CN115265783A - Multi-platform satellite-borne point instantaneous cross calibration method and device based on hyperspectral data - Google Patents
Multi-platform satellite-borne point instantaneous cross calibration method and device based on hyperspectral data Download PDFInfo
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Abstract
The invention provides a multi-platform satellite-borne point instantaneous cross calibration method and device based on hyperspectral data, wherein the method comprises the following steps: determining a target load, determining matching data meeting the situation within the transit observation time difference according to the track prediction of the reference load and the target load, acquiring hyperspectral remote sensing data through the reference load, acquiring the radiance of each channel through the multispectral load of the target load, and converting the acquired hyperspectral remote sensing data into equivalent radiance of each channel of the multispectral load of the target load; and matching the reference load and the target load with a point-to-point manner for the area observed by the sub-satellite point, extracting effective cross calibration data for each pixel of the hyperspectral sensor, and calculating a radiometric calibration coefficient for the optical sensor to be calibrated according to the effective cross calibration data so as to correct the original radiance acquired by the optical sensor to be calibrated. The method can use a hyperspectral sensor with good calibration precision to uniformly perform on-orbit cross calibration on multi-platform optical loads at home and abroad.
Description
Technical Field
The invention relates to the technical field of on-orbit radiation calibration of a water color satellite optical sensor, in particular to a cross calibration method and device based on hyperspectral data transmission.
Background
Radiometric calibration is used for determining the corresponding relation between the observation value and the entrance pupil radiance value of a satellite sensor, and high-precision radiometric calibration is an important premise for the quantitative application of satellite remote sensing data. In the existing radiometric calibration technology, for satellite sensors in visible and near-infrared bands, three methods, such as on-orbit calibration, alternative calibration, and cross calibration, are generally used. Currently, international cross-calibration of different satellite platform sensors is often based on the sub-satellite point instantaneous cross-calibration method (SNO, simultaneous Nadir overlay). Research has found that SNO matching can accurately determine the offset and the difference of nonlinear coefficients between satellite pairs, thereby providing a strong constraint for linking the scaling coefficients of different satellites together. For a particular pair of polar orbiting satellites, the essence of the SNO method is to minimize the differences between instrumental measurements related to the earth scene by using instantaneous observations of the sub-satellite points near the intersection of the satellite orbits. The SNO method has been widely used for radiometric cross-calibration between polar orbiting satellites.
However, even with the SNO method, cross-scaling between different satellite platforms still has certain drawbacks: due to the lack of hyperspectral sensors, the cross calibration between international water color satellites at present mainly takes the cross calibration between multispectral loads, but because the spectral characteristics of different sensors are obviously different, obvious errors are introduced in the process of calculating spectrum matching and then acquiring equivalent entrance pupil radiance. Therefore, how to realize the cross calibration between different platform loads through a high-spectrum sensor with stable performance and high calibration precision is a problem to be solved urgently in the technical field of on-orbit radiometric calibration.
Disclosure of Invention
The primary objects of the present invention are: based on the method for calibrating instantaneous cross of the satellite points, the method and the device for calibrating the ocean optical remote sensing loads of a plurality of different satellite platforms in the on-orbit mode by utilizing the hyperspectral data are provided, and the technical problem that the spectrum difference and the calibration result of the calibration of the loads of different platforms are difficult to unify is solved.
The above purpose of the invention is realized by the following technical scheme:
firstly, providing a multi-platform satellite point instantaneous cross calibration method based on hyperspectral data, and carrying out on-orbit cross calibration by taking an optical sensor of a satellite platform as a target load and taking a hyperspectral water color sensor as a reference load; the method comprises the following steps: determining an optical sensor to be calibrated as a target load, determining matching data meeting the requirement in a transit observation time difference according to track prediction of a reference load and the target load, acquiring hyperspectral remote sensing data through the reference load, acquiring radiance of each channel through the multispectral load of the target load, and converting the acquired hyperspectral remote sensing data into equivalent radiance of each channel of the multispectral load of the target load; and matching the reference load and the target load point to point in an area observed by the satellite points to determine a one-to-one matching relation of data, extracting effective cross calibration data for each pixel of the hyperspectral sensor serving as the reference load, and calculating a radiometric calibration coefficient for the optical sensor to be calibrated according to the effective cross calibration data to correct the original radiance acquired by the optical sensor to be calibrated.
The multi-platform satellite-down point instantaneous cross calibration method based on the hyperspectral data is a universal method, can be used as a hyperspectral watercolor sensor with reference load as good calibration precision, and comprises the currently only on-Satellite Calibration Spectrometers (SCS) which are loaded on HY-1C and HY-1D, and hyperspectral loads which are loaded on polar orbit satellite platforms and can be transmitted in the following international places, such as an ocean watercolor instrument (OCI) on a PACE task.
In a preferred embodiment of the present invention, the track prediction for the reference load and the target load may be performed by the following method: and acquiring two-line satellite orbit data according to the reference load and the satellite number of the target load, and calculating the satellite orbit according to a satellite prediction model, thereby acquiring the SNO time and the spatial position of the reference load and the target load.
In a preferred embodiment of the present invention, the determination satisfies matching data within the transit observation time difference, and specifically, all data obtained by the orbit prediction needs to be screened, so that data from the reference load and the target load at least satisfy three conditions of time matching, space matching, and observation geometric matching.
In a further preferred scheme of the invention, the time matching means that data come from the off-satellite points of near-synchronous observation, and the off-satellite point data of near-synchronous observation come from a sensor with the transit time difference not exceeding 60 minutes; more preferably from sensors with transit time differences of no more than 10 minutes; most preferably from sensors with transit time differences of no more than 5 minutes. If the matching time is too long (more than 60 minutes), the water body and the atmospheric environment can generate large changes, so that a certain difference exists between the reference load and the target to be calibrated, and the calibration result is seriously influenced. Thus, the 60 minute setting is only a certain lower limit and the most preferred is also presented.
In a further preferred embodiment of the present invention, the spatial matching means that the spatial position difference between two pixels is not more than 0.01 °. The initial selection of the spatial matching principle comes from the consideration of the spatial resolution of the selected reference load SCS, and then other hyperspectral reference loads are added subsequently, and then corresponding adjustment is needed according to the actual spatial resolution.
In the preferred scheme of the invention, the hyperspectral remote sensing data acquired by the reference load is the top radiance of the full-wave-band atmosphere layer, so that the wave band setting of different multispectral sensors can be covered to the greatest extent, and the compatibility is better.
In a further preferred scheme of the present invention, the conversion of the acquired hyperspectral remote sensing data into equivalent radiances of each channel of the multispectral load of the target load is specifically realized by the following method: and reading the spectral response function of the target load, and converting the full-waveband atmospheric layer top radiance of the reference load into equivalent radiance corresponding to the target load through a convolution method.
In a further preferred embodiment of the present invention, the radiometric calibration coefficient is calculated for the optical sensor to be calibrated, and the following formula (2) is calculated:
wherein the content of the first and second substances,
for reference load in
The equivalent atmospheric layer top radiance of the band,
for the target load at
The top radiance of the atmospheric layer of the band.
In addition, the invention also provides a multi-platform satellite-bottom point instantaneous cross calibration device based on hyperspectral data, which is used for performing on-orbit cross calibration by taking an optical sensor of a satellite platform as a target load and taking a hyperspectral water color sensor as a reference load; the device comprises:
the matching data determining module is used for determining an optical sensor to be calibrated as a target load, determining matching data meeting the transit observation time difference according to the track prediction of the reference load and the target load, and screening effective pixels to generate a high-quality SNO matching data set;
a radiance data acquisition module, configured to acquire hyperspectral remote sensing data through the reference load, acquire radiance of each channel through the multispectral load of the target load, and convert the acquired hyperspectral remote sensing data into equivalent radiance of each channel of the multispectral load of the target load;
the radiometric calibration coefficient calculation module is used for matching the reference load and the target load with respect to a region observed by a satellite point in a point-to-point manner so as to determine a one-to-one matching relationship of data, extracting effective cross calibration data for each pixel of the hyperspectral sensor, and calculating a radiometric calibration coefficient for the optical sensor to be calibrated according to the effective cross calibration data;
and the correction module is used for correcting the original radiance acquired by the optical sensor to be calibrated based on the radiometric calibration coefficient obtained by the radiometric calibration coefficient calculation module.
The invention also provides a system for multi-platform satellite-borne point instantaneous cross calibration based on hyperspectral data, which comprises a memory and a processor, wherein the memory is used for storing a program for multi-platform satellite-borne point instantaneous cross calibration, and the processor is used for operating the program for multi-platform satellite-borne point instantaneous cross calibration based on hyperspectral data so as to enable the system to execute the method for multi-platform satellite-borne point instantaneous cross calibration based on hyperspectral data.
The invention also provides a computer readable storage medium, wherein a program for multi-platform off-satellite point instantaneous cross calibration is stored on the computer readable storage medium, and when the program for multi-platform off-satellite point instantaneous cross calibration is executed by a processor, the multi-platform off-satellite point instantaneous cross calibration method based on hyperspectral data is realized.
The method can realize the purpose of uniformly carrying out on-orbit cross calibration on the domestic and foreign multi-platform optical loads by utilizing one hyperspectral sensor with good calibration precision, and has the following beneficial effects compared with the prior art:
(1) As a universal method, the on-orbit cross calibration of multispectral/hyperspectral optical loads on different international water color satellite platforms can be realized by utilizing a hyperspectral sensor with higher radiometric calibration precision;
(2) Compared with an on-site substitution calibration method, the on-orbit radiation calibration method can effectively improve the frequency of on-orbit radiation calibration and save a large amount of manpower and material resources required by on-site substitution calibration;
(3) The invention introduces the high-spectrum optical load into the in-orbit cross calibration, improves the spectrum matching effect, has good applicability to the multi-spectrum optical loads with different parameters running in the orbit at present, has good compatibility to the multi-spectrum or high-spectrum optical loads which are not transmitted, and has both practical and future significance;
(4) The invention carries out cross calibration work through the hyperspectral remote sensing data of the sub-satellite points, and connects multispectral loads of different platforms together, so that the unified analysis and research on calibration results of different loads become possible.
In addition, the method combines the satellite orbit prediction and the cross calibration between satellites to form a set of cross validation program integrating the SNO time of the matched load, the position prediction and the hyperspectral cross calibration. The method of the invention can achieve continuous accumulation and update, thereby perfecting the SNO database and realizing the monitoring and analysis of the integral change of the instrument by utilizing the formed long-time calibration sequence of each sensor.
Drawings
FIG. 1 is a flow chart of cross calibration based on hyperspectral data and SNO methods in accordance with the present invention.
FIG. 2 is a chart of cross-scaling coefficient spectra of SCS-HY1C/HY1D and multi-stage sensor in example 1.
Detailed Description
The invention provides a cross calibration method for internationally different satellite platform loads based on hyperspectral data and intersatellite point instantaneous cross. In order that the above objects, features and advantages of the present invention may be more clearly illustrated, the present invention will be described in detail below with reference to fig. 1 and a specific embodiment.
The invention relates to a multi-platform satellite-bottom point instantaneous cross calibration method based on hyperspectral data, which is used for carrying out on-orbit cross calibration by taking any optical sensor of different international satellite platforms as a target load and taking a hyperspectral water color sensor with good calibration precision as a reference load; referring to fig. 1, the specific implementation flow is as follows:
(1) Reading of desired data
Firstly, two lines of orbit data of a satellite are obtained according to satellite numbers of a reference load and a target load, calculation of the satellite orbit is carried out according to an SGP4 (Simplified General orbits 4) satellite prediction model to obtain SNO time and positions of the reference load and the target load, preparation is made for later data selection, the transit time difference is preferably controlled within 5 minutes, and the influence of orbit drift on calibration is eliminated simultaneously through matching. Secondly, for the reference load, the original radiance data of each wave band needs to be acquired through well-scaled L1 level image data. Finally, for the target load, after the data including the SNO location is acquired, the spectral response function is also read in preparation for subsequent spectral matching.
(2) Determination of SNO region
After the data of SNO areas contained in the reference load and the target load are respectively obtained through the step (1), the longitude and latitude information of the reference load and the target load are respectively read in, and the crossed SNO areas are selected through longitude and latitude matching. To produce a high quality SNO match data set, the matching principle that needs to be followed is as follows:
a time matching principle: when the hyperspectral sensor used as the reference load is used for carrying out cross calibration with other platform loads, data products of sub-satellite points which are approximately synchronously observed are selected, and the data products are recommended to be guaranteed within 10 minutes or less in transit time difference, so that the influence of observation difference caused by time change on cross calibration results is avoided as much as possible. If the transit time of the target load needing to be calibrated and the reference load is really different greatly, so that a matching result is difficult to obtain, the transit time can be relaxed as appropriate, but at most one hour is recommended;
a space matching principle: after the longitude and latitude, the observation geometry and the atmospheric layer top radiance of the two sensors in a cross area are respectively obtained, point-to-point space matching is carried out on the two sensors, a 0.01-degree space threshold value is set, the closest pixel points meeting the threshold value range are obtained through matrix operation and are used as the matching points of the two sensors, repeated matching points are eliminated, only one-to-one conditions and relevant matching parameters are kept, and therefore the reference load and the pixel points of the target load are completely matched, and a preliminary matching data set is provided for the calculation of a subsequent cross calibration coefficient.
Observing a geometric matching principle: when intersecting other loads, it is desirable to ensure as far as possible that the matching data are obtained under the same observation geometry. When the two geometric information are matched, the observation geometric information of the two geometric information also needs to be recorded, so that the calibration result can be conveniently analyzed subsequently;
and respectively reading data of the intersection region of the reference load and the target load according to the principle, performing primary screening, and storing information including DN (numerical digit) value (or atmospheric layer top radiance) of the intersection part, observation geometry and the like. And the DN values of the reference load and the target load are converted into respective atmospheric layer top radiance values.
(3) Efficient pixel screening
After longitude and latitude matching is carried out on the reference load and the target load, effective matched pixels are screened through the mask information of the pixels, and invalid pixels including cloud, flare, pixels with overlarge observation angles and the like are eliminated. And finally, determining the matched pixel points meeting the validity.
(4) Uniform region selection
And carrying out sliding window processing on the target load through mean filtering so as to eliminate the non-uniform area. Taking MODIS as an example, two kinds of sliding windows, 3 × 3 and 5 × 5, are respectively provided, and uniformity judgment is performed on the top radiation brightness of the atmospheric layer of the 869nm channel. The data are first filtered with these two sliding windows (A1, A2), respectively, and then the ratio of the two filters is calculated. The mass percent is 1%, namely the ratio range after two kinds of filtering is shown as the following formula (1):
the quality control conditions can also be adjusted according to actual conditions, and finally, the matching data set meeting the uniformity conditions is further determined.
(5) Selected region parameter extraction
After the matching and screening processes, a group of radiance matching data sets of the reference load and the target load are determined, wherein the reference hyperspectral sensor needs to obtain the full-wave-band top radiance of the atmospheric layer, and regular on-track calibration needs to be carried out to ensure the data accuracy of the reference load.
(6) Calculation of cross-scaling results
Due to the band difference, in order to calculate the cross scaling coefficient, the atmospheric top radiance of the hyperspectral space of the reference load must be converted into the equivalent radiance corresponding to the target load, and a spectral response function of the target load and a convolution method are required.
After calculating the equivalent radiance of the reference load, the cross calibration coefficient is carried out
The formula (2) is as follows:
wherein the content of the first and second substances,
for reference load in
The equivalent atmospheric layer top radiance of the band,
for the target load at
The top radiance of the atmospheric layer of the band. Finally, an average cross-scaling coefficient of the total matching data set can be obtained through the obtained respective cross-scaling coefficient of each group of matching data.
(7) Accumulated SNO database
In the continuous cross calibration process of the reference load and the target load, calibration data and results of each satellite platform are gradually accumulated to form a continuous perfect SNO database. Through the formation of the database, the reanalysis of each satellite in the future can be well facilitated.
Example 1.
Based on the specific implementation manner of the invention, the high-spectrum sensor on-Satellite Calibration Spectrometer (SCS) respectively carried on HY-1C and HY-1D is selected as a reference load, the cross calibration of the optical loads of other satellite platforms is calculated, and a preliminary calibration result is given below. Wherein, the SCS carried on an HY-1C platform (morning star) is crossly calibrated with sensors such as MODIS-Terra and OLCI-S3A/S3B; and (3) carrying out cross calibration on SCS (SCS) carried on an HY-1D platform (afternoon star) and sensors such as MODIS-Aqua, VIIRS-SNPP, VIIRS-NOAA20 and the like. The specific matching cases are shown in the following table.
Watch (A)
Multi-platform cross calibration matching correspondence table
According to the principle and the method, the crossing conditions of the satellite calibration spectrometers respectively carried on HY-1C and HY-1D and other platform loads are sorted and selected, 11 groups of crossing calibration results of SCS and 5 different loads are obtained, and specific matching data and results are respectively shown in a table 2 and a figure 2.
Watch (A)
SCS versus target load transit schedule
Note: the transit time is exemplified by "20200322T024403", and represents 2020, 03, 22, 2, 44 min, 03 sec of UTC time.
From the result of the present embodiment that the SCS of the hyperspectrum is used to calibrate the instantaneous intersection of the sub-satellite points of other multi-platform sensors, the following preliminary conclusions are obtained:
(1) For the sensor which obtains more than one effective cross calibration result, the cross calibration results of each time by utilizing the hyperspectral load are more consistent;
(2) The cross calibration coefficient of the reference load to each sensor is about 1.0, and the effectiveness of the method for cross calibration of the multi-satellite platform load is preliminarily shown;
(3) As can be seen from FIG. 2, the calibration coefficient curves of MODIS-Terra and MODIS-Aqua are relatively similar, and the calibration coefficient curves of VIIRS-SNPP and VIIRS-NOAA20 are relatively similar, which also indicates the effectiveness of the calibration method of the present invention.
Claims (10)
1. A multi-platform satellite-bottom point instantaneous cross calibration method based on hyperspectral data is characterized in that on-orbit cross calibration is carried out by taking an optical sensor of a satellite platform as a target load and taking a hyperspectral water color sensor as a reference load; the method comprises the following steps: determining an optical sensor to be calibrated as a target load, determining matching data meeting the requirement in a transit observation time difference according to track prediction of a reference load and the target load, acquiring hyperspectral remote sensing data through the reference load, acquiring radiance of each channel through the multispectral load of the target load, and converting the acquired hyperspectral remote sensing data into equivalent radiance of each channel of the multispectral load of the target load; and matching the reference load and the target load point to point in an area observed by the satellite points to determine a one-to-one matching relation of data, extracting effective cross calibration data for each pixel of the hyperspectral sensor serving as the reference load, and calculating a radiometric calibration coefficient for the optical sensor to be calibrated according to the effective cross calibration data to correct the original radiance acquired by the optical sensor to be calibrated.
2. The method of claim 1, wherein: the track prediction of the reference load and the target load is completed by the following method: and acquiring two-line satellite orbit data according to the reference load and the satellite number of the target load, and calculating the satellite orbit according to a satellite prediction model, thereby acquiring the SNO time and the spatial position of the reference load and the target load.
3. The method of claim 1, wherein: the determination meets the matching data in the transit observation time difference, and particularly all data obtained through the track prediction need to be screened, so that the data from the reference load and the target load at least meet three conditions of time matching, space matching and observation geometric matching; the time matching refers to that data come from a sensor with the transit time difference not exceeding 60 minutes; the spatial matching means that the spatial position difference of two pixel points is not more than 0.01 degrees.
4. The method of claim 3, wherein: the time matching refers to that data come from a sensor with the transit time difference not exceeding 10 minutes.
5. The method of claim 3, wherein: the hyperspectral remote sensing data acquired by the reference load is the top radiance of the full-wave-band atmosphere layer.
6. The method of claim 1, wherein: converting the acquired hyperspectral remote sensing data into equivalent radiances of each channel of the multispectral load of the target load by the following method: and reading the spectral response function of the target load, and converting the full-waveband atmospheric layer top radiance of the reference load into equivalent radiance corresponding to the target load through a convolution method.
7. The method of claim 1, wherein: calculating the radiometric calibration coefficient of the optical sensor to be calibrated, and calculating the formula (2) as follows:
wherein the content of the first and second substances,
for reference load in
The equivalent atmospheric layer top radiance of the band,
for the target load at
The top radiance of the atmospheric layer of the band.
8. The device for multi-platform satellite lower point instantaneous cross calibration based on hyperspectral data is used for performing on-orbit cross calibration by taking an optical sensor of a satellite platform as a target load and taking a hyperspectral water color sensor as a reference load; the device comprises:
the matching data determining module is used for determining an optical sensor to be calibrated as a target load, determining matching data meeting the transit observation time difference according to the track prediction of the reference load and the target load, and screening effective pixels to generate a high-quality SNO matching data set;
a radiance data acquisition module, configured to acquire hyperspectral remote sensing data through the reference load, acquire radiance of each channel through the multispectral load of the target load, and convert the acquired hyperspectral remote sensing data into equivalent radiance of each channel of the multispectral load of the target load;
the radiometric calibration coefficient calculation module is used for matching the reference load and the target load with respect to a region observed by a satellite point in a point-to-point manner so as to determine a one-to-one matching relationship of data, extracting effective cross calibration data for each pixel of the hyperspectral sensor, and calculating a radiometric calibration coefficient for the optical sensor to be calibrated according to the effective cross calibration data;
and the correction module is used for correcting the original radiance acquired by the optical sensor to be calibrated based on the radiometric calibration coefficient obtained by the radiometric calibration coefficient calculation module.
9. The hyperspectral data based multi-platform off-satellite instantaneous crossing calibration system comprises a memory and a processor, wherein the memory is used for storing a multi-platform off-satellite instantaneous crossing calibration program, and the processor is used for running the hyperspectral data based multi-platform off-satellite instantaneous crossing calibration program so as to enable the system to execute the hyperspectral data based multi-platform off-satellite instantaneous crossing calibration method according to claim 1.
10. A computer readable storage medium, on which a multi-platform off-satellite point instantaneous crossing calibration program is stored, which when executed by a processor implements the hyper-spectral data based multi-platform off-satellite point instantaneous crossing calibration method of claim 1.
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| CN116306819A (en) * | 2023-03-22 | 2023-06-23 | 大连海事大学 | Hyperspectral cross calibration method and device based on spectrum reconstruction and electronic equipment |
| CN116735008A (en) * | 2023-08-11 | 2023-09-12 | 中国科学院空天信息创新研究院 | Calibration method and device for infrared cross radiation, electronic equipment and medium |
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| CN113177512A (en) * | 2021-05-20 | 2021-07-27 | 国家卫星气象中心(国家空间天气监测预警中心) | Matching threshold analysis method for intersatellite cross radiometric calibration |
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| CN116735008A (en) * | 2023-08-11 | 2023-09-12 | 中国科学院空天信息创新研究院 | Calibration method and device for infrared cross radiation, electronic equipment and medium |
| CN116735008B (en) * | 2023-08-11 | 2023-11-14 | 中国科学院空天信息创新研究院 | Calibration method and device for infrared cross radiation, electronic equipment and medium |
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