CN112818605B - Method and system for rapidly estimating earth surface albedo - Google Patents
Method and system for rapidly estimating earth surface albedo Download PDFInfo
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Abstract
The invention provides a method and a system for quickly estimating earth surface albedo, which comprises the steps of establishing a channel conversion model, inputting an old channel earth surface albedo database, converting the earth surface albedo of a new satellite with consistent space-time range and corresponding sun zenith angles, and forming a new channel earth surface albedo mapping table based on the principle of space-time nearest neighbor; constructing a multi-layer artificial neural network, and training according to a new and old channel earth surface albedo mapping table; the estimation process of the new channel earth surface albedo comprises the steps of extracting longitude and latitude, observation time and sun zenith angle during observation when atmospheric remote sensing is carried out based on new channel observation, searching the old channel earth surface albedo and the sun zenith angle which are closest in distance and time in an old channel database, and using the old channel earth surface albedo and the sun zenith angle as input of an artificial neural network to obtain the earth surface albedo corresponding to the new channel; and converting to the earth surface albedo corresponding to the solar zenith angle at the observation time according to the assumption of the earth surface reflection model.
Description
Technical Field
The invention relates to the technical field of satellite passive remote sensing, in particular to an earth surface albedo estimation scheme.
Background
The satellite passive remote sensing technology inverts the characteristics of atmospheric molecules, aerosols, oceans or terrestrial surfaces by observing solar radiation reflected by the atmospheric molecules, aerosols, oceans or terrestrial surfaces. However, the radiation observation of satellite loads is a composite result from atmospheric molecular scattering, aerosol scattering, and marine or terrestrial reflections. Therefore, accurate estimation of surface reflection is an important prerequisite for extracting atmospheric composition information from satellite observations, such as aerosol inversion, cloud attribute inversion, trace gas inversion, and the like. An accurate earth surface albedo database becomes one of important supports of the atmospheric passive remote sensing technology.
The earth surface albedo is not a fixed value, changes along with the wavelength and the zenith angle of the sun, and the change rule is different according to the types of the ground objects. The change rule of the earth surface albedo is more complicated by the change of the ground features in the spatial distribution and the change along with the change of seasons. In addition, different satellite loads usually have different observation channels, which have different center wavelengths, different wavelength ranges, and different instrument responses. These differences all add difficulty to building a unified earth albedo database.
The difference in channels limits the use of existing ground albedo databases. Although decades of satellite observation accumulate a large amount of knowledge of the earth surface albedo, with the development of satellite observation technology, more and more new observation channels appear, the band division of the channels is more and more refined, and the new technologies cannot directly use the existing earth surface albedo database. The existing atmospheric passive remote sensing method uses independent databases (which are surface albedo databases established according to channel parameters of each load) or only can convert between observation channels with similar parameters to acquire the surface albedo on a new channel.
In conclusion, the old channel earth surface albedo product is more mature, a method for estimating the new channel earth surface albedo from the old channel earth surface albedo database is developed, summarized earth surface albedo knowledge can be fully utilized, reliable earth surface reflection information is provided for the atmospheric remote sensing based on new channel observation, and the development of a new satellite passive inversion technology is accelerated.
Disclosure of Invention
In order to solve the defects in the prior art, the invention provides a scheme for establishing a new channel conversion model and an old channel conversion model to finish the rapid estimation of the earth surface albedo.
In order to achieve the purpose, the technical scheme provided by the invention is a method for quickly estimating the earth surface albedo, which comprises a channel conversion model establishing process and a new channel earth surface albedo estimating process,
the channel conversion model establishing process comprises the following steps,
A1) inputting an old channel earth albedo database comprising earth albedo products alpha of old satellites1And corresponding solar zenith angle theta1；
A2) Inputting a new satellite earth surface albedo inversion result alpha consistent with the old satellite earth surface albedo product space-time range2And the corresponding solar zenith angle theta2；
A3) According to the assumption of the earth surface reflection model, alpha is2Conversion to solar zenith angle theta1Real surface albedo of'2；
A4) Surface albedo alpha 'for each new channel based on space-time nearest neighbor principle'2Searching the old channel earth surface albedo database for the earth surface albedo alpha of the nearest pixel and the nearest moment1And sun zenith angle theta1Forming a group of new and old channel earth surface albedo mapping tables in one-to-one correspondence;
A5) constructing a multilayer artificial neural network N, and mapping alpha in the new and old channel ground surface albedo mapping table1And theta1As network input, alpha'2As network output, training and storing the artificial neural network;
the estimation process of the new channel earth surface albedo comprises the following steps,
B1) when atmospheric remote sensing is carried out based on new channel observation, the longitude and latitude (Lat) of an observation target is extracted*,Long*) And observation time t*And the zenith angle of the sun during observation
B2) According to the latitude and longitude (Lat) of the target*,Long*) And an observation time t*Searching the old channel earth surface albedo database for the old channel earth surface albedo at the nearest distance and the nearest moment
And corresponding solar zenith angle
B3) Reflecting the earth surface of the old observation channel
And corresponding solar zenith angle
As the input of the artificial neural network N, calculating the earth surface albedo of the corresponding new channel
B4) Based on the assumptions of the earth's surface reflection model, will
Solar zenith angle at the time of conversion to observation time
Corresponding ground surface albedo
Moreover, the artificial neural network N preferably adopts a 10-layer BP neural network.
Furthermore, the obtained ground surface albedo
The method is applied to cloud attribute inversion and provides information of surface reflection.
The invention also provides a system for quickly estimating the earth surface albedo, which is used for realizing the method for quickly estimating the earth surface albedo.
Further, a processor and a memory are included, the memory for storing program instructions, the processor for invoking the stored instructions in the memory to perform a method for rapid estimation of earth's surface albedo as described above.
Alternatively, a readable storage medium is included, on which a computer program is stored, which, when executed, implements a method for fast estimation of earth's surface albedo as described above.
Aiming at the problem of the missing of the earth surface albedo database on the new channel, the invention uses the artificial neural network technology to establish a new and old channel conversion model of the hidden ground object type information. The model provides information of earth surface reflection radiation for an atmosphere remote sensing method based on a new observation channel, and provides support for accurately extracting atmospheric composition information. The invention does not require that new and old observation channels have correlation, namely different center wavelengths, different allowed wavelength ranges and different instrument responses are allowed. The key point of the invention is that the invention can be widely applied to various satellite loads.
The scheme of the invention is simple and convenient to implement, has strong practicability, solves the problems of low practicability and inconvenient practical application of the related technology, can improve the user experience, and has important market value.
Drawings
FIG. 1 is a flow chart of a method according to an embodiment of the present invention.
Detailed Description
The technical solution of the present invention is specifically described below with reference to the accompanying drawings and examples.
The method for quickly estimating the earth surface albedo provided by the embodiment of the invention comprises a channel conversion model establishing process and a new channel earth surface albedo estimating process. The establishment of the channel conversion model comprises the time-space matching of new and old channel earth surface albedo data and the training of an artificial neural network; the estimation of the new channel earth surface albedo is based on the trained artificial neural network to quickly estimate the earth surface albedo on the new channel of the new satellite.
A) Establishing channel conversion model according to past satellite products
1. Preparation of a surface albedo product (denoted as alpha) for a long time of a large area of old satellites1) And the corresponding zenith angle of the sun (denoted as theta)1) Namely an old channel surface albedo database. For example, MOD43C3, which is a global terrestrial albedo product based on MODIS observations, contains the terrestrial albedo on several channels and the corresponding zenith angle of the sun. In particular, it is preferred to prepare a surface albedo product for at least one year of old satellites in the area of use.
2. Preparing the inversion result of the new satellite's earth surface albedo (denoted as alpha) consistent with the space-time range of the old satellite's earth surface albedo product2) And the corresponding solar zenith angle (denoted as theta)2). The space-time range is consistent, namely the geographic range is consistent and the space range is consistent, for example, the data in 2020 in the range of Chinese continent. The invention only needs a small number of inversion results of the albedo of the new satellite earth surface, such as OCO2_ L2_ Lite _ FP. The method comprises the earth surface albedo based on OCO-2 satellite O2A hyperspectral channel inversion, but due to factors such as cloud layer shading, only a few part of observations can provide a credible earth surface albedo inversion result (compared with daily massive observation data of OCO-2). In practice, the view of the whole yearMeasurements are made hundreds of millions of times, but only a modest number of samples, such as a million samples, are required to build the conversion model.
3. According to the assumption of the earth surface reflection model, alpha is2Conversion to solar zenith angle theta1Surface albedo (. alpha. ')'2). In specific implementation, the surface reflection model may be implemented by using the prior art, and the present invention is not described in detail.
4. Ground surface albedo (alpha ') for each new channel based on the principle of space-time nearest neighbor'2) Searching the old channel earth surface albedo database for the earth surface albedo (alpha) of the nearest pixel and the nearest moment1) And the solar zenith angle (theta)1). And after the search is finished, a group of new and old channel earth surface albedo mapping tables which are in one-to-one correspondence is formed.
5. Constructing a multilayer artificial neural network (denoted as N), and mapping alpha in the mapping table1And theta1As network input, alpha'2The artificial neural network is trained and stored as a network output. In specific implementation, the BP neural network structure can be realized by adopting the prior art, and preferably, a 10-layer BP neural network is recommended, so that the effect is better.
B) Estimating earth albedo for new channel observations
1. When atmospheric remote sensing is carried out based on new channel observation, the longitude and latitude (Lat) of an observation target is extracted from an observation file*,Long*) Observation time (t)*) And the zenith angle of the sun during observation
For example, the latitude and longitude, the time and the sun zenith angle recorded in the product OCO2_ L1b _ Science are observation record files of a hyperspectral channel of an OCO-2 satellite O2A.
2. According to the latitude and longitude (Lat) of the target*,Long*) And an observation time (t)*) Searching the old channel earth surface albedo database for the old channel earth surface albedo at the nearest distance and the nearest moment
And itCorresponding sun zenith angle
Such as the surface albedo of several channels at corresponding locations and times in MOD43C3 and their corresponding solar zenith angles.
3. Reflecting the earth surface of the old observation channel
And corresponding solar zenith angle
As the input of the artificial neural network (N), the earth surface albedo of the corresponding new channel is calculated
4. Based on the assumptions of the earth's surface reflection model, will
Solar zenith angle at the time of conversion to observation time
Corresponding ground surface albedo
I.e. the earth's surface albedo at the observation moment of the new channel.
For the sake of easy understanding of the technical effects of the present invention, the following examples of the application of the method provided in the embodiments are provided:
1. object of implementation
Taking the cloud attribute inversion based on the hyperspectral channel of the OCO-2 satellite O2A as an example, before inversion, the interference of surface reflection on cloud information extraction needs to be removed from radiance observation. However, the OCO-2 satellite only provides the inversion result of the ground albedo under clear sky conditions, and lacks ground albedo data which can be used for inversion in cloud scenes. Therefore, when performing cloud inversion based on O2A channel, the invention can be applied to quickly estimate the ground surface albedo (wavelength range 758-.
2. Data selection
The global earth surface albedo daily product MCD43C3 established based on Aqua and Terra satellite MODIS instruments can provide 10 white space and 10 black space albedo of 10 channels (seven multispectral channels with central wavelengths of 645, 858, 469, 555, 1240, 1640 and 2130 nanometers, visible light broadband channels with the wavelength range of 0.3-0.7 micrometer, near infrared broadband channels with the wavelength range of 0.7-5.0 micrometer and short wave broadband channels with the wavelength range of 0.3-5.0 micrometer).
In order to carry out cloud property inversion by observing hyperspectral channels of an OCO-2 satellite O2A in a global range, a 2016 global MCD43C3 product and an OCO2_ L2_ Lite product with a credible earth surface albedo inversion result under a clear sky condition can be selected to establish a new channel conversion model and an old channel conversion model (artificial neural network).
3. Carrying out the process
A. Establishing a surface albedo conversion model of an MODIS channel and an O2A channel
1) 2016 collecting a global MCD43C3 product (alpha)1,θ1) And OCO2_ L2_ Lite product (. alpha.)2,θ2) Note that the product OCO2_ L2_ Lite only contains the inversion results of the earth surface albedo under clear sky conditions.
2) According to the assumption about the earth surface reflection model in the OCO2_ L2_ Lite product, alpha is converted into alpha2Conversion to solar zenith angle theta1Surface albedo (. alpha. ')'2)。
3) Searching and establishing new and old channel earth surface albedo mapping table (alpha) based on space-time nearest neighbor principle1,θ1)→α′2。
4) And (3) taking the mapping table as training data, selecting a 10-layer BP neural network as a new channel conversion model and an old channel conversion model, and training and storing the trained model (N). The training process only needs to be carried out once, and the training time is (alpha)1,θ1) As input, alpha'2As an output, the training process may be completed when a preset iteration condition is satisfied.
B. Predicting earth surface albedo of O2A channel in cloud scene
1) When cloud attribute inversion is performed based on 2016 OCO-2 satellite O2A hyperspectral channel observation, existing satellite products cannot provide earth surface albedo in a cloud scene. Extracting longitude and latitude (Lat) of the observation target from the observation record file OCO2_ L1b _ Science*,Long*) Observation time (t)*) And the zenith angle of the sun during observation
2) According to the 2016 MCD43C3 product data set and the space-time nearest neighbor principle, the latitude and longitude (Lat) is retrieved*,Long*) And time (t)*) Corresponding earth surface albedo of MODIS channel
And the zenith angle of the sun
3) Will be provided with
And
as input, the calculation is carried out by a 10-layer BP neural network
4) Based on the assumptions about the earth's surface reflection model in the OCO2_ L2_ Lite product, we will find that
Solar zenith angle at the time of conversion to observation time
Corresponding ground surface albedo
Namely according to the old and new channelsThe earth surface albedo at 765 nm wavelength of the channel of OCO-2 satellite O2A was estimated using a modeling.
5)
Will be applied in cloud attribute inversion to provide information on surface reflections.
4. Evaluation of results
In order to verify the feasibility and robustness of the invention, a verification test is designed in the embodiment. The experiment divides the collected 2016 new and old channel earth surface albedo collected in one-to-one correspondence into two groups according to longitude: 180 DEG W-90 DEG W and 0 DEG-90 DEG E are the first group, and 90 DEG W-0 DEG and 90 DEG E-180 DEG E are the second group. The first group is used as training data to train the artificial neural network, and the second group is used as test data to verify the accuracy of the method for estimating the O2A channel earth surface albedo.
The residual error trained based on the first group of data can be obtained through experiments, the error of the albedo of the O2A channel earth surface is estimated based on the trained new and old channel earth surface albedo conversion model, the conversion precision of the method, the correlation coefficient between the estimated value and the reference value all reach more than 0.9, the estimated value deviation is extremely small (about-0.001), and the root mean square error is only 0.023. According to the distribution of the model errors obtained by the test on the space, the absolute value of the deviation of most samples is less than 0.05. In addition, although the input of the artificial neural network does not contain time information and space information, the model still has very consistent performance on a training set and a testing set. This shows that the present invention is a method based on the characteristics of the terrain, and the applicability of the method is better than that of the method which relies on the space-time information to estimate the earth surface albedo.
If the above embodiment is not adopted, the ground albedo of the 858 nano-channel in the MCD43C3 is directly used as the output, and the error is much larger.
In specific implementation, a person skilled in the art can implement the automatic operation process by using a computer software technology, and a system device for implementing the method, such as a computer-readable storage medium storing a corresponding computer program according to the technical solution of the present invention and a computer device including a corresponding computer program for operating the computer program, should also be within the scope of the present invention.
In some possible embodiments, a system for fast estimation of earth's surface albedo is provided, comprising a processor and a memory, the memory for storing program instructions, the processor for calling the stored instructions in the memory to execute a method for fast estimation of earth's surface albedo as described above.
In some possible embodiments, a system for fast estimation of a ground surface albedo is provided, comprising a readable storage medium, on which a computer program is stored, which, when executed, implements a method for fast estimation of a ground surface albedo as described above.
The specific embodiments described herein are merely illustrative of the spirit of the invention. Various modifications or additions may be made to the described embodiments or alternatives may be employed by those skilled in the art without departing from the spirit or ambit of the invention as defined in the appended claims.
Claims (6)
1. A method for rapidly estimating the earth surface albedo is characterized by comprising the following steps: comprises a channel conversion model establishing process and a new channel earth surface albedo estimating process,
the channel conversion model establishing process comprises the following steps,
A1) inputting an old channel earth albedo database comprising earth albedo products alpha of old satellites1And corresponding solar zenith angle theta1；
A2) Inputting a new satellite earth surface albedo inversion result alpha consistent with the old satellite earth surface albedo product space-time range2And the corresponding solar zenith angle theta2；
A3) According to the assumption of the earth surface reflection model, alpha is2Conversion to solar zenith angle theta1Real surface albedo of'2；
A4) Based on the principle of space-time nearest neighbor, aiming at the earth surface albedo of each new channelα′2Searching the old channel earth surface albedo database for the earth surface albedo alpha of the nearest pixel and the nearest moment1And sun zenith angle theta1Forming a group of new and old channel earth surface albedo mapping tables in one-to-one correspondence;
A5) constructing a multilayer artificial neural network N, and mapping alpha in the new and old channel ground surface albedo mapping table1And theta1As network input, alpha'2As network output, training and storing the artificial neural network;
the estimation process of the new channel earth surface albedo comprises the following steps,
B1) when atmospheric remote sensing is carried out based on new channel observation, the longitude and latitude (Lat) of an observation target is extracted*,Long*) And observation time t*And the zenith angle of the sun during observation
B2) According to the latitude and longitude (Lat) of the target*,Long*) And an observation time t*Searching the old channel earth surface albedo database for the old channel earth surface albedo at the nearest distance and the nearest moment
And corresponding solar zenith angle
B3) Reflecting the earth surface of the old observation channel
And corresponding solar zenith angle
As the input of the artificial neural network N, calculating the earth surface albedo of the corresponding new channel
B4) Based on the assumptions of the earth's surface reflection model, will
Solar zenith angle at the time of conversion to observation time
Corresponding ground surface albedo
2. The method for rapidly estimating the albedo of the earth's surface as claimed in claim 1, wherein: the artificial neural network N preferably adopts a 10-layer BP neural network.
3. The method for rapidly estimating the albedo of the earth's surface as claimed in claim 1, wherein: obtained ground surface albedo
The method is applied to cloud attribute inversion and provides information of surface reflection.
4. A system for rapidly estimating the albedo of a ground surface is characterized in that: method for the fast estimation of the albedo of a ground surface as claimed in any of the claims 1-3.
5. The system for fast estimation of albedo of the earth's surface as claimed in claim 4, wherein: comprising a processor and a memory for storing program instructions, the processor being adapted to invoke the stored instructions in the memory to perform a method for fast estimation of earth's surface albedo as claimed in any one of claims 1-3.
6. The system for fast estimation of albedo of the earth's surface as claimed in claim 4, wherein: comprising a readable storage medium having stored thereon a computer program which, when executed, implements a method for fast estimation of earth's surface albedo as claimed in any one of claims 1-3.
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