urgent.
Summary of the invention
Technical problem to be solved by the invention is to provide the city underlying surface thermal emission directionalities under a kind of close shot scale
Model had both been taken surface temperature into account and had been changed rapidly in time dimension, it is further contemplated that the directional change of Remote Sensing temperature.
In order to solve the above-mentioned technical problem, technical solution proposed by the present invention is as follows:
A kind of time-scale extension method of urban architecture scene thermal emission directionality intensity, comprising the following steps:
Step 1: the component of urban architecture scene is divided into the wall on roof, illumination ground, shade ground and different directions
Body；
Step 2: input building scene geometry and sun-sensor angle, the building scene geometry include average
Building height-interval than (h/w) and roof accounting (λp)；The sun-sensor angle includes solar zenith angle (θs), sensor see
Observation apex angle (θv) and sensor and sun relative bearing
Step 3: according to component ratio in the building scene geometry and sun-sensor angle calculation visual field；
Step 4: defining wall temperature Tw；
Step 5: calculating wall average brightness temperature in visual field；
Step 6: defining illumination ground brightness temperature in visual field is Tig, the bright temperature in shade ground is Tsg, the bright temperature in roof is Troof；
Step 7: calculating the average brightness temperature of object in visual field when sensor perturbations are observed, the i.e. bright temperature of inclined direction；
Step 8: calculating the average brightness temperature of object in visual field when sensor vertical is observed, the i.e. bright temperature of zenith direction；
Step 9: calculating bright temperature direction heterogeneity intensity；
Step 10: model coefficient parametrization；
Step 11: calculating any time bright temperature direction heterogeneity intensity.
This method is to build scene geometry, the sun and sensor observation angle and the bright Wen Yi of different moments multi-angle
Matter intensity is as input variable, and the bright temperature direction heterogeneity intensity at other moment is as output variable under the conditions of clear sky, by group
Point temperature difference changes with time to be combined with thermal emission directionality geometrical model, is realized and is become at any time to bright temperature directionality intensity
The accurate simulation of change.The model is proposed based on physical process, it is contemplated that builds the particular attribute of scene, and it is anti-to be suitable for remote sensing
It drills, can be applied to carry out angle correct to different moments direction temperature observation data.
Detailed description of the invention
It, below will be to specific in order to illustrate more clearly of the specific embodiment of the invention or technical solution in the prior art
Embodiment or attached drawing needed to be used in the description of the prior art are briefly described.
Fig. 1 shows urban architecture scene thermal emission directionality strength time expanding method techniqueflow chart of the invention.
Fig. 2 is to utilize the bright temperature directionality intensity mould in 1 year (including different year different months) according to the method for the present invention
Quasi- data are corrected GUTA-T model, the model system of the model coefficient being fitted and energy balance model TUF-3D simulation
Several comparing results.
Fig. 3 is to utilize the bright temperature directionality intensity mould in 1 year (including different year different months) according to the method for the present invention
Quasi- data are corrected GUTA-T model, and the model coefficient inverse iteration that fitting obtains is entered GUTA-T model, difference is calculated
The bright temperature directionality Strength Changes of different moments in month and one day, the analog result pair with sensor observatory control model SUM
Than.
Fig. 4 is the verifying knot verified using measured data to the in a few days bright temperature direction heterogeneity intensity that GUTA-T is simulated
Fruit.
Specific embodiment
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with attached drawing to the present invention
Technical solution be clearly and completely described, it is clear that described embodiments are some of the embodiments of the present invention, rather than
Whole embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art are not making creative work premise
Under every other embodiment obtained, shall fall within the protection scope of the present invention.
Referring to Fig.1, urban architecture scene thermal emission directionality strength time expanding method of the invention the following steps are included:
A. component divides.The component of urban architecture scene is divided into roof, illumination ground, shade ground and different directions
Wall.
B. input building scene geometry and sun-sensor angle.Building scene geometry includes average building
Height-interval is than (h/w) and roof accounting (λp)；Sun-sensor angle includes solar zenith angle (θs), sensor view zenith angle
(θv) and sensor and sun relative bearing
C. component ratio in visual field is calculated.It is regarded according to the building scene geometry of input and sun-sensor angle calculation
Component ratio in.Wall ratio fwallCalculation method it is as follows:
The visible shade ground scale f of sensorvsgIt is as follows:
The then ratio f on the visible illumination ground of sensorvigIt is as follows:
D. wall temperature T is definedw.Metope illumination is stronger, and temperature is higher, according to metope direction with sun angle to wall table
Face temperature is parameterized.Assuming that being T without the wall temperature by direct solar radiation0, all metope ranges of temperature
For Ta, then wall temperature T is defined with formula (4)wAre as follows:
Wherein, n indicates the unit normal vector perpendicular to long sidelight screen wall facing the gate of a house body；S indicates solar direction unit normal vector.
E. wall average brightness temperature in visual field is calculated.
Wherein,It is sensor and sun relative bearing, range is 0 between π.
F. the bright temperature of other components in visual field is defined.If illumination ground brightness temperature is Tig, the bright temperature in shade ground is Tsg,
The bright temperature in roof is Troof。
G. the average brightness temperature of object in visual field when sensor perturbations are observed, the i.e. bright temperature of inclined direction are calculated.
The bright temperature calculation formula of inclined direction is as follows:
H. the average brightness temperature of object in visual field when sensor vertical is observed, the i.e. bright temperature of zenith direction are calculated.
By θv=0 brings formula (6) into, and it is as follows to obtain the bright temperature calculation formula of zenith direction:
I. bright temperature direction heterogeneity intensity is calculated.Bright temperature direction heterogeneity intensity is equal to Directional Brightness Temperature, and to subtract zenith direction bright
Temperature.In conjunction with formula (5) and (6), (θ under any sun-building-sensor geometrical condition is obtaineds,θv,) bright temperature direction is heterogeneous
Intensity:
Wherein,
fiso=T0-Tig (9)
fori=Ta (10)
fshw=Tsg-Tig (11)
Wherein,
kiso,kori,kshwIt is three kernel functions of model, it is several inputs known observation angle, sun angle and building scene
What structure, is directly calculated by formula (12)-(14), is known parameter.fiso,fori,fshwIt is three unknown systems of model
Number, the numerically respectively equal to temperature difference on shade wall and illumination ground, the different temperature difference and shade ground towards between wall
With the temperature difference on illumination ground；Fitting need to be observed by multi-angle Directional Brightness Temperature to obtain.fisokiso,forikori,fshwkshwTable respectively
Face the contribution of bright temperature direction heterogeneity intensity with levying shade wall, the variation of wall direction and shade.
J. model coefficient parameterizes.Component temperature difference in formula (9)-(11) is further parameterized, sun day is expressed as
Vertex angle thetasFunction it is as follows:
T0-Tig=a1cosθs (17)
Ta=a2sin2θs (18)
Tsg-Tig=a3cosθs (19)
Wherein, a1,a2,a3It is the new coefficient of model, characterizes shade wall and illumination the ground difference in temperature, different directions respectively
The temperature difference of wall and the temperature difference on shade ground and illumination ground are to the susceptibility of solar zenith angle, with material properties, building structure
It is related with weather conditions.
K. any time bright temperature direction heterogeneity intensity is calculated.Calculation method is as follows:
Input building scene structural parameters λpWith h/w, sun angle and observation angle, k in calculation formula (20)iso,
kori,kshw；It is fitted to obtain the coefficient in formula (20) by temperature direction heterogeneity intensity bright in different moments several observed directions
a1,a2,a3,；The sun angle and sensor observation angle for inputting any time again, calculate the bright Wen Fangxiang in the observed direction
Heterogeneous intensity.
The superiority of interpretation of result and this method:
(1) using the bright temperature direction heterogeneity strength simulation data in 1 year (including different year different months) to GUTA-T
Model is corrected, and the comparing result of the model coefficient of the model coefficient being fitted and energy balance model TUF-3D simulation is such as
Fig. 2.Fig. 2 a, b, c are respectively three coefficient a1,a2,a3The comparison of fitting result.
(2) using the bright temperature directionality intensity analogue data in 1 year (including different year different months) to GUTA-T model
It is corrected, the model coefficient inverse iteration that fitting obtains is entered into GUTA-T model, when being calculated in different months and one day different
The bright temperature directionality Strength Changes carved, analog result comparison such as Fig. 3 with sensor observatory control model SUM.Fig. 3 (a1),
(b1), (c1), (d1) are that the heterogeneous intensity of SUM modeling changes over time figure in different observed directions.Fig. 3 (a2),
(b2), (c2), (d2) are that the heterogeneous intensity of corresponding GUTA-T simulation changes over time figure.Fig. 3 (a3), (b3), (c3),
It (d3) is the average error curve figure of GUTA-T every month and SUM analog result.
(3) the in a few days bright temperature direction heterogeneity intensity that GUTA-T is simulated is verified using measured data, verification result
Such as Fig. 4.
(4) it is very big to show that Estimating The Model Coefficients result is influenced by building dense degree for test result, and Architecture Field red-spotted stonecrop is empty
It can be seen that the factor is smaller, Estimating The Model Coefficients error is bigger.But fitting result can characterize building structure to component to a certain extent
The influence of the temperature difference.GUTA-T can substantially simulate the distribution rule of the heterogeneous intensity of the bright temperature of different moments in different months and one day
Rule.In (view zenith angle θv, observed azimuth) be (40 °, 130 °), (40 °, 220 °), (60 °, 180 °) and (60 °,
270 °) when, the absolute error of heterogeneous strength simulation is respectively 0.33,0.36,1.10and 0.64 DEG C.Utilize measured data pair
The bright temperature direction heterogeneity intensity of GUTA-T simulation is verified, and the root-mean-square error of the two is 2.02 DEG C.
Embodiment described above, only a specific embodiment of the invention, to illustrate technical solution of the present invention, rather than
It is limited, scope of protection of the present invention is not limited thereto, although having carried out with reference to the foregoing embodiments to the present invention detailed
Illustrate, those skilled in the art should understand that: anyone skilled in the art the invention discloses
In technical scope, it can still modify to technical solution documented by previous embodiment or variation can be readily occurred in, or
Person's equivalent replacement of some of the technical features；And these modifications, variation or replacement, do not make corresponding technical solution
Essence is detached from the spirit and scope of technical solution of the embodiment of the present invention, should be covered by the protection scope of the present invention.Therefore,
The protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (9)
1. a kind of time-scale extension method of urban architecture scene thermal emission directionality intensity, which comprises the following steps:
Step 1: the component of urban architecture scene is divided into the wall on roof, illumination ground, shade ground and different directions；
Step 2: scene geometry is built in input and sun-sensor angle, the building scene geometry include average build
Height-interval is built than (h/w) and roof accounting (λp)；The sun-sensor angle includes solar zenith angle (θs), sensor observe day
Apex angle (θv) and sensor and sun relative bearing
Step 3: according to component ratio in the building scene geometry and sun-sensor angle calculation visual field；
Step 4: defining wall temperature Tw；
Step 5: calculating wall average brightness temperature in visual field；
Step 6: defining illumination ground brightness temperature in visual field is Tig, the bright temperature in shade ground is Tsg, the bright temperature in roof is Troof；
Step 7: calculating the average brightness temperature of object in visual field when sensor perturbations are observed, the i.e. bright temperature of inclined direction；
Step 8: calculating the average brightness temperature of object in visual field when sensor vertical is observed, the i.e. bright temperature of zenith direction；
Step 9: calculating bright temperature direction heterogeneity intensity；
Step 10: model coefficient parametrization；
Step 11: calculating any time bright temperature direction heterogeneity intensity.
2. according to the method described in claim 1, it is characterized by: wall ratio f in component ratio in step 3wallMeter
Calculation method is as follows:
Shade ground scale fvsgIt is as follows:
The ratio f on illumination groundvigIt is as follows:
3. according to the method described in claim 1, it is characterized by: the T of wall temperature described in step 4wIs defined as:
Wherein, n indicates the unit normal vector perpendicular to long sidelight screen wall facing the gate of a house body；S indicates solar direction unit normal vector.
4. according to the method described in claim 1, it is characterized by: wall average brightness temperature is calculated as follows in step 5:
Wherein,It is sensor and sun relative bearing, range is 0 between π.
5. according to the method described in claim 1, it is characterized by: the bright temperature calculation formula of inclined direction is as follows in step 7:
6. according to the method described in claim 1, it is characterized by: the bright temperature calculation formula of zenith direction in step 8 is as follows:
7. according to the method described in claim 1, it is characterized by: bright temperature direction heterogeneity strength calculation formula in step 9
It is as follows:
Wherein,
fiso=T0-Tig (2)
fori=Ta (3)
fshw=Tsg-Tig (4)
Wherein,
kiso,kori,kshwIt is three kernel functions of model, inputs known observation angle, sun angle and building scene geometry knot
Structure is directly calculated by formula (12)-(14), is known parameter.fiso,fori,fshwIt is three unknowm coefficients of model,
Numerically it is respectively equal to the temperature difference, different towards the temperature difference and shade ground and light between wall on shade wall and illumination ground
According to the temperature difference on ground；Fitting need to be observed by multi-angle Directional Brightness Temperature to obtain, fisokiso,forikori,fshwkshwCharacterization yin respectively
Face to shadow wall, the variation of wall direction and shade the contribution of bright temperature direction heterogeneity intensity.
8. according to the method described in claim 7, it is characterized by:
Component temperature difference in formula (9)-(11) is further parameterized, solar zenith angle θ is expressed assFunction it is as follows:
T0-Tig=a1cosθs (10)
Ta=a2sin2θs (11)
Tsg-Tig=a3cosθs (12)
Wherein, a1,a2,a3It is the new coefficient of model, characterizes shade wall and illumination the ground difference in temperature respectively, is different towards wall
The temperature difference and shade ground and illumination ground the temperature difference to the susceptibility of solar zenith angle, with material properties, building structure and day
Vaporous condition is related.
9. the method according to claim 1, wherein the calculation method of any time bright temperature direction heterogeneity intensity
It is as follows:
Input building scene structural parameters λp, h/w, different moments Directional Brightness Temperature observation, sun angle and observation angle, fitting
Formula (20), obtains model coefficient a1,a2,a3, then the sun angle and sensor observation angle of any time is inputted, calculating should
Bright temperature direction heterogeneity intensity in observed direction.
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| CN112985607A (en) * | 2021-01-25 | 2021-06-18 | 中国科学院空天信息创新研究院 | Method for correcting heat radiation directivity of geostationary satellite earth surface uplink long-wave radiation product |
| CN114323308A (en) * | 2022-01-06 | 2022-04-12 | 中国地质大学（北京） | Correction method for angle effect of remote sensing urban surface temperature |
| 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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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112985607A (en) * | 2021-01-25 | 2021-06-18 | 中国科学院空天信息创新研究院 | Method for correcting heat radiation directivity of geostationary satellite earth surface uplink long-wave radiation product |
| CN114323308A (en) * | 2022-01-06 | 2022-04-12 | 中国地质大学（北京） | Correction method for angle effect of remote sensing urban surface temperature |
| 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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