A method for measuring the volcanic ash diffusion process based on remote sensing satellite images

Abstract

The present invention discloses a method for measuring the volcanic ash diffusion process based on remote sensing satellite images, including: observing a volcano using a remote sensing satellite to obtain multiple frames of volcanic eruption images; performing filtering processing on each frame of volcanic eruption images to obtain corresponding filtered images; obtaining the image edge information corresponding to each frame of filtered image; calculating the corresponding volcanic ash diffusion range using the image edge information obtained for each frame; obtaining the energy centroid of the volcanic ash mass for each frame of filtered image; determining the volcanic ash diffusion trend using the volcanic ash diffusion ranges obtained from multiple frames; and determining the volcanic ash diffusion direction using the energy centroids obtained from multiple frames. Through edge detection, the present invention can complete the judgment of the volcanic ash diffusion range, and through image centroid extraction, it can judge the movement direction of the volcanic ash. Therefore, it can efficiently and accurately measure the volcanic ash diffusion process using remote sensing satellite images to further analyze its impact on the environment, etc.

Description

Technical Field

[0001] The present invention belongs to the field of aerospace measurement and control, and particularly relates to a method for measuring the volcanic ash diffusion process based on remote sensing satellite images. Background Art

[0002] The analysis of the impact and intensity of volcanic eruptions is an important direction in the fields of geology and environmental research. Among them, volcanic ash is a hazard with a relatively large affected range after a volcanic eruption, which can pollute water sources and air, have an adverse impact on the growth of crops, and at the same time affect air route communication and global temperature, etc.

[0003] Due to the characteristics of short repeat cycle and good observation effect of remote sensing satellites, they have been widely used in fields such as national land census and mapping. Therefore, how to use remote sensing satellite images to efficiently and accurately measure the volcanic ash diffusion process is a technical direction worthy of research. Summary of the Invention

[0004] In order to solve the above problems existing in the prior art, the present invention provides a method for measuring the volcanic ash diffusion process based on remote sensing satellite images. The technical problems to be solved by the present invention are realized through the following technical solutions:

[0005] Use a remote sensing satellite to observe a volcano and obtain multiple frames of volcanic eruption images;

[0006] Perform filtering processing on each frame of volcanic eruption image to obtain the corresponding filtered image;

[0007] Obtain the image edge information corresponding to each frame of filtered image; and calculate the corresponding volcanic ash diffusion range using the image edge information obtained for each frame;

[0008] Obtain the energy centroid of the volcanic ash cluster for each frame of filtered image;

[0009] Determine the volcanic ash diffusion trend using the volcanic ash diffusion ranges obtained from multiple frames; and determine the volcanic ash diffusion direction using the energy centroids obtained from multiple frames.

[0010] In an embodiment of the present invention, before the step of using a remote sensing satellite to observe a volcano and obtain multiple frames of volcanic eruption images, the method further includes:

[0011] Calculate the payload pointing angle of the remote sensing satellite for observing the target area, and when the target area is visible, adjust the payload pointing angle for observation and positioning; wherein, the target area includes the volcano.

[0012] In an embodiment of the present invention, the calculation of the payload pointing angle of the remote sensing satellite for observing the target area includes:

[0013] According to the two-line elements of the remote sensing satellite, the position of the remote sensing satellite in the geocentric inertial coordinate system is obtained by using the STK software in combination with the SGP4 model ;

[0014] Obtain the central point position of the target area in the geocentric inertial coordinate system ;

[0015] According to the position of the remote sensing satellite in the geocentric inertial coordinate system and the central point position of the target area , calculate the viewing vector of the remote sensing satellite position ;

[0016] Calculate the viewing vector between the remote sensing satellite position and the geocenter ;

[0017] According to the velocities of the remote sensing satellite in three directions , and , calculate the motion direction vector of the remote sensing satellite ;

[0018] According to the viewing vector of the remote sensing satellite position , the viewing vector between the remote sensing satellite position and the geocenter and the motion direction vector of the remote sensing satellite , calculate the east-west payload pointing angle and the north-south payload pointing angle of the remote sensing satellite observing the target area as:

[0019] ;

[0020] wherein, represents the east-west payload pointing angle of the remote sensing satellite observing the target area; represents the north-south payload pointing angle of the remote sensing satellite observing the target area.

[0021] In an embodiment of the present invention, the filtering process for each frame of volcanic eruption image to obtain the corresponding filtered image includes:

[0022] Perform Gaussian filtering on each frame of volcanic eruption image to obtain the corresponding filtered image ;

[0023] wherein, ; represents the Gaussian filtering function; ; In the Gaussian filtering function, represents the pixel point in; represents the noise.

[0024] In an embodiment of the present invention, obtaining the image edge information corresponding to each filtered image includes:

[0025] For each filtered image, by calculating the first derivative of the filtered image, the corresponding gradient vector is obtained: ; where and represent the first-order partial derivatives in the direction and the direction;

[0026] Using the gradient vector corresponding to the filtered image, solve the gradient magnitude at the pixel point of the filtered image as ; calculate the direction angle at the pixel point of the filtered image as ; and determine that the initial image edge information of the filtered image is the maximum value point of the gradient found along the direction of this direction angle: ;

[0027] Based on the obtained initial image edge information , use the double-threshold algorithm to determine the pixel edge information of the pixel point , and obtain the image edge information corresponding to the filtered image from the pixel edge information obtained by traversing all pixel points .

[0028] In an embodiment of the present invention, the based on the obtained initial image edge information , using the double-threshold algorithm to determine the pixel edge information of the pixel point includes:

[0029] If the initial image edge information is less than the low threshold preset by the double-threshold algorithm, then eliminate the initial image edge information ;

[0030] If the initial image edge information is greater than the high threshold preset by the double-threshold algorithm, then retain the initial image edge information and define it as a strong edge, and use the initial image edge information as the pixel edge information of the pixel point ;

[0031] If the initial image edge information satisfies , then use the initial image edge information Define it as a weak edge and judge the pixel point Among the 8 neighboring pixels of the pixel point, whether there is a pixel point that meets the definition of a strong edge. If so, retain the weak edge as the true edge and use it as the pixel point The pixel edge information.

[0032] In an embodiment of the present invention, the calculation formula used to calculate the corresponding volcanic ash diffusion range using the image edge information obtained from each frame includes:

[0033] ;

[0034] Wherein, Represents the volcanic ash diffusion range.

[0035] In an embodiment of the present invention, the calculation formula used to obtain the energy centroid of the volcanic ash mass for each filtered image includes:

[0036] ;

[0037] Wherein, Represents the coordinates of the energy centroid; Represents the volcanic ash mass as the target.

[0038] In an embodiment of the present invention, the calculation formula used to determine the volcanic ash diffusion trend using the volcanic ash diffusion ranges obtained from multiple frames includes:

[0039] ;

[0040] Wherein, Represents the volcanic ash diffusion trend obtained from two adjacent frames; Represents the volcanic ash diffusion range obtained from the earlier frame among two adjacent frames; Represents the volcanic ash diffusion range obtained from the later frame among two adjacent frames.

[0041] In an embodiment of the present invention, the method for determining the volcanic ash diffusion direction using the energy centroids obtained from multiple frames includes:

[0042] Connect the energy centroids obtained from multiple frames in sequence to obtain a centroid connection line, and determine the volcanic ash diffusion direction according to the direction of the centroid connection line.

[0043] The beneficial effects of the present invention:

[0044] In the solution provided by the embodiments of the present invention, first, multiple frames of volcanic eruption images are obtained by using a remote sensing satellite; secondly, each frame of volcanic eruption image is filtered to obtain the corresponding filtered image; next, the image edge information corresponding to each frame of filtered image is obtained; and the corresponding volcanic ash diffusion range is calculated by using the image edge information obtained for each frame; then, the energy centroid of the volcanic ash mass is obtained for each frame of filtered image; finally, the volcanic ash diffusion trend is determined by using the volcanic ash diffusion ranges obtained from multiple frames; and the volcanic ash diffusion direction is determined by using the energy centroids obtained from multiple frames. It can be seen that through edge detection, the embodiments of the present invention can complete the judgment of the volcanic ash diffusion range, and through image centroid extraction, the movement direction of the volcanic ash can be judged. Therefore, the remote sensing satellite images can be used to efficiently and accurately measure the volcanic ash diffusion process to further analyze its impact on the environment, etc. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 It is a schematic flowchart of a method for measuring the volcanic ash diffusion process based on remote sensing satellite images provided by the embodiments of the present invention;

[0046] Figure 2 Multiple frames of volcanic eruption images obtained by the embodiments of the present invention;

[0047] Figure 3 The image edge information corresponding to each frame of filtered image in the embodiments of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0048] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0049] Currently, as the role of remote sensing satellites is becoming more and more extensive, the volcanic eruption process can be detected and mastered during their flight. And remote sensing satellites have the characteristics of a short repetition period and good observation effect. Therefore, the embodiments of the present invention consider that remote sensing satellites can be used to conduct key monitoring of volcanic eruption areas through observation planning. Specifically, for volcanic eruptions, regular return visits can be made through remote sensing satellites to summarize the laws of volcanic eruptions and volcanic ash changes, and by analyzing remote sensing satellite images, the laws of volcanic ash diffusion and movement can be summarized to provide basic services for geological and environmental research.

[0050] As Figure 1 shown, a method for measuring the volcanic ash diffusion process based on remote sensing satellite images provided by the embodiments of the present invention may include the following steps:

[0051] S1. Observe the volcano using a remote sensing satellite to obtain multiple frames of volcanic eruption images;

[0052] It can be understood that each frame of the volcanic eruption image is a remote sensing satellite image during the volcanic eruption.

[0053] Among them, before S1, the method further includes:

[0054] Calculate the payload pointing angle of the remote sensing satellite observing the target area, and when the target area is visible, adjust the payload pointing angle for observation and positioning; wherein, the target area includes the volcano, that is, the volcano to be measured.

[0055] Specifically, calculating the payload pointing angle of the remote sensing satellite observing the target area may include the following steps:

[0056] 1) According to the two-line elements of the remote sensing satellite, use STK software in combination with the SGP4 model to obtain the position of the remote sensing satellite in the geocentric inertial coordinate system ;

[0057] In the embodiments of the present invention, the volcanic eruption is observed in combination with the operating orbit of the remote sensing satellite. Among them, STK software is the abbreviation of Satellite Tool Kit software, which is a leading commercial analysis software in the aerospace field developed by Analytical Graphics Company of the United States. The full name of the SGP4 model is Simplified Deep Space Perturbations, which means a simplified deep space perturbation model. Using this model, the satellite position at each moment can be obtained by orbit extrapolation.

[0058] For the specific implementation process of this step, please understand it in combination with relevant technologies and no detailed description will be given here.

[0059] 2) Obtain the central point position of the target area in the geocentric inertial coordinate system ;

[0060] Among them, the central point position of the target area in the geocentric inertial coordinate system is known in advance, and the corresponding coordinate values can be directly obtained.

[0061] 3) According to the position of the remote sensing satellite in the geocentric inertial coordinate system and the central point position of the target area , calculate the position visual vector of the remote sensing satellite ;

[0062] It can be understood that the position visual vector of the remote sensing satellite can be calculated at each moment .

[0063] 4) Calculate the position of the remote sensing satellite and the geocentric visual vector ;

[0064] Similarly, the position of the remote sensing satellite and the geocentric viewing vector can be calculated at each moment. .

[0065] 5) Calculate the motion direction vector of the remote sensing satellite according to the velocities of the remote sensing satellite in three directions , and ; , and , and calculate the motion direction vector of the remote sensing satellite. ;

[0066] Similarly, at each moment, using the velocities of the remote sensing satellite in three directions , and at that moment, the motion direction vector of the remote sensing satellite at that moment can be calculated. , and , the motion direction vector of the remote sensing satellite at that moment can be calculated. .

[0067] 6) Calculate the east-west payload pointing angle and the north-south payload pointing angle of the remote sensing satellite observing the target area according to the position viewing vector of the remote sensing satellite, the position of the remote sensing satellite and the geocentric viewing vector and the motion direction vector of the remote sensing satellite as: , the position of the remote sensing satellite and the geocentric viewing vector and the motion direction vector of the remote sensing satellite, the east-west payload pointing angle and the north-south payload pointing angle of the remote sensing satellite observing the target area are calculated as:

[0068] ;

[0069] wherein, represents the east-west payload pointing angle of the remote sensing satellite observing the target area; represents the north-south payload pointing angle of the remote sensing satellite observing the target area.

[0070] It can be understood that after calculating the payload pointing angle of the remote sensing satellite observing the target area, when the target area is visible, the payload pointing angle can be adjusted to realize the observation of the target area and obtain multiple frames of volcanic eruption images.

[0071] S2. Perform filtering processing on each frame of volcanic eruption image to obtain corresponding filtered images;

[0072] Performing filtering processing on each frame of volcanic eruption image is to remove noise and better retain edge information.

[0073] In an optional implementation manner, S2 may include:

[0074] Perform Gaussian filtering processing on each frame of volcanic eruption image to obtain corresponding filtered images ;

[0075] wherein, ; represents the Gaussian filtering function; ; in the Gaussian filtering function represents the pixel in represents noise.

[0076] Regarding the process of Gaussian filtering, please understand it in combination with related technologies and no detailed description will be given here.

[0077] S3. Obtain the image edge information corresponding to each frame of the filtered image; and calculate the corresponding volcanic ash diffusion range by using the image edge information obtained from each frame;

[0078] Obtaining the image edge information corresponding to each frame of the filtered image, that is, the trajectory edge of the volcanic eruption image, can be realized by using an edge detection algorithm.

[0079] In an optional implementation manner, the obtaining of the image edge information corresponding to each frame of the filtered image includes:

[0080] A1. For each frame of the filtered image, obtain the corresponding gradient vector by calculating the first derivative of the filtered image of this frame: ;

[0081] where and represent the first-order partial derivatives in the direction and the direction.

[0082] A2. Use the gradient vector corresponding to the filtered image of this frame to solve the gradient amplitude of the filtered image of this frame at the pixel point is ; calculate the direction angle of the filtered image of this frame at the pixel point is ; and determine that the initial image edge information of the filtered image of this frame is the maximum value point of the gradient found along the direction angle direction: ;

[0083] A3. Based on the obtained initial image edge information , use the double-threshold algorithm to determine the pixel edge information of the pixel point , and obtain the image edge information corresponding to the filtered image of this frame from the pixel edge information obtained by traversing all pixel points .

[0084] In an optional implementation manner, based on the obtained initial image edge information , using the double-threshold algorithm to determine the pixel edge information of the pixel point may include:

[0085] ① If the edge information of the initial image is less than the low threshold preset by the double-threshold algorithm , then the edge information of the initial image is removed ;

[0086] In the embodiment of the present invention, the double-threshold algorithm is used to determine real and potential edges, specifically using the low threshold and the high threshold to implement. . and can be reasonably set according to needs and are not limited here.

[0087] Specifically, if the edge information of the initial image is less than the low threshold preset by the double-threshold algorithm , then it is removed.

[0088] ② If the edge information of the initial image is greater than the high threshold preset by the double-threshold algorithm , then the edge information of the initial image is retained and defined as a strong edge, and the edge information of the initial image is used as the pixel edge information of the pixel point ;

[0089] ③ If the edge information of the initial image meets , then the edge information of the initial image is defined as a weak edge, and it is judged whether there is a pixel point in the 8-neighbor pixels of the pixel point that meets the definition of a strong edge. If so, the weak edge is retained as a real edge and used as the pixel edge information of the pixel point . It should be noted that if none of the 8-neighbor pixels of the pixel point meets the definition of a strong edge, then the edge point is discarded.

[0090] Among them, the definition of a strong edge can be seen in the description in ②. It can be understood that usually after setting appropriate thresholds for the algorithm test, those with the edge information of the initial image higher than are definitely edge points, those between and may or may not be, and the double-threshold method will have a better processing effect when the set thresholds are appropriate, and can accurately determine the pixel edge information of the pixel point .

[0091] After obtaining the pixel edge information of all pixel points in the above manner, the image edge information corresponding to the filtered image of this frame can be obtained , please refer to Figure 2 and Figure 3 for understanding. Figure 2 These are multiple frames of volcanic eruption images obtained in the embodiments of the present invention. Figure 3 These are the image edge information corresponding to each frame of the filtered image.

[0092] After obtaining the trajectory edge of the volcanic eruption image in S3 of the embodiments of the present invention, on this basis, the volcanic ash diffusion range can be calculated through the edge of the volcanic eruption image, that is, the volcanic ash action range is analyzed by combining the image edge information.

[0093] In an optional embodiment, the calculation formula used to calculate the corresponding volcanic ash diffusion range by using the image edge information obtained from each frame includes:

[0094] ;

[0095] Wherein, represents the volcanic ash diffusion range, that is, the volcanic ash action range. It can be understood that this formula represents integral to solve the area.

[0096] Therefore, for each frame, the corresponding volcanic ash diffusion range can be calculated according to the above formula. .

[0097] S4. Obtain the energy centroid of the volcanic ash mass for each frame of the filtered image;

[0098] This step can be executed after S2. In an optional embodiment, the calculation formula used to obtain the energy centroid of the volcanic ash mass for each frame of the filtered image includes:

[0099] ;

[0100] Wherein, represents the coordinates of the energy centroid; represents the volcanic ash mass as the target. It can be understood that the energy centroid of the volcanic ash mass is the average value of all points.

[0101] S5. Determine the volcanic ash diffusion trend by using the volcanic ash diffusion ranges obtained from multiple frames; and determine the volcanic ash diffusion direction by using the energy centroids obtained from multiple frames.

[0102] In an optional embodiment, the calculation formula used to determine the volcanic ash diffusion trend by using the volcanic ash diffusion ranges obtained from multiple frames includes:

[0103] ;

[0104] Wherein, represents the volcanic ash diffusion trend obtained from two adjacent frames; represents the volcanic ash diffusion range obtained from the prior frame in two adjacent frames; represents the volcanic ash diffusion range obtained from the subsequent frame in two adjacent frames.

[0105] Therefore, one can be obtained from two adjacent frames. Then, (number of frames - 1) can be obtained from multiple frames of volcanic eruption images.

[0106] In an optional implementation manner, determining the volcanic ash diffusion direction by using the energy centroids obtained from multiple frames includes:

[0107] Connect the energy centroids obtained from multiple frames in sequence to obtain a centroid connection line, and determine the volcanic ash diffusion direction according to the direction of the centroid connection line.

[0108] It can be understood that the centroid connection line obtained by connecting the energy centroids in sequence may be in a zigzag shape, and each line segment is the connection line segment of the energy centroids at two adjacent moments. Therefore, the diffusion direction of volcanic ash at corresponding moments can be determined by using the directions of the connection line segments between different moments, and the change trend of the volcanic ash diffusion direction at all moments can be statistically analyzed to obtain its movement trend, etc.

[0109] In the solution provided by the embodiments of the present invention, first, multiple frames of volcanic eruption images are obtained by using a remote sensing satellite; secondly, each frame of volcanic eruption image is filtered to obtain a corresponding filtered image; next, the image edge information corresponding to each frame of filtered image is obtained; and the volcanic ash diffusion range is calculated by using the image edge information obtained from each frame; then, the energy centroid of the volcanic ash group is obtained for each frame of filtered image; finally, the volcanic ash diffusion trend is determined by using the volcanic ash diffusion ranges obtained from multiple frames; and the volcanic ash diffusion direction is determined by using the energy centroids obtained from multiple frames. It can be seen that through edge detection, the embodiments of the present invention can complete the judgment of the volcanic ash diffusion range, and through image centroid extraction, the movement direction of volcanic ash can be judged. Therefore, the diffusion process of volcanic ash can be efficiently and accurately measured by using remote sensing satellite images to further analyze its impact on the environment, etc.

[0110] The above are only the preferred embodiments of the present invention, and are not used to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention are all included in the protection scope of the present invention.

Claims

1. A method for measuring the volcanic ash diffusion process based on remote sensing satellite images, characterized in that Including: Observing a volcano using a remote sensing satellite to obtain multiple frames of volcanic eruption images; Performing filtering processing on each frame of the volcanic eruption images to obtain corresponding filtered images; Obtaining the image edge information corresponding to each frame of the filtered image; And calculating the corresponding volcanic ash diffusion range using the image edge information obtained for each frame; Obtaining the energy centroid of the volcanic ash cluster for each frame of the filtered image; wherein, the calculation formula used when obtaining the energy centroid of the volcanic ash cluster for each frame of the filtered image includes: Among them, (x c , y c ) represents the coordinates of the energy centroid; T represents the volcanic ash mass as the target; Ig(x, y) represents the corresponding filtered image obtained after filtering the volcanic eruption image I(x, y); (x, y) represents the coordinates in the image; Determining the volcanic ash diffusion trend using the volcanic ash diffusion ranges obtained from multiple frames; and determining the volcanic ash diffusion direction using the energy centroids obtained from multiple frames.

2. The measurement method of the volcanic ash diffusion process based on remote sensing satellite images according to claim 1, wherein, Before the step of observing a volcano using a remote sensing satellite to obtain multiple frames of volcanic eruption images, the method further includes: Calculating the load pointing angle of the remote sensing satellite for observing the target area, and adjusting the load pointing angle for observation and positioning when the target area is visible; wherein, the target area includes the volcano.

3. The measurement method of the volcanic ash diffusion process based on remote sensing satellite images according to claim 2, characterized in that, The calculating the load pointing angle of the remote sensing satellite for observing the target area includes: According to the two-line elements of the remote sensing satellite, the position of the remote sensing satellite in the geocentric inertial coordinate system (x s , y s , z s ) is obtained by using the STK software in combination with the SGP4 model; Obtaining the central point position (x0, y0, z0) of the target area in the geocentric inertial coordinate system; According to the position (x s , y s , z s ) of the remote sensing satellite in the geocentric inertial coordinate system and the central point position (x0, y0, z0) of the target area, calculate the viewing vector of the remote sensing satellite position Calculate the position of the remote sensing satellite and the geocentric visual vector According to the velocities V of the remote sensing satellite in three directions x , V y and V z , calculate the motion direction vector of the remote sensing satellite According to the view vector of the remote sensing satellite position The view vector between the remote sensing satellite position and the earth center And the motion direction vector of the remote sensing satellite Calculate the east-west load pointing angle and north-south load pointing angle of the remote sensing satellite observing the target area as follows: Wherein, A represents the east-west load pointing angle of the remote sensing satellite for observing the target area; E represents the north-south load pointing angle of the remote sensing satellite for observing the target area.

4. The measurement method of the volcanic ash diffusion process based on remote sensing satellite images according to claim 1, characterized in that, The performing filtering processing on each frame of the volcanic eruption images to obtain corresponding filtered images includes: Performing Gaussian filtering processing on each frame of the volcanic eruption image I(x, y) to obtain the corresponding filtered image Ig(x, y); Wherein, Ig(x, y) = I(x, y) * G(x, y, σ); G(x, y, σ) represents the Gaussian filtering function; In the Gaussian filtering function, (x, y) represents the pixel points in I(x, y); σ represents the noise.

5. The measurement method of the volcanic ash diffusion process based on remote sensing satellite images according to claim 4, characterized in that, The obtaining the image edge information corresponding to each frame of the filtered image includes: For each filtered image frame, the corresponding gradient vector is obtained by calculating the first derivative of the filtered image frame: where G x (x, y, σ) and G y (x, y, σ) represent the first partial derivatives of G(x, y, σ) in the x - direction and y - direction; Using the gradient vector corresponding to the image after frame filtering, solve for the gradient magnitude of the image after frame filtering at the pixel point (x, y) as Calculate the direction angle of the image after frame filtering at the pixel point (x, y) as And determine the initial image edge information I of the image after frame filtering xy (x, y) is the maximum value point of the gradient found along the direction of this direction angle: Based on the obtained initial image edge information I xy (x, y), the pixel edge information of the pixel point (x, y) is determined by using the double-threshold algorithm, and the image edge information I corresponding to the filtered image of this frame is obtained from the pixel edge information obtained by traversing all pixel points e (x, y).

6. The method for measuring the volcanic ash diffusion process based on remote sensing satellite images according to claim 5, characterized in that, Based on the obtained initial image edge information I xy (x, y), the edge information of the pixel point (x, y) is determined by using a double-threshold algorithm, including: If the initial image edge information I xy (x, y) is less than the low threshold preset by the double threshold algorithm then eliminate the initial image edge information I xy (x, y); If the initial image edge information I xy (x, y) is greater than the high threshold preset by the double-threshold algorithm then retain the initial image edge information I xy (x, y) and define it as a strong edge, and use the initial image edge information I xy (x, y) as the pixel point edge information of the pixel point (x, y); If the initial image edge information I xy (x, y) satisfies then the initial image edge information I xy (x, y) is defined as a weak edge, and it is determined whether there is a pixel point among the 8 neighboring pixels of the pixel point (x, y) that satisfies the strong edge definition. If so, the weak edge is retained as the true edge and used as the pixel edge information of the pixel point (x, y).

7. The measurement method for the volcanic ash diffusion process based on remote sensing satellite images according to claim 6, characterized in that The calculation formula used when calculating the corresponding volcanic ash diffusion range using the image edge information obtained for each frame includes: Wherein, S represents the volcanic ash diffusion range.

8. The method for measuring the volcanic ash diffusion process based on remote sensing satellite images according to claim 7, wherein The calculation formula used when determining the volcanic ash diffusion trend using the volcanic ash diffusion ranges obtained from multiple frames includes: ΔS = S1 - S2; Wherein, ΔS represents the volcanic ash diffusion trend obtained from two adjacent frames; S1 represents the volcanic ash diffusion range obtained from the prior frame among two adjacent frames; S2 represents the volcanic ash diffusion range obtained from the subsequent frame among two adjacent frames.

9. The measurement method of the volcanic ash diffusion process based on remote sensing satellite images according to claim 4, characterized in that, The determining the volcanic ash diffusion direction using the energy centroids obtained from multiple frames includes: Sequentially connecting the energy centroids obtained from multiple frames to obtain a centroid connection line, and determining the volcanic ash diffusion direction according to the direction of the centroid connection line.

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