CN115436369B - A method and system for identifying atmospheric rivers based on domestic hyperspectral satellites - Google Patents
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Abstract
本发明公开了一种基于国产超光谱卫星的大气河识别方法及系统，相关方法包括：对全球水汽柱总量数据集进行平滑处理并排除热带水汽干扰，再进行大气河事件的初步识别，若初步识别为大气河事件，则划分大气河发生区域；利用大气河发生区域内的多年际水汽柱总量分布确定阈值，并利用阈值从所述大气河发生区域中提取大气河路径；利用大气河路径中最高水汽柱总量对应的像素点计算大气河轴线，并利用大气河轴线判断是否属于气旋系统；若属于，则表明初步识别的大气河事件为误判；若不属于，则表明最终识别出的大气河事件。上述方案能够实现全球范围全自动的大气河识别，无需繁琐的图像细化处理，也可以滤除非大气河引起的其他强水汽输送事件的干扰。
The present invention discloses an atmospheric river identification method and system based on a domestic hyperspectral satellite. The related method includes: smoothing the global water vapor column total data set and eliminating tropical water vapor interference, and then performing preliminary identification of atmospheric river events. If it is initially identified as an atmospheric river event, the atmospheric river occurrence area is divided; the threshold is determined by using the multi-year inter-annual water vapor column total distribution in the atmospheric river occurrence area, and the atmospheric river path is extracted from the atmospheric river occurrence area using the threshold; the atmospheric river axis is calculated using the pixel points corresponding to the highest water vapor column total in the atmospheric river path, and the atmospheric river axis is used to determine whether it belongs to a cyclone system; if it does, it indicates that the initially identified atmospheric river event is a misjudgment; if it does not, it indicates that the atmospheric river event is finally identified. The above scheme can realize fully automatic atmospheric river identification on a global scale without cumbersome image refinement processing, and can also filter out interference from other strong water vapor transport events caused by non-atmospheric rivers.
Description
Technical Field
The invention relates to the field of geophysics, in particular to an atmospheric river identification method and system based on a domestic hyperspectral satellite.
Background
Atmospheric rivers are an elongated water vapor conveyor belt located below the troposphere, typically at medium and high latitudes, originating from tropical and subtropical ocean surfaces, and can transport large amounts of water vapor to medium and high latitudes. The atmospheric river covers less than 1/10 of the circumference of the earth, but the ratio of the atmospheric river to the total amount of water vapor transported to the polar region at the middle latitude exceeds 9/10, and the atmospheric river is a key factor for generating strong precipitation and flood. Therefore, for global extreme hydrologic event research, it is particularly important to accurately identify atmospheric river events. The current definition of an atmospheric river is "narrow and transient strong horizontal vapor transport hallways, usually associated with low-altitude rapid flows in front of a temperate zone cyclonic cold front". Since the definition does not specify specific values for the length, width and water vapor transport capacity of the atmospheric river, it emphasizes morphological features of the atmospheric river and its correlation with weather systems, which is detrimental to identifying atmospheric river events. Therefore, it is necessary to quantify morphological characteristics of the atmospheric river. It is generally considered that the region where the water vapor transport direction is directed from the equator to a high latitude, the length is more than 2000km, the width is less than 1000km, and the total amount of the water vapor column is more than 2cm is an atmospheric river occurrence region.
The current water vapor data that can be used to identify atmospheric river events includes (1) satellite-observed total water vapor column volume and (2) pattern-simulated water vapor flux. The comparison result shows that the number and the shape of the atmospheric rivers identified by the two data are almost the same, and the feasibility of identifying the atmospheric river event by utilizing the total quantity of the water vapor columns observed by satellites is proved. However, the existing atmospheric river event identification scheme mainly has the following technical problems that (1) global full-automatic identification cannot be achieved, (2) complicated image refinement processing is involved, and (3) interference of other strong water vapor conveying events exists to influence the accuracy of atmospheric river event identification.
Disclosure of Invention
The invention aims to provide an atmospheric river identification method and system based on domestic hyperspectral satellites, which are a global and full-automatic atmospheric river identification scheme, do not need complicated image refinement treatment, and can also filter interference of other strong water vapor conveying events caused by non-atmospheric rivers.
The invention aims at realizing the following technical scheme:
An atmospheric river identification method based on domestic hyperspectral satellites comprises the following steps:
Acquiring a global water vapor column total data set inverted by utilizing a domestic satellite hyperspectral, performing smoothing treatment on the global water vapor column total data set and removing tropical water vapor interference to obtain a corrected global water vapor column total data set;
Performing preliminary identification of the atmospheric river event from the corrected global water vapor column total data set, and dividing an atmospheric river occurrence area if the preliminary identification is the atmospheric river event;
Determining a threshold value by utilizing the total quantity distribution of the water vapor columns in the atmosphere river generation area for years, and extracting an atmosphere river path from the atmosphere river generation area by utilizing the threshold value;
calculating an atmospheric river axis by using a pixel point corresponding to the total quantity of the highest water vapor column in the atmospheric river path, judging whether the atmospheric river axis belongs to a cyclone system or not by using the atmospheric river axis, if the atmospheric river axis belongs to the cyclone system, indicating that the preliminarily identified atmospheric river event is misjudgment, and if the atmospheric river event does not belong to the cyclone system, indicating that the finally identified atmospheric river event.
An atmospheric river identification system based on domestic hyperspectral satellites, comprising:
the data acquisition and correction unit is used for acquiring a global water vapor column total data set inverted by utilizing the hyperspectral of the domestic satellite, carrying out smoothing treatment on the global water vapor column total data set and removing tropical water vapor interference to obtain a corrected global water vapor column total data set;
The preliminary identification and region division unit is used for carrying out preliminary identification of the atmospheric river event from the corrected global water vapor column total data set, and if the preliminary identification is the atmospheric river event, the atmospheric river occurrence region is divided;
the atmospheric river path extraction unit is used for determining a threshold value by utilizing the total quantity distribution of the vapor columns in the atmosphere river generation area for years, and extracting an atmospheric river path from the atmosphere river generation area by utilizing the threshold value;
The secondary atmospheric river event identification unit is used for calculating an atmospheric river axis by using pixel points corresponding to the total quantity of the highest water vapor columns in the atmospheric river path, judging whether the atmospheric river axis belongs to a cyclone system or not by using the atmospheric river axis, if the atmospheric river axis belongs to the cyclone system, indicating that the primarily identified atmospheric river event is misjudgment, and if the atmospheric river event does not belong to the cyclone system, indicating that the finally identified atmospheric river event.
A processing device includes one or more processors, a memory for storing one or more programs, a plurality of programs, and a plurality of programs;
wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the aforementioned methods.
A readable storage medium storing a computer program which, when executed by a processor, implements the method described above.
According to the technical scheme provided by the invention, the total water vapor column data set inverted by the domestic satellite hyperspectral can be utilized to automatically identify the atmospheric river event, complicated image refinement processing is not required to be executed in the identification process, and the interference of other strong water vapor conveying events caused by non-atmospheric river is filtered through twice identification, so that the identification accuracy of the atmospheric river event is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of an atmospheric river identification method based on a domestic hyperspectral satellite, which is provided by the embodiment of the invention;
FIG. 2 is a schematic illustration of an atmospheric river event according to an embodiment of the present invention;
FIG. 3 is a schematic view of dividing an atmospheric river generating area according to an embodiment of the present invention;
FIG. 4 is a schematic diagram showing the comparison between the total amount of the domestic hyperspectral satellite water vapor column and the total amount of the American hyperspectral satellite water vapor column according to the embodiment of the invention;
FIG. 5 is a schematic illustration of calculating an atmospheric river axis provided by an embodiment of the present invention;
FIG. 6 is a schematic diagram of an atmospheric river identification system based on a domestic hyperspectral satellite according to an embodiment of the present invention;
Fig. 7 is a schematic diagram of a processing apparatus according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to fall within the scope of the invention.
The terms that may be used herein will first be described as follows:
The terms "comprises," "comprising," "includes," "including," "has," "having" or other similar referents are to be construed to cover a non-exclusive inclusion. For example, inclusion of a feature (e.g., a starting material, component, ingredient, carrier, dosage form, material, size, part, component, mechanism, apparatus, step, procedure, method, reaction condition, processing condition, parameter, algorithm, signal, data, product or article of manufacture, etc.) should be construed as including not only the feature explicitly recited, but also other features known in the art that are not explicitly recited.
The AAAA method provided by the present invention is described in detail below. What is not described in detail in the embodiments of the present invention belongs to the prior art known to those skilled in the art. The specific conditions are not noted in the examples of the present invention and are carried out according to the conditions conventional in the art or suggested by the manufacturer. The reagents or apparatus used in the examples of the present invention were conventional products commercially available without the manufacturer's knowledge.
Example 1
The embodiment of the invention provides an atmospheric river identification method based on a domestic hyperspectral satellite, which mainly comprises the following steps as shown in fig. 1:
step 1, acquiring a global water vapor column total data set inverted by utilizing a domestic satellite hyperspectrum, performing smoothing treatment on the global water vapor column total data set, removing tropical water vapor interference, and acquiring a corrected global water vapor column total data set.
The preferred embodiment of this step is as follows:
(1) And a smoothing processing section.
In the embodiment of the invention, the global water vapor column total data set is processed by interpolation technology to obtain the daily regular point data set, and then the daily regular point data set is smoothed by a median filter. Specific:
Because global water vapor column total data inverted by domestic hyperspectral satellites are influenced by factors such as orbit width, cloud cover, inversion failure and the like, the number of individual pixel points is lost, the global water vapor column total data is processed by interpolation technology, and a daily regular point data set of 0.25 degrees multiplied by 0.25 degrees is obtained. The life of the atmospheric river is 36 hours, so that the average value of the total amount of the vapor columns every 2 days is used as input data, and the defect of pixels caused by the width of a track can be overcome. And smoothing by using a median filter with the size of 15 multiplied by 15, reducing noise interference in the image, and filling the missing pixel points in a small range. To ensure data reliability, large-scale missing pixels are not processed. The specific values referred to herein are by way of example only and are not limiting, as the user may make appropriate adjustments according to actual conditions or experience in actual applications.
(2) And eliminating the Tropical water vapor interference part.
In the embodiment of the invention, N upward longitude grid points corresponding to each latitude grid point in the smoothed global water vapor column total amount data set are divided into J groups, each group comprises K longitude grid points, and the average value of the total water vapor column amount of each group is calculatedExpressed as:
wherein, Representing the total amount of water vapor columns of the kth longitude grid point of the jth group in the warp direction corresponding to the latitude grid point i.
Illustratively, n=1440, j=96, k=15 are provided.
Calculating the total amount average value of warp water vapor columns corresponding to latitude grid pointsExpressed as:
if the conditions are satisfied: And is also provided with J is not less than 1 and not more than J, the latitude lattice point i is positioned in the heated water vapor influence area, the total amount of the water vapor column corresponding to the latitude lattice point i is deleted, wherein,Representing eventsN represents a set water vapor column total amount threshold, and U represents a set ratio.
Illustratively, it is provided that U=2/3, n=2.
And step 2, carrying out preliminary identification of the atmospheric river event from the corrected global water vapor column total data set, and dividing an atmospheric river occurrence area if the preliminary identification is the atmospheric river event.
The preferred embodiment of this step is as follows:
(1) And (5) primarily identifying the atmospheric river event.
Considering that the northern hemisphere (/ southern hemisphere) atmospheric river is generally transmitted along the southwest-northeast (/ northwest-southeast) 45 DEG direction, the direction derivative perpendicular to the transmission direction of the atmospheric river is calculated for the corrected global water vapor column total data set, the direction derivative changes in the vertical direction, the process of changing the direction derivative into positive value and negative value is respectively called positive jump and negative jump, the condition that the direction derivative changes from positive value to negative value is judged in the vertical direction is judged, if the condition exists, the condition that the change trend that the water vapor column total in the vertical direction is increased first and then reduced is meant, the length and width of the covered area where the direction derivative changes from positive value to negative value are respectively a and b, and when a/b > P, the atmospheric river event is considered to exist, wherein P represents the set value.
Illustratively, p=2 is set. a. The value of b is determined according to the actual situation, and is not limited herein.
(2) Dividing the occurrence area of the atmospheric river.
If the atmospheric river event is initially identified, the position of the (a/2, b/2) coordinates of the coverage area from the first positive transition to the last negative transition is regarded as the center of the atmospheric river occurrence area, and the distance a is respectively extended from the center to 4 directions with 0 DEG, 90 DEG, 180 DEG and 270 DEG included angles with the forward east direction, and the area obtained after the extension is the atmospheric river event occurrence area.
The method is characterized by comprising the steps of (1) showing an atmospheric river event schematic diagram in fig. 2, and showing a partitioned atmospheric river occurrence region schematic diagram in fig. 3, wherein a and b respectively show the length and the width of a directional derivative transition region, and a square region with a side length of 2a is the partitioned atmospheric river occurrence region. In fig. 2 and 3, taking the northern hemisphere as an example, the atmospheric river is transmitted along the direction of 45 ° from southwest to northeast, the derivative of the direction in the direction of 135 ° from the forward direction (perpendicular to the direction of transmission of the atmospheric river) changes from a positive value to a negative value, generally, the atmospheric river axis is taken as a boundary, the right side is positive (corresponding to the white grid line area in the figure), and the left side is negative (corresponding to the white oblique line area in the figure).
And 3, determining a threshold value by utilizing the total quantity distribution of the water vapor columns in the atmosphere river generation area for years, and extracting an atmosphere river path from the atmosphere river generation area by utilizing the threshold value.
The preferred embodiment of this step is as follows:
(1) A first threshold is calculated.
In the occurrence area of the atmospheric river, counting the total quantity distribution of the vapor columns in the corresponding months of years when the atmospheric river event occurs, sorting from small to large, and taking the N1% quantile as a first threshold value c 1.
For example, n1=86 is set.
Considering that the running time of the domestic hyperspectral satellite is shorter, the total amount data of the years old water vapor column in the embodiment of the invention can come from a foreign hyperspectral satellite, and the total amount of the domestic hyperspectral satellite water vapor column is compared with the total amount of the American hyperspectral satellite water vapor column, as shown in fig. 4, the result shows that the correlation R of the total amount of the domestic hyperspectral satellite water vapor column and the total amount of the American hyperspectral satellite water vapor column is 0.983, and the inversion water vapor column total amount of the domestic hyperspectral satellite water vapor column is obviously related, so that the total amount of the American hyperspectral satellite water vapor column can replace the long-term distribution condition of the total amount of the domestic hyperspectral satellite water vapor column, in addition, x and y in fig. 4 respectively represent the total amount of the American hyperspectral satellite water vapor column and the total amount of the domestic hyperspectral satellite water vapor column, and in y=kx+b, when k=1 and b=0, the total amount data sets of the two water vapor columns are considered consistent.
(2) A second threshold is calculated.
In the generation area of the atmospheric river, counting total water vapor column distribution for years, sorting from small to large, and taking N2% fractional number as a second threshold value c 2.
Likewise, the water vapor column inventory data herein for years comes from foreign hyperspectral satellites, such as the U.S. hyperspectral satellites listed above.
Exemplary, set up: n2=80.
(3) And extracting an atmospheric river path.
Taking a larger value in c 1 and c 2 as a pixel point threshold value for any pixel point in the atmosphere river generation area, if the total amount of water vapor columns corresponding to the pixel points is higher than the threshold value, reserving the pixel points, otherwise, deleting the pixel points, traversing all the pixel points in the atmosphere river generation area, and forming an atmosphere river path by the reserved pixel points.
In the embodiment of the invention, the atmospheric river path is a path with a certain width, only the pixel points in the atmospheric river path are reserved, and the pixel points outside the atmospheric river path are deleted.
And 4, calculating an atmospheric river axis by using a pixel point corresponding to the total quantity of the highest water vapor column in the atmospheric river path, judging whether the atmospheric river axis belongs to a cyclone system or not by using the atmospheric river axis, if so, indicating that the preliminarily identified atmospheric river event is misjudgment, and if not, indicating that the finally identified atmospheric river event.
The preferred embodiment of this step is as follows:
(1) And calculating the axis of the atmospheric river.
And A, selecting a pixel point corresponding to the total quantity of the highest water vapor column in the atmospheric river path, and marking the selected pixel point as a point A.
And B, selecting a plurality of pixel points (for example, 9×9) around the point A, obtaining a plurality of pixel points (for example, 15) in the same category as the point A through nearest neighbor classification, obtaining a regression line through linear regression, and indicating the stepping direction by the regression line.
And C, counting line segments formed by pixel points with the total water vapor column quantity larger than ncm in the direction (ab direction) perpendicular to the stepping direction, and calculating mass centers of the line segments, wherein n represents a set water vapor column total quantity threshold value, and n=2 in an exemplary manner.
And D, moving the mass center to the next pixel point (for example, a point C and a point C') along the stepping direction, wherein the next pixel point is the pixel point which is closest to the mass center in the stepping direction by M km, taking the next pixel point as a point A, returning to the step B until the atmospheric river edge is reached, and connecting all the mass centers to obtain an atmospheric river axis, wherein M is a set distance value, and the setting is that M=50.
In the embodiment of the invention, the atmospheric river edge refers to the internal and external junction of the atmospheric river path, and when the current centroid moves to the next pixel point along the stepping direction, the current centroid can be considered to reach the atmospheric river edge without the nearest M km pixel point.
As shown in fig. 5, a flow of calculating the axis of the atmospheric river is shown, wherein different gray scales represent different total water vapor columns, point a represents the pixel point corresponding to the highest total water vapor column in the initial path of the atmospheric river,The stepping direction calculated by the nearest neighbor method is denoted, ab, cd, c ' D ', ef are perpendicular lines to the stepping direction, and D ' B-BD-DF are calculated atmospheric axis lines. The open dots (points C, C ', E) other than point A represent pixels closest to the last centroid in the stepping direction by 50km, which are used to determine the vertical line position (e.g., cd, c'd ', ef) in the stepping direction, and thus determine the centroid, and the triangle (points B, D, D', F) is the centroid on the vertical line. Point C, D in the figure is the same location point, representing the "step directionThe pixel point C 'which is closest to the centroid B by 50km is exactly coincident with the centroid D' on the vertical line cd determined according to the pixel point C, and the point E, F is the same. The centroid F, C' in fig. 5 continues to move along the respective step direction, and the above steps are repeated until a pixel is not found about 50km away in the step direction when the particle moves to the next pixel along the step direction, and the particle is taken as the endpoint of the atmospheric axis.
(2) The cyclone effect is filtered.
Considering that a part of the cyclone system can be misjudged as an atmospheric river event, judging whether the atmospheric river event belongs to the cyclone system or not by utilizing the atmospheric river axis, specifically, dividing the atmospheric river axis into a plurality of parts on average, respectively calculating the included angle between the end point and the starting point of each part, and if the included angle is larger than 90 degrees, the atmospheric river event belongs to the cyclone system, and the preliminary identification is indicated as misjudgment and needs to be abandoned. Otherwise, it is indicated that the atmospheric river event is ultimately identified.
After the final identification of the atmospheric river event, the following work can also be performed:
(1) And determining the width of the atmospheric river.
And calculating the width of the atmospheric river by combining the area covered by the atmospheric river path and the axial length of the atmospheric river, wherein the area covered by the atmospheric river path is denoted as S, the axial length of the atmospheric river is denoted as L, and the width W=S/L of the atmospheric river.
(2) And judging the landing point of the atmospheric river.
To determine if the atmospheric river event extends to a sea-land boundary, the atmospheric river path may be overlapped with the global sea Liu Yanmo, if an intersection exists, the atmospheric river event is considered to be landing, and the intersection is marked as a landing point.
Example two
The invention also provides an atmospheric river identification system based on the domestic hyperspectral satellite, which is mainly realized based on the method provided by the embodiment, as shown in fig. 6, and mainly comprises the following steps:
the data acquisition and correction unit is used for acquiring a global water vapor column total data set inverted by utilizing the hyperspectral of the domestic satellite, carrying out smoothing treatment on the global water vapor column total data set and removing tropical water vapor interference to obtain a corrected global water vapor column total data set;
The preliminary identification and region division unit is used for carrying out preliminary identification of the atmospheric river event from the corrected global water vapor column total data set, and if the preliminary identification is the atmospheric river event, the atmospheric river occurrence region is divided;
the atmospheric river path extraction unit is used for determining a threshold value by utilizing the total quantity distribution of the vapor columns in the atmosphere river generation area for years, and extracting an atmospheric river path from the atmosphere river generation area by utilizing the threshold value;
The secondary atmospheric river event identification unit is used for calculating an atmospheric river axis by using pixel points corresponding to the total quantity of the highest water vapor columns in the atmospheric river path, judging whether the atmospheric river axis belongs to a cyclone system or not by using the atmospheric river axis, if the atmospheric river axis belongs to the cyclone system, indicating that the primarily identified atmospheric river event is misjudgment, and if the atmospheric river event does not belong to the cyclone system, indicating that the finally identified atmospheric river event.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional modules is illustrated, and in practical application, the above-described functional allocation may be performed by different functional modules according to needs, i.e. the internal structure of the system is divided into different functional modules to perform all or part of the functions described above.
Example III
The invention also provides processing equipment, as shown in fig. 7, which mainly comprises one or more processors, a memory, and a control unit, wherein the memory is used for storing one or more programs, and the one or more programs are executed by the one or more processors, so that the one or more processors realize the method provided by the previous embodiment.
Further, the processing device further comprises at least one input device and at least one output device, and in the processing device, the processor, the memory, the input device and the output device are connected through buses.
In the embodiment of the present invention, specific types of the memory, the input device and the output device are not limited, for example:
The input device can be a touch screen, an image acquisition device, a physical key or a mouse and the like;
the output device may be a display terminal;
The memory may be random access memory (Random Access Memory, RAM) or non-volatile memory (non-volatile memory), such as disk memory.
Example IV
The invention also provides a readable storage medium storing a computer program which, when executed by a processor, implements the method provided by the foregoing embodiments.
The readable storage medium according to the embodiment of the present invention may be provided as a computer readable storage medium in the aforementioned processing apparatus, for example, as a memory in the processing apparatus. The readable storage medium may be any of various media capable of storing a program code, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a magnetic disk, and an optical disk.
The foregoing is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions easily contemplated by those skilled in the art within the scope of the present invention should be included in the scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.
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|---|---|---|---|---|
| CN106950574A (en) * | 2017-04-14 | 2017-07-14 | 北京市环境保护监测中心 | The remote sensing measuring method and device of gray haze total amount in a kind of air |
| CN109086540A (en) * | 2018-08-14 | 2018-12-25 | 中国科学院遥感与数字地球研究所 | A kind of method and device constructing Forecasting of Tropical Cyclone model |
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| CN109086540A (en) * | 2018-08-14 | 2018-12-25 | 中国科学院遥感与数字地球研究所 | A kind of method and device constructing Forecasting of Tropical Cyclone model |
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