CN117590397B - Coastal zone change detection method based on SAR image and electronic equipment - Google Patents
Coastal zone change detection method based on SAR image and electronic equipment Download PDFInfo
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Abstract
The invention provides a coastal zone change detection method and electronic equipment based on SAR images, which relate to the field of coastal zone change detection and comprise the following steps: acquiring SAR images P k and wind speeds V k corresponding to a target monitoring area at the current calculation time k; if V k‑1≥V0,Vk is more than or equal to V0, taking P k‑1 as a current first comparison image and P k as a current second comparison image; if V k‑1＜V0,Vk is more than or equal to V0, removing the corresponding water body areas in P k and P k‑1 by using the water body area in P k‑1 as a mask area, taking the image P k‑1 with the water body area removed as a current first comparison image, and taking the image P k with the water body area removed as a current second comparison image; and acquiring a change area of the current second comparison image relative to the current first comparison image as a change area of P k relative to P k‑1. The method and the device can improve the accuracy of coastal zone change detection.
Description
Technical Field
The invention relates to the field of coastal zone change detection, in particular to a coastal zone change detection method based on SAR images and electronic equipment.
Background
The coastal zone is the area where the ocean system and the land system are connected and interacted, and is an important homeland resource of the coastal country. The coastal zone has important roles in ocean development or ecological protection, the coastal zone has rich resources, and along with the social development, the urban process is also gradually accelerated, and the development problem of the coastal zone is also gradually highlighted. The illicit reclamation sea development or other offshore development processes may cause irreversible damage processes to both the ecological landscape and natural resources along the shore, thus necessitating time-series monitoring of the coast.
The periodic monitoring method comprises remote sensing technology monitoring, ground periodic investigation monitoring and the like, wherein the periodic monitoring method is limited by a special geographic position of a coastal zone, huge manpower and material resource participation is required for carrying out ground field investigation work, and the investigation cost is too high. The remote sensing technology, including the development of aerospace remote sensing, can realize regional land surface land utilization change monitoring, and the data acquisition process reduces possible artificial interference and simultaneously reduces the risk of data acquisition. The remote sensing image is used for identifying vegetation, water and construction land, and provides technology and data guarantee for change monitoring.
The weather conditions of the coastal zone are changeable and are influenced by a sea and land system, cloud cover along the coast is more, the sea surface wind speed is larger and other weather conditions, and the remote sensing data acquisition monitored by the coastal zone is influenced to a certain extent. The cloud cover affects the effective acquisition of the optical satellite data, and the excessive wind speed affects the normalized back scattering section intensity (NormalRadar Cross Section:NRCS) of the synthetic aperture radar (SYNTHETIC APERTURE RADAR:SAR) image. Particularly, the surface of the water body is broken, the roughness is increased, the NRCS is enhanced, the water body image characteristics are similar to those of bare land or vegetation, and erroneous judgment in the image detection process can be caused.
Disclosure of Invention
Aiming at the technical problems, the invention adopts the following technical scheme:
According to a first aspect of the present invention, there is provided a coastal zone change detection method based on SAR images, the method comprising the steps of:
s100, SAR images P k and wind speeds V k corresponding to the target monitoring area at the current calculation time k are obtained; the target monitoring area is an area in a target coastal zone.
S200, if V k-1≥V0,Vk is more than or equal to V0, taking the SAR image P k-1 corresponding to the previous calculation time k-1 as a current first comparison image, taking P k as a current second comparison image, and executing S400; if V k-1＜V0,Vk is greater than or equal to V0, executing S300; v k-1 is the wind speed corresponding to the last calculation time k-1 of the target monitoring area; v0 is a set wind speed threshold.
S300, setting the pixel values corresponding to the water body areas in P k-1 and P k to be the same pixel value, taking P k-1 with the pixel value as a current first comparison image, and taking P k with the pixel value as a current second comparison image; s400 is performed.
S400, obtaining a change area of the current second comparison image relative to the change of the current first comparison image as a change area of P k relative to the change of P k-1; s100 is performed.
According to a second aspect of the present invention, there is provided an electronic device comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being arranged to perform the method according to the first aspect of the invention.
The invention has at least the following beneficial effects:
According to the embodiment of the invention, the SAR image is adopted to detect the change of the coastal zone, so that effective data can be stably acquired, uncertainty of unfavorable weather on data acquisition is reduced, and a data source is stable and reliable. In addition, when the wind speed of the target monitoring area is larger than the wind speed threshold value, the water body area in the low wind speed image is used as a mask area to remove the water body area in the front and rear images, and then the two-stage images with the water body area removed are subjected to change detection, so that the pseudo-change area caused by the wind speed can be reduced, and the change detection result is more accurate.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the invention or to delineate the scope of the invention. Other features of the present invention will become apparent from the description that follows.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a timing diagram of the strength of the backscattering of an offshore surface in accordance with one embodiment of the invention;
FIGS. 2a and 2b are schematic views of images at high and low wind speeds, respectively;
FIG. 3 is a graph of wind speed versus backscatter intensity for an embodiment of the present invention;
Fig. 4 is a flowchart of a coastal zone change detection method based on SAR images 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 completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. 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.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.
It should be noted that some exemplary embodiments are described as a process or a method depicted as a flowchart. Although a flowchart depicts steps as a sequential process, many of the steps may be implemented in parallel, concurrently, or with other steps. Furthermore, the order of the steps may be rearranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figures. The processes may correspond to methods, functions, procedures, subroutines, and the like.
The inventor of the invention explores the imaging of wind speed on water body in the research process of coastal zone change detection. The method specifically comprises the following steps:
First, the present invention selects an offshore region of interest (the region of interest is the region shown by the white boxes in fig. 2a and 2 b) near a designated coast, and a backscatter intensity variation timing chart for a designated year is plotted as shown in fig. 1. Wherein, the maximum value of the scattering intensity is-14.58 dB, the minimum value is-25.35 dB, and the average value is-19.53 dB. Wherein the maximum and minimum differ by more than 10dB.
Next, two-phase images with larger backscattering of the sea surface water body are selected for comparison, the features of the SAR image water body are shown in fig. 2a and 2b, fig. 2b is an image at a low wind speed, and fig. 2a is an image at a high wind speed. As can be seen from fig. 2a and 2b, the sea surface in the image shows gray tone or dark tone, in fig. 2b, islands are bright tone, and the contrast between the sea surface and the dark tone is obvious, whereas in fig. 2a, the difference between the islands and the sea surface is reduced, and the island-to-sea surface separability in the image is obviously reduced.
As can be seen from the comparison of the areas, the backscattering intensities of the islands and the sea surface are greatly different at different wind speeds. The backscattering intensity of the island (land) at low wind speed is obviously higher than that of the sea surface, and in the connecting line of the sea surface and the island, the island part presents an obvious peak area. In the high wind speed image, the island (land) has similar backscattering intensity with the sea surface, and the island boundary is fuzzy and the image characteristics are indistinguishable.
Furthermore, according to the semi-empirical geophysical model function of the sea surface wind field inversion algorithm, the relation between the wind speed and the backscattering intensity of the SAR image is known to be positive, and the backscattering intensity is increased along with the increase of the wind speed. According to the invention, COMD4 is adopted to estimate the relation between the wind speed and the back scattering intensity, wherein under the condition that the included angle between the incident angle (30 ℃) and the wind speed and the included angle between the wind direction (0 ℃) are fixed, the relation between the wind speed and the back scattering intensity is calculated according to a semi-empirical geophysical function model CMOD4, and the trend between the back scattering intensity and the wind speed can be shown as shown in figure 3. In one exemplary embodiment, the resulting wind speed versus backscatter intensity relationship satisfies the following condition:
y=6.278ln(x)-21.985 （1）
where y represents the backscatter intensity and x represents the wind speed.
Therefore, as the wind speed increases, the backward scattering intensity of the water body in the SAR image increases, which reduces the difference between the water body and other ground objects such as vegetation and the like, and the distinguishing property of the water body is poor.
Based on the research, the imaging process of the water body in SAR imaging is obviously influenced by weather, and in order to reduce the influence of weather, the invention provides a coastal zone change detection method of SAR images by combining wind speed data under the condition of considering wind speed, and the detected change monitoring result is corrected.
Further, an embodiment of the present invention provides a method for detecting a change in a coastal zone based on SAR images, as shown in fig. 4, which may include the following steps:
s100, SAR images P k and wind speeds V k corresponding to the target monitoring area at the current calculation time k are obtained; the target monitoring area is an area in a target coastal zone.
In the embodiment of the invention, the SAR image has the characteristics of cloud penetration and fog penetration and all-weather imaging, is suitable for monitoring coastal zones, and can acquire stable and reliable data sources. In an exemplary embodiment of the present invention, the SAR image may be a sentinel No. 1 image. The interferometric broad (IW) mode of the sentinel number 1 image may include VV/VH polarization. Wherein, for coastal zone changes, the homopolar data of VV is adopted for change detection in consideration of that homopolar data is stronger than the received signal of cross polarization. The VV polarization mode signal transmission and receiving adopt vertical directions, so that the method has a good monitoring effect on targets with volume scattering characteristics, is suitable for land use change monitoring, and has more advantages in shore zone change monitoring.
In an embodiment of the present invention, the target coastal zone may be a user-specified coastal zone. The target monitoring area may be a user-specified area, and may be an area of the coastline near the land side.
In the embodiment of the invention, the change of the target monitoring area can be detected according to a set time period, namely, the time interval between two adjacent calculation moments. The set time period may be set based on actual needs.
In the embodiment of the invention, the wind speed V k may be obtained based on daily wind field data of the ECMWF (long term weather forecast in europe), and may specifically be 10 meters wind field data of the ECMWF. The time resolution of the data was 6h, and the data time per day was 0, 6, 12, and 18 time points, and the spatial resolution was 0.75 ° ×0.75 °, 0.5 ° ×0.5 °,0.25 ° ×0.25 °,0.125 ° ×0.125 °, and other different data accuracies, respectively, wherein the 0.125 ° spatial resolution was about 10 Km.
Specifically, V k may be obtained based on the following steps:
S101, wind field data DEk={DE1 k,DE2 k,……,DEs k,……,DEq k},DEs k corresponding to a target monitoring area is obtained as the S-th data in DE k, DE s k=（ts k,vs k）,ts k is the monitoring time corresponding to DE s k, and v s k is the wind speed monitored at t s k; s has a value of 1 to q, q being the number of data in DE s k.
The wind field data corresponding to the target monitoring area may be wind field data of a unit time period corresponding to an imaging time T k of k, and a duration of one unit time period is 1 day.
S102, if the imaging time T k∈tk of P k, taking the wind speed corresponding to T k as V k; otherwise, execute S103;tk=（t1 k,t2 k,……,ts k,……,tq k）.
S103, a time adjacent to T k and located before T k is acquired from T k as a first time T1, and a time adjacent to T k and located after T k is acquired from T k as a second time T2.
S104, obtaining V k=v1+（Tk -t 1)/(t 2-t 1)(V 2-v 1); v1 is the wind speed corresponding to t1, and v2 is the wind speed corresponding to t 2.
S200, if V k-1≥V0,Vk is more than or equal to V0, taking the SAR image P k-1 corresponding to the previous calculation time k-1 as a current first comparison image, taking P k as a current second comparison image, and executing S400; if V k-1＜V0,Vk is greater than or equal to V0, executing S300; v k-1 is the wind speed corresponding to the last calculation time k-1 of the target monitoring area; v0 is a set wind speed threshold.
In the embodiment of the invention, in order to reduce the influence of wind speed on SAR image change detection by combining with the ground feature back scattering intensity characteristics in SAR images, and combining with the relationship between the back scattering intensity and the wind speed shown in FIG. 3, the back scattering intensity is selected as the threshold wind speed when approaching-10 dB change, and the threshold wind speed V0 = 6.5m/s is known.
S300, setting the pixel values corresponding to the water body areas in P k-1 and P k to be the same pixel value, taking P k-1 with the pixel value as a current first comparison image, and taking P k with the pixel value as a current second comparison image; s400 is performed.
In the embodiment of the invention, the water body area in the P k-1 can be identified by a water body identification method. Those skilled in the art will recognize that any method of identifying a water body region from P k-1 is within the scope of the present invention.
Those skilled in the art will recognize that the pixel values corresponding to the water body regions in P k-1 and P k may be set to any same pixel value, and the present invention is not particularly limited.
In one exemplary embodiment, the pixel values corresponding to the water regions in P k-1 and P k may be set to the pixel value of the water region in P k-1, i.e., the water region in P k is replaced with the water region in P k-1.
In another exemplary embodiment, the pixel values corresponding to the water regions in P k-1 and P k may be set to 0, i.e., the corresponding water regions in P k and P k-1 are removed using the water region in P k-1 as a mask region.
Those skilled in the art will appreciate that any method of removing the corresponding water regions in P k and P k-1 using the water region in P k-1 as a mask region falls within the scope of the present invention.
Since the pixel values of the water body regions in P k-1 and P k are set to the same pixel value, in the change detection, the change of the water body region is not detected, so that the influence of high wind speed on the water body region can be avoided.
S400, obtaining a change area of the current second comparison image relative to the change of the current first comparison image as a change area of P k relative to the change of P k-1; s100 is performed.
Further, S400 may specifically include:
S401, respectively preprocessing the current first comparison image and the current second comparison image to obtain a preprocessed first comparison image and a preprocessed second comparison image.
In an embodiment of the present invention, the preprocessing at least includes the following steps:
S4011, at least performing radiation calibration, geocoding and terrain correction on the current first comparison image and the current second comparison image respectively to obtain a first intermediate comparison image and a second intermediate comparison image.
For sentinel number 1 images, the preprocessing may also include applying track correction and thermal noise removal processes.
As known to those skilled in the art, a specific implementation of the preprocessing process of SAR images may be prior art.
S4012, respectively filtering the first intermediate comparison image and the second intermediate comparison image to obtain a first intermediate comparison image and a second intermediate comparison image after filtering.
In an embodiment of the present invention, the filtering method in the filtering process may include enlee filtering, enfrost filtering, etc. for reducing the influence of speckle, and median filtering for enhancing the edge information of the image. The filter window size may be 5 x 5.
S4013, clipping is respectively carried out from the first intermediate comparison image and the second intermediate comparison image after the filtering processing so as to extract the target monitoring area, and a corresponding first clipping image and a corresponding second clipping image are obtained.
S4014, performing histogram matching on the first clipping image and the second clipping image to obtain a first clipping image and a second clipping image after histogram matching, and using the first clipping image and the second clipping image as a first comparison image and a second comparison image after preprocessing.
In the embodiment of the invention, the histogram matching is used for reducing the back scattering intensity change of the same ground object caused by imaging differences such as the atmosphere. It is known to those skilled in the art that any method for histogram matching the first cropped image and the second cropped image falls within the scope of the present invention.
S402, based on an iterative weighted multi-element change detection algorithm, a first change region of the preprocessed second comparison image relative to the preprocessed first comparison image is obtained.
Further, S402 may specifically include:
S4021, performing linear stretching on the preprocessed first comparison image and the preprocessed second comparison image to obtain unsigned integer image data with the bit depth of 8 bits.
S4202, based on the iterative weighted multivariate variation detection algorithm, performing variation detection on the unsigned integer image data to obtain a corresponding chi-square chart.
Those skilled in the art know that any implementation method for detecting the change of the unsigned integer image data based on the iterative weighted multivariate change detection algorithm to obtain the corresponding chi-square chart belongs to the protection scope of the present invention. For example, the image obtained by preprocessing is subjected to centering processing, iteration times and a minimum weight convergence threshold are set, and iterative calculation is performed on the image so as to obtain a corresponding chi-square chart.
S4303, clustering the chi-square graph by using a preset clustering method to obtain a binary graph of a variation range.
In the embodiment of the invention, the preset clustering method can be a k-means clustering method.
It is known to those skilled in the art that any method of clustering chi-square patterns to obtain a binary pattern of varying scope falls within the scope of the present invention.
S4304, dividing the obtained binary image with the variation range, and removing the image spots smaller than the preset image spot area threshold value from the divided image spots to obtain a final variation image spot serving as the first variation area.
In the embodiment of the invention, the preset pattern area threshold value can be set based on actual needs.
Further, in the embodiment of the present invention, the final variation patch is a patch after morphological optimization.
It is known to those skilled in the art that plaque segmentation of binary maps can be prior art.
S403, based on an image difference method, a second change area of the preprocessed second comparison image relative to the preprocessed first comparison image is obtained.
Further, S403 may specifically include:
S4031, performing a difference operation on the preprocessed first comparison image and the preprocessed second comparison image to obtain a corresponding difference image, wherein the backscattering strength corresponding to the ith pixel point in the difference image is equal to |db 1i-db2i |; wherein db 1i is the backscatter intensity corresponding to the i-th pixel in the target detection area of the first comparison image after preprocessing, db 2i is the backscatter intensity corresponding to the i-th pixel in the target detection area of the second comparison image after preprocessing; i takes on values from 1 to n, n being the number of pixels in the target detection area. And | represents taking the absolute value.
S4032, if the i db 1i-db2i > db0, adding the i-th pixel point in the target detection area into the current change pixel point set; changing the initial value of the pixel point set to be a null value; db0 is a set backscatter intensity threshold.
In one embodiment of the present invention, db0 may be an empirical value.
In another embodiment of the present invention, db0 may be obtained by using a maximum inter-class variance method based on the difference image. It is known to those skilled in the art that any method for obtaining a corresponding threshold value using the maximum inter-class variance method based on the difference image falls within the scope of the present invention.
S4033, i=i+1 is set, if i is less than or equal to n, S4032 is executed, otherwise S4034 is executed.
S4034, obtaining the second change area based on the current change pixel point set, namely taking the area formed by all the pixel points in the current change pixel point set as the second change area.
S404, the first change area and the second change area are spatially connected to obtain a change area which is changed relative to the current first comparison image in the current second comparison image.
Further, S404 may specifically include:
S4041, acquiring a first pattern spot set PG1 corresponding to the first change area and a second pattern spot set PG2 corresponding to the second change area; wherein, PG 1= { PG1 1,PG12,……,PG1j,……,PG1m},PG1j is the j-th image patch in PG1, the value of j is 1to m, and m is the number of the image patches in PG 1; pg2= { PG2 1,PG22,……,PG2r,……,PG2u},PG2r is the r-th pattern spot in PG2, the value of r is 1to u, and u is the number of pattern spots in PG 2. PG1 j={P1j1,P1j2,……,P1jb,……,P1jf（j）},P1jb is the position of the b-th pixel point in PG1 j, the value of b is 1to f (j), and f (j) is the number of the pixel points in PG1 j; PG2 r={P2r1,P2r2,……,P2rc,……,P2rg（r）},P2rc is the position of the c-th pixel in PG2 r, c has a value of 1to g (r), and g (r) is the number of pixels in PG2 r.
S4042, j=1.
S4043, r=1 is set.
S4044, acquiring a patch intersection pg=pg1 j∩PG2r, if the patch intersection PG is not null, adding PG1 j to the current target patch set, and executing S4046; otherwise, S4045 is performed; the initial value of the target pattern spot set is a null value;
S4045, setting r=r+1, if r is equal to or less than u, executing S4044, otherwise, executing S4046;
S4046, setting j=j+1, if j is less than or equal to m, executing S4043, otherwise, executing S4047;
S4047, the map spots in the current target map spot set are regarded as the change regions of the current second comparison image, which change with respect to the current first comparison image.
In practical applications, an attribute table of the patch vector in the difference image may be edited, a column of attribute (mark=1) may be added, and Spatial connection may be performed with the variable patch vector obtained by IR-MAD by using Spatial overlay analysis tool Spatial Join of ArcGIS. ArcToolbox-Analysis Tools-Spatial Join, performing preliminary filtering, and extracting a change pattern in which the pattern in the second change area overlaps with the pattern in the first change area as a change detection result.
Further, in the embodiment of the present invention, S200 further includes: if V k-1≥V0,Vk < V0, S310 is performed.
S310, removing corresponding water body areas in P k and P k-1 by using the water body areas in P k as mask areas, taking the image P k-1 with the water body areas removed as a current first comparison image, and taking the image P k with the water body areas removed as a current second comparison image; s400 is performed.
Further, S310 may be replaced by the following steps:
S320, in the historical SAR image corresponding to the target monitoring area, acquiring a water body area in the image which is closest to the imaging time corresponding to P k-1 and has the wind speed smaller than V0 as a mask area to remove the corresponding water body areas in P k and P k-1, taking the image P k-1 with the water body area removed as a current first comparison image, and taking the image P k with the water body area removed as a current second comparison image; s400 is performed.
The technical effect of S320 is that, compared to S310, errors caused by using newly generated pit water as a mask region can be avoided. For example, if a pool body of water is newly created in P k, if the body of water area in P k is used as a mask area, no change in the body of water can be detected.
The method provided by the embodiment of the invention can evaluate the change degree of the area based on the monitored change pattern spot range when being applied to specific applications. For example, if the change results corresponding to a plurality of calculation times in adjacent periods are concentrated in a certain area, the construction of the area is always suggested, and the accuracy of detecting the pattern spots in the area is more reliable.
The embodiment of the invention also provides electronic equipment, which comprises: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being configured to perform the methods of embodiments of the present invention.
The embodiment of the invention also provides a non-transitory computer readable storage medium, which stores computer executable instructions for executing the method according to the embodiment of the invention.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution disclosed in the present invention can be achieved, and are not limited herein.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.
Claims (9)
1. The coastal zone change detection method based on SAR image is characterized by comprising the following steps:
S100, SAR images P k and wind speeds V k corresponding to the target monitoring area at the current calculation time k are obtained; the target monitoring area is an area in a target coastal zone;
S200, if V k-1≥V0,Vk is more than or equal to V0, taking the SAR image P k-1 corresponding to the previous calculation time k-1 as a current first comparison image, taking P k as a current second comparison image, and executing S400; if V k-1＜V0,Vk is greater than or equal to V0, executing S300; v k-1 is the wind speed corresponding to the last calculation time k-1 of the target monitoring area; v0 is a set wind speed threshold value;
S300, setting the pixel values corresponding to the water body areas in P k-1 and P k to be the same pixel value, taking P k-1 with the pixel value as a current first comparison image, and taking P k with the pixel value as a current second comparison image; s400 is executed;
S400, obtaining a change area of the current second comparison image relative to the change of the current first comparison image as a change area of P k relative to the change of P k-1; s100 is performed.
2. The method according to claim 1, wherein S400 specifically comprises:
S401, respectively preprocessing a current first comparison image and a current second comparison image to obtain a preprocessed first comparison image and a preprocessed second comparison image;
s402, acquiring a first change region of the preprocessed second comparison image relative to the preprocessed first comparison image based on an iterative weighted multivariate change detection algorithm;
S403, acquiring a second change region of the preprocessed second comparison image relative to the preprocessed first comparison image based on an image difference method;
s404, the first change area and the second change area are spatially connected to obtain a change area which is changed relative to the current first comparison image in the current second comparison image.
3. The method according to claim 2, characterized in that the pre-treatment comprises at least the following steps:
S4011, at least performing radiation calibration, geocoding and topography correction on a current first comparison image and a current second comparison image in sequence to obtain a first intermediate comparison image and a second intermediate comparison image;
S4012, respectively filtering the first intermediate comparison image and the second intermediate comparison image to obtain a first intermediate comparison image and a second intermediate comparison image after filtering;
s4013, clipping is respectively carried out from the first intermediate comparison image and the second intermediate comparison image after the filtering processing so as to extract the target monitoring area and obtain a corresponding first clipping image and a corresponding second clipping image;
S4014, performing histogram matching on the first clipping image and the second clipping image to obtain a first clipping image and a second clipping image after histogram matching, and using the first clipping image and the second clipping image as a first comparison image and a second comparison image after preprocessing.
4. The method of claim 1, wherein the SAR image is a sentinel No. 1 image.
5. The method according to claim 2, wherein S402 specifically comprises:
S4021, respectively linearly stretching the preprocessed first comparison image and the preprocessed second comparison image into unsigned integer image data with the bit depth of 8 bits;
S4202, performing change detection on the unsigned integer image data based on an iterative weighted multivariate change detection algorithm to obtain a corresponding chi-square chart;
S4303, clustering the chi-square graph by using a preset clustering method to obtain a binary graph of a variation range;
S4304, dividing the obtained binary image with the variation range, and removing the image spots smaller than the preset image spot area threshold value from the divided image spots to obtain a final variation image spot serving as the first variation area.
6. The method according to claim 2, wherein S403 specifically comprises:
S4031, performing a difference operation on the preprocessed first comparison image and the preprocessed second comparison image to obtain a corresponding difference image, wherein the backscattering strength corresponding to the ith pixel point in the difference image is equal to |db 1i-db2i |; wherein db 1i is the backscatter intensity corresponding to the i-th pixel in the target detection area of the first comparison image after preprocessing, db 2i is the backscatter intensity corresponding to the i-th pixel in the target detection area of the second comparison image after preprocessing; i takes the value of 1 to n, n is the number of pixel points in the target detection area, and || represents the absolute value;
S4032, if the i db 1i-db2i > db0, adding the i-th pixel point in the target detection area into the current change pixel point set; changing the initial value of the pixel point set to be a null value; db0 is a set backscatter intensity threshold;
s4033, setting i=i+1, if i is less than or equal to n, executing S4032, otherwise, executing S4034;
And S4034, obtaining the second change area based on the current change pixel point set.
7. The method according to claim 2, wherein S404 specifically comprises:
S4041, acquiring a first pattern spot set PG1 corresponding to the first change area and a second pattern spot set PG2 corresponding to the second change area; wherein, PG 1= { PG1 1,PG12,……,PG1j,……,PG1m},PG1j is the j-th image patch in PG1, the value of j is 1 to m, and m is the number of the image patches in PG 1; pg2= { PG2 1,PG22,……,PG2r,……,PG2u},PG2r is the r-th pattern spot in PG2, the value of r is 1 to u, and u is the number of pattern spots in PG2;
s4042, set j=1;
S4043, r=1;
S4044, acquiring a patch intersection pg=pg1 j∩PG2r, if the patch intersection PG is not null, adding PG1 j to the current target patch set, and executing S4046; otherwise, S4045 is performed; the initial value of the target pattern spot set is a null value;
S4045, setting r=r+1, if r is equal to or less than u, executing S4044, otherwise, executing S4046;
S4046, setting j=j+1, if j is less than or equal to m, executing S4043, otherwise, executing S4047;
S4047, the map spots in the current target map spot set are regarded as the change regions of the current second comparison image, which change with respect to the current first comparison image.
8. The method of claim 1, wherein V k is obtained based on the steps of:
S101, wind field data DEk={DE1 k,DE2 k,……,DEs k,……,DEq k},DEs k corresponding to a target monitoring area is obtained as the S-th data in DE k, DE s k=（ts k,vs k）,ts k is the monitoring time corresponding to DE s k, and v s k is the wind speed monitored at t s k; s has a value of 1 to q, q being the number of data in DE s k;
S102, if the imaging time T k∈tk of P k, taking the wind speed corresponding to T k as V k; otherwise, execute S103;tk=（t1 k,t2 k,……,ts k,……,tq k）;
S103, acquiring a time adjacent to T k and located before T k from T k as a first time T1, and acquiring a time adjacent to T k and located after T k from T k as a second time T2;
S104, obtaining V k=v1+（Tk -t 1)/(t 2-t 1) (V 2-v 1); v1 is the wind speed corresponding to t1, and v2 is the wind speed corresponding to t 2.
9. An electronic device comprising a processor and a memory;
The processor is adapted to perform the steps of the method according to any of claims 1 to 8 by invoking a program or instruction stored in the memory.
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