CN111707376B - Surface temperature inversion method for broadband thermal infrared sensor - Google Patents
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Abstract
The invention discloses a surface temperature inversion method for a broadband thermal infrared sensor. The method mainly comprises the following steps: firstly, when observation data are obtained through a broadband thermal infrared sensor, a broadband spectral response function is divided into a plurality of narrow channels at set fixed intervals, then a formula of radiation energy and brightness temperature obtained by the broadband thermal infrared sensor is established according to the radiation energy obtained by each narrow channel, and finally the earth surface temperature can be obtained through the formula established in the solving step. The invention has the beneficial effects that: the inversion method provided by the invention adopts a plurality of equivalent wavelengths in the sensor spectral response range to substitute the radiation transmission equation and the Planck black body radiation equation to solve the LST, thereby improving the inversion precision of the LST and ensuring the implementation simplicity of the LST inversion.
Description
Technical Field
The invention belongs to the technical field of thermal infrared remote sensing, and particularly relates to a surface temperature inversion method for a broadband thermal infrared sensor.
Background
Surface Temperature (LST) is an important parameter that characterizes the characteristics of surface radiation and the exchange of energy between the surface and the atmosphere. LST is widely applied to the research fields of climate, environment, agriculture and the like. The broadband thermal infrared sensor is usually placed on the ground or in low altitude to observe the brightness and temperature of the ground surface. Because the influence of the atmosphere is small, the LST acquired on the ground can verify the satellite remote sensing LST product. LST images with high spatial resolution and high temporal resolution in the target area can be obtained from low-altitude thermal imager data with no man or people. The combination of the earth surface and the LST observed in the low altitude is helpful for analyzing the radiation characteristic of the heterogeneous underlying surface, and further promotes the remote sensing LST verification of the heterogeneous underlying surface satellite. Therefore, inverting high-precision LST from surface and low-altitude observation data is particularly important for correlation studies.
Currently, there are two main types of surface temperature inversion methods for single-channel sensors: (1) adopting a single-channel oriented inversion method: the method is mainly characterized in that atmospheric influences are approximately eliminated by means of a radiation transmission method or a simplification method thereof, and the atmospheric influences are substituted into equivalent wavelengths obtained by integral calculation of a spectral response function in a response waveband to solve LST. The method is simple in operation, but when the method is applied to observation data of a broadband thermal infrared sensor, the LST inversion accuracy is low. (2) The method of the lookup table comprises the following steps: the method substitutes data such as various atmospheric profiles, surface emissivity and the like by means of a radiation transmission model to establish a corresponding relation between the LST and the observed brightness temperature of the sensor, and has the problems that the implementation process is complex and highly depends on the spectral response characteristics of the sensor, a large amount of analog calculation is needed in the process of establishing a lookup table, and different lookup tables need to be established for different sensors.
Disclosure of Invention
The invention aims to provide a method for easily inverting a high-precision LST from observation data of a wide-band thermal infrared sensor aiming at the defects of the prior art.
The purpose of the invention is realized by the following technical scheme: a surface temperature inversion method facing a broadband thermal infrared sensor comprises the following steps:
s1, dividing the spectral response function of the broadband thermal infrared sensor into a plurality of narrow channels at set fixed intervals, wherein the equivalent wavelength of each narrow channel is as follows:
in the formula, λiIs the equivalent wavelength of the ith narrow channel in μm; lambda [ alpha ]1And λ2The starting wavelength and the ending wavelength of the narrow channel i; f (λ) is the spectral response function at wavelength λ;
s2, establishing the radiation energy and the brightness temperature T acquired by the broadband thermal infrared sensor according to the radiation energy acquired by each narrow channelsenThe formula of (a):
where n is the number of narrow channels,
is the radiance of the ith narrow channel, Bλ(Ts) For the surface temperature being TsSurface radiance of time, unit W/(m)2Sr μm), τ is the atmospheric permeability, L↓And L↑Is the atmospheric downlink radiation and the atmospheric uplink radiation, and the unit is W/(m)2·sr·μm)，LsolarRepresenting the radiance observed by the sensor contributed by the sun, b is a proportionality coefficient, b ≈ ajT2+bjT+cjA, b and c are coefficients corresponding to the sensor j, and sigma is Stefan-Boltzmann constant, and the value is 5.67 × 10-8W·m-2·K-4，△λiEquivalent band width:
fi(λ) is the spectral response function of the sensor in the ith narrow channel;
ελ,iemissivity for the ith narrow channel:
wherein, the first and second connecting parts are connected with each other; epsilonλT is the emissivity at wavelength λ, with a fixed value of 300K;
s3, the earth surface temperature T can be obtained by solving the formula established in the step S2s。
The invention has the beneficial effects that: the inversion method provided by the invention adopts a plurality of equivalent wavelengths in the sensor spectral response range to substitute the radiation transmission equation and the Planck black body radiation equation to solve the LST, thereby improving the inversion precision of the LST and ensuring the implementation simplicity of the LST inversion.
Drawings
FIG. 1 is a spectral response function of a sensor used in an example;
FIG. 2 is a diagram showing the change of the proportion b of radiant energy observed by each sensor to blackbody radiant exitance at the same temperature along with the temperature;
FIG. 3 is a graph of LST error for each sensor at different heights as a function of channel division width;
FIG. 4 is a graph of the parameter sensitivity of the surface temperature inversion method applied to different sensors.
Detailed Description
The technical scheme of the invention is described in detail below with reference to the accompanying drawings and embodiments:
inversion of the LST from the radiation data observed by the sensor typically requires calculation of the equivalent wavelength over the entire response band, and then substitution into the planck black body radiation formula for calculation to achieve conversion between radiation energy and temperature. For satellite sensors, the equivalent wavelength is usually calculated using the integral of the spectral response function of the channel with the wavelength, due to the narrow response band width. However, for a thermal infrared sensor with a wide response band, the equivalent wavelength obtained by the calculation method may bring a large uncertainty after being substituted, thereby reducing the accuracy of the LST inversion. In order to reduce the uncertainty of the broadband sensor caused by using a single equivalent wavelength, the broadband spectral response function is divided into a plurality of narrow channels at certain intervals, and then the equivalent wavelength of each narrow channel can be calculated by using the formula (1) (Jimeinez-
2003)：
In the formula, λiIs the equivalent wavelength of the ith narrow channel in μm; lambda [ alpha ]1And λ2The starting wavelength and the ending wavelength of the narrow channel i; f (λ) is the spectral response function at wavelength λ. Theoretically, the smaller the segmentation interval of the channel is, the higher the calculation accuracy is, but actually, when the segmentation interval is smaller than a certain width, the inversion accuracy can reach an acceptable range, and at this time, more calculation resources do not need to be consumed to obtain limited accuracy improvement.
The observation of broadband thermal infrared sensors, such as thermal infrared radiometers and thermal imagers, is typically luminance temperature. The total radiant energy observed by the channel is calculated from the observed luminance temperature, which can be calculated using the spectral response function and the black body radiation at the corresponding luminance temperature, as shown in equation (2):
wherein M' is the total energy observed in the channel in W/M2；Bλ(T) represents the radiance at wavelength λ at a luminance temperature of T, and the unit of B is W/(m)2Sr-. mu.m), the unit of T is K. When the temperature rises, the proportion b of the observed total radiant energy M' to the total blackbody radiation exitance M gradually rises. The relationship of b to the luminance temperature T can be well represented using a quadratic polynomial, which is also determined when the sensor is determined. In practical application, M' at the temperature T can be quickly calculated by using the proportion b and the blackbody radiation exitance M.
Wherein σ is Stefan-Boltzmann constant, and the value is 5.67X 10-8W·m-2·K-4(ii) a a. And b and c are coefficients corresponding to the sensor j.
One basic method of inverting LST is to invert according to the radiative transport equation of the thermal infrared band and the black body radiation equation. The radiation in the thermal infrared band is affected by the atmosphere when passing through the atmosphere, and according to the thermal infrared radiation transmission theory, the radiance observed by the sensor can be expressed by formula (4):
in the formula, LλThe unit is W/(m) for the radiance observed by the sensor2Sr μm); epsilon is the channel emissivity; b isλ(Ts) For the surface temperature being TsSurface radiance of time, unit W/(m)2Sr μm); τ is the atmospheric transmittance; l is↓And L↑Is the atmospheric downlink radiation and the atmospheric uplink radiation, and the unit is W/(m)2·sr·μm)。
For reducing the use of a single equivalent wavelengthThe invention discloses uncertainty of a broadband thermal infrared sensor in LST inversion, and a multi-equivalent-wavelength method is adopted. The radiation energy observed by the sensor in the corresponding range of the narrow spectrum can be represented by substituting the equivalent wavelength of each narrow channel obtained by the division into a radiation transmission equation and then multiplying the equivalent width of the narrow channel. And the total radiation energy observed by the sensor is the sum of the radiation energy of each narrow channel. Since the response band of some sensors extends to 4 μm, the effect of solar radiation needs to be considered together. Multiplying the observed radiance of each narrow channel by pi can calculate the unit of W/m2Can be described using equation (5):
in the formula, LsolarRepresents the radiance observed by the sensor contributed by the sun in W/(m)2Sr μm); Δ λ represents the equivalent width of the narrow channel, in μm; t issenThe luminance temperature observed by the sensor is in units of K. The equivalent band width can be calculated according to equation (6),
in the formula (f)i(λ) is the spectral response function of the sensor in the ith narrow channel.
The calculation method of each narrow-channel emissivity can be represented by formula (7) (Cheng and Liang, 2014):
in the formula, epsilonλ,iEmissivity of the ith narrow channel; epsilonλEmissivity at wavelength λ; t is an approximate LST, which is mostly around 300K, and since temperature changes have little influence on the emissivity calculation result, T is set to a fixed value of 300K at the time of calculation. Due to the selected sensorThe corresponding range of the spectrum has little difference with the curve range of the emissivity, and the emissivity changes smoothly in a thermal infrared band, so that the emissivity exceeding the curve range of the emissivity adopts the emissivity at the adjacent wavelength when calculating the emissivity of a narrow channel.
Examples
In the embodiment, four broadband thermal infrared sensors including SI-111, FLIR VUE pro, KT15.85 and TEL1000LW are selected, as shown in FIG. 1. A simulation data set is established by using the actually measured atmospheric profile and the surface emissivity to analyze the performance and the parameter sensitivity of the method, and then the method is applied to surface temperature inversion of actual observed data to compare LST differences acquired by different sensors.
The processing flow of this example is:
step 1: the spectral response function of the sensor is segmented in steps of 0.5 μm, for six segmentation intervals from 0.5 μm to 3.0 μm.
Step 2: and (3) inputting the spectral response function obtained by the segmentation in the step (1), the actually measured atmosphere profile and the earth surface emissivity into a MODTRAN 5.2 radiation transmission model for radiation transmission simulation. The input surface temperature range during simulation is 283.15-343.15K, and the step size of the temperature change is 2K. The simulated sensors were 2m, 300m and 1200m from the ground, respectively.
And step 3: and substituting the simulated atmospheric uplink radiation, atmospheric downlink radiation and atmospheric transmittance of each narrow band into the formula (5).
And 4, step 4: the equivalent wavelength of each narrow band is calculated using equation (1) and then substituted into equation (5).
And 5: the equivalent width of each narrow band is calculated using equation (6) and then substituted into equation (5).
Step 6: emissivity of each narrow band is calculated using equation (7) and then substituted into equation (5).
And 7: the surface temperature is solved from equation (5) and then compared to the surface temperature input by MODTRAN.
In example 1, the division width of the spectral response function significantly affects the inversion accuracy of LST; meanwhile, the optimal division width is influenced by the spectral response function type of the sensor and the erection height of the sensor. At a height of 2m, the LST of the four sensors yielded an RMSE below 0.2K and an MBE near-0.1K using a split width similar to the satellite sensor channel width, i.e. 0.5 μm. As the split width increases, the LST error of all sensors increases significantly; and the difference between the LSTs of the different sensors increases significantly. Sensors that are less affected by the atmosphere, namely SI-111, FLIR VUE pro and KT15.85, have less variation in the accuracy of the method as the sensor height increases; the LST accuracy of a sensor strongly affected by the atmosphere, TEL-1000LW, decreases rapidly with increasing height.
The method of the invention was subjected to sensitivity analysis:
step 1: errors are added to input parameters of the method, and the errors of the emissivity, the atmospheric uplink radiation, the atmospheric downlink radiation and the atmospheric transmittance are 1-15%.
Step 2: and substituting the parameters added with the errors into a formula (5) to solve the surface temperature.
And step 3: the method is applied to the observed data of different sensors, and the sensitivity of each parameter is analyzed.
In the above analysis, the sensitivity of the method to various parameters was obtained. When the method is applied to SI-111 and FLIR VUE pro, the sensitivity to LSE is very close; when the derivative is applied to KT15.85, the sensitivity to LSE is highest; applied to TEL-1000LW, the sensitivity to LSE was the lowest. The sensitivity of different sensors to LSE varies, with a 1% LSE uncertainty giving an uncertainty of 0.4-0.6K to LST. The method is most sensitive to atmospheric up-radiation when applied to TEL-1000 LW. The sensitivity of the four sensors to atmospheric downlink radiation is low. The sensitivity of the four sensors to atmospheric transmittance is very close, and each 1% uncertainty will introduce an error of 0.5-0.6K to the LST.
And (3) performing surface temperature inversion and comparison based on actual observation data:
step 1: and (5) simulating the emissivity, the atmospheric uplink radiation, the atmospheric downlink radiation and the atmospheric transmittance of each narrow waveband by using the actually measured atmospheric profile and substituting the measured atmospheric profile into the formula (5).
Step 2: and calculating the emissivity of each narrow channel by using the measured emissivity spectral curve, and substituting the measured emissivity spectral curve into the formula (5).
And step 3: the equivalent width of each narrow channel is calculated using equation (6) and then substituted into equation (5).
And 4, step 4: the surface temperature is solved from equation (5).
Through the content, the LST inversion result of the method used for actual observation data shows that the LST of the two sensors of FLIR VUE pro and SI-111 has larger difference in HZZ with stronger heterogeneity, and RMSE/MBE is 2.8/2.3K; the SD difference with the lowest heterogeneity is small, and the RMSE/MBE is 2.0/1.2K; in MFS at the downstream of the black river, the LST difference observed by the two instruments is 1.9K; in SUP, the difference in LST is 2.3K. Although the surface temperature inversion results in actual applications mostly generate differences exceeding 2.0K, the generation of the differences is influenced by the uncertainty of the actual instrument and the observation geometric differences.
Claims (1)
1. A surface temperature inversion method facing a broadband thermal infrared sensor is characterized by comprising the following steps:
s1, dividing the spectral response function of the broadband thermal infrared sensor into a plurality of narrow channels at set fixed intervals, wherein the equivalent wavelength of each narrow channel is as follows:
in the formula, λiIs the equivalent wavelength of the ith narrow channel in μm; lambda [ alpha ]1And λ2The starting wavelength and the ending wavelength of the narrow channel i; f (λ) is the spectral response function at wavelength λ;
s2, establishing the radiation energy and the brightness temperature T acquired by the broadband thermal infrared sensor according to the radiation energy acquired by each narrow channelsenThe formula of (a):
whereinN is the number of narrow channels,
is the radiance of the ith narrow channel, Bλ(Ts) For the surface temperature being TsSurface radiance of time, unit W/(m)2Sr μm), τ is the atmospheric permeability, L↓And L↑Is the atmospheric downlink radiation and the atmospheric uplink radiation, and the unit is W/(m)2·sr·μm)，LsolarRepresenting the intensity of radiation observed by the sensor, contributed by the sun, b is a proportionality coefficient, b ≈ ajT2+bjT+cj，aj、bj、cjIs the coefficient corresponding to the sensor j, sigma is Stefan-Boltzmann constant, and takes the value of 5.67 x 10-8W·m-2·K-4，△λiEquivalent band width:
fi(λ) is the spectral response function of the sensor in the ith narrow channel;
eλ,iemissivity for the ith narrow channel:
wherein epsilonλT is the emissivity at wavelength λ, with a fixed value of 300K;
s3, the earth surface temperature T can be obtained by solving the formula established in the step S2s。
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103616078A (en) * | 2013-11-19 | 2014-03-05 | 中国科学院地理科学与资源研究所 | Portable thermal infrared load field calibration and water surface temperature verification system device |
| CN104155007A (en) * | 2014-09-01 | 2014-11-19 | 中国科学院地理科学与资源研究所 | Multi-angle full-automatic earth surface fine emissivity spectrum collecting system device |
| CN105928620A (en) * | 2016-04-14 | 2016-09-07 | 中国科学院地理科学与资源研究所 | Thermal-infrared atmosphere correction parameterization method based on look-up table |
| WO2018145229A1 (en) * | 2017-02-10 | 2018-08-16 | 广西壮族自治区气象减灾研究所 | Accurate large-area inversion method for near-surface air temperature |
| KR20190136850A (en) * | 2018-05-31 | 2019-12-10 | 한국전자통신연구원 | Method for mitigation of topographic effect in infrared images taken from geostationary orbit imaging system and Apparatus Thereof |
| CN111323129A (en) * | 2020-03-25 | 2020-06-23 | 长光卫星技术有限公司 | Earth surface temperature inversion method based on broadband thermal infrared image |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103293522B (en) * | 2013-05-08 | 2014-12-10 | 中国科学院光电研究院 | Intermediate infrared two-channel remote sensing data surface temperature inversion method and device |
| CN103744069A (en) * | 2013-12-31 | 2014-04-23 | 中国科学院遥感与数字地球研究所 | Methane profile orthogonal inversion method aiming at AIRS (atmospheric infrared sounder) hyper-spectrum satellite data |
| CN107576417B (en) * | 2017-09-04 | 2019-05-10 | 电子科技大学 | A kind of round-the-clock surface temperature generation method |
| CN109446739B (en) * | 2018-12-20 | 2020-01-10 | 中国农业科学院农业资源与农业区划研究所 | Surface temperature multi-channel thermal infrared remote sensing inversion method |
| CN109596223B (en) * | 2018-12-24 | 2019-10-22 | 中国农业科学院农业资源与农业区划研究所 | A kind of multispectral satellite borne sensor lane device and method of direct inversion surface temperature |
-
2020
- 2020-06-30 CN CN202010607851.8A patent/CN111707376B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103616078A (en) * | 2013-11-19 | 2014-03-05 | 中国科学院地理科学与资源研究所 | Portable thermal infrared load field calibration and water surface temperature verification system device |
| CN104155007A (en) * | 2014-09-01 | 2014-11-19 | 中国科学院地理科学与资源研究所 | Multi-angle full-automatic earth surface fine emissivity spectrum collecting system device |
| CN105928620A (en) * | 2016-04-14 | 2016-09-07 | 中国科学院地理科学与资源研究所 | Thermal-infrared atmosphere correction parameterization method based on look-up table |
| WO2018145229A1 (en) * | 2017-02-10 | 2018-08-16 | 广西壮族自治区气象减灾研究所 | Accurate large-area inversion method for near-surface air temperature |
| KR20190136850A (en) * | 2018-05-31 | 2019-12-10 | 한국전자통신연구원 | Method for mitigation of topographic effect in infrared images taken from geostationary orbit imaging system and Apparatus Thereof |
| CN111323129A (en) * | 2020-03-25 | 2020-06-23 | 长光卫星技术有限公司 | Earth surface temperature inversion method based on broadband thermal infrared image |
Non-Patent Citations (2)
| Title |
|---|
| 基于AVHRR和VIRR数据的改进型Becker"分裂窗"地表温度反演算法;权维俊 等;《气象学报》;20121231;全文 * |
| 航空遥感地表温度时间归一化;朱琳清 等;《遥感学报》;20161004;全文 * |
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