Method and device for selecting time-series InSAR interferometric image pairs

Abstract

The application discloses a kind of selection method and device of time series InSAR interference image pair, wherein the method comprises: obtaining SAR single view complex image in research period in covering research area;The image is obtained by pairing two by two to obtain several interference image pairs;Based on interference image pair, the interference coherence coefficient of each pixel is calculated to obtain interference coherence coefficient chart;The average coherence coefficient of each interference chart is calculated;Interference chart is classified according to the acquisition date of main image by month, and the monthly average coherence coefficient of total and each month is calculated;Interference chart is divided into high and low coherence month with month as unit;With high average coherence coefficient as threshold value, interference image pair in high coherence month is selected, with low average coherence coefficient as threshold value, interference image pair in low coherence month is selected, and the selected interference image pair is used for time series InSAR analysis.The application considers coherence coefficient month difference and carries out time series InSAR interference image pair selection, and can realize discontinuous coherence area interference image pair optimization selection.

Description

Technical Field

[0001] This invention relates to the field of temporal InSAR technology, and in particular to a method and apparatus for selecting temporal InSAR interferometric image pairs that takes into account the monthly differences in coherence coefficients. Background Technology

[0002] This section is intended to provide background or context for the embodiments of the invention set forth in the claims. The description herein is not an admission that it is prior art simply because it is included in this section.

[0003] Time Series Interferometric Synthetic Aperture Radar (TS-InSAR) is a promising Earth observation technology. By interferometric processing and time-series inversion of interferometric pairs composed of multiple single-look complex SAR images covering the same area, it can obtain information on small deformations of the Earth's surface over a large area. It is widely used in the detection and monitoring of creep geological hazards.

[0004] However, temporal InSAR technology places high demands on the quantity, quality, and interferometric baseline network structure of interferometric pairs. Good interferometric pairs and robust interferometric baseline networks are prerequisites for the effective identification of surface deformation by temporal InSAR technology. Therefore, optimizing the selection of interferometric pairs is essential. Currently, the main methods for selecting interferometric pairs are as follows: 1. Manually selecting interferometric pairs with good coherence based on empirical judgment; 2. Selecting interferometric pairs based on short-spatial baseline thresholds; 3. Selecting interferometric pairs based on environmental factors of the study area (temperature, humidity, vegetation cover, etc.); 4. Selecting interferometric pairs based on coherence coefficient thresholds. Among these, manual selection requires expert knowledge and is time-consuming and labor-intensive, making it unsuitable for processing long-term InSAR studies with large amounts of data; short-spatial baseline thresholds cannot eliminate interferograms with short intervals but poor coherence, easily introducing decorrelation errors, and using only short-spatial baseline interferograms may introduce systematic errors; referencing environmental factors of the study area requires obtaining a large amount of accurate external data, which is difficult to achieve in many regions. Using a coherence coefficient threshold to select interferometric pairs can effectively avoid the above problems. As a characterization factor of the quality of interferometric pairs, the coherence coefficient is applied to the selection of interferometric pairs.

[0005] However, in intermittent coherence regions where the coherence coefficient varies monthly, selecting interferometric pairs using a coherence coefficient threshold presents a challenge in determining the threshold. Currently, a uniform custom coherence coefficient (0.1–0.6) or average coherence coefficient threshold is mainly used. However, selecting interferograms based on a custom coherence coefficient threshold requires prior knowledge and is subjective. Setting the threshold too high can easily lead to discontinuities or missing interferometric baselines. Discontinuities in the interferometric baselines can reduce the accuracy of deformation inversion results or even render them unusable. Missing interferometric baselines result in too few interferometric pairs, failing to meet the requirements of time-series InSAR processing. Setting the threshold too low can lead to interferometric pair redundancy and the introduction of low-coherence interferometric pairs. Redundancy increases processing difficulty, and low-coherence interferometric pairs participating in time-series InSAR inversion can easily introduce decorrelation errors. Using an average coherence coefficient threshold for interferometric pair selection easily leads to discontinuities in the interferometric baselines. Therefore, existing methods for selecting interferometric pairs based on coherence coefficient thresholds are not applicable in intermittent coherence regions where the coherence coefficient varies monthly. Optimizing the selection of interferometric pairs in intermittent coherence regions is a pressing problem that needs to be solved in current time-series InSAR processing. Summary of the Invention

[0006] This invention provides a method for selecting temporal InSAR interferometric image pairs to optimize the selection of interferometric image pairs in discontinuous coherence regions. The method includes:

[0007] Acquire synthetic aperture radar SAR single-look complex images covering the study area during the study period;

[0008] Several interferometric image pairs are obtained by pairing SAR single-look complex images with a preset time baseline as a threshold.

[0009] The interference coherence coefficient of each pixel is calculated based on the interference image pairs to obtain the interference coherence coefficient map;

[0010] Calculate the average coherence coefficient for each interferometric coherence coefficient image;

[0011] The interferometric coherence maps are categorized by month based on the acquisition date of the main image, and the overall average coherence coefficient and the monthly average coherence coefficient for each month are calculated; the overall average coherence coefficient is the mean of the average coherence coefficients of all interferometric coherence maps.

[0012] The interferometric coherence coefficient map is divided into high coherence months and low coherence months on a monthly basis. Months with a monthly average coherence coefficient greater than the total average coherence coefficient are classified as high coherence months, and months with a monthly average coherence coefficient less than the total average coherence coefficient are classified as low coherence months.

[0013] Interferometric pairs within high-coherence months are selected using a high average coherence coefficient as the threshold, and interferometric pairs within low-coherence months are selected using a low average coherence coefficient as the threshold. The selected interferometric pairs are used for time-series InSAR analysis. The high average coherence coefficient is the mean of the average coherence coefficients of all interferometric coherence coefficient maps within the high-coherence months, and the low average coherence coefficient is the mean of the average coherence coefficients of all interferometric coherence coefficient maps within the low-coherence months.

[0014] This invention also provides a device for selecting time-series InSAR interferometric image pairs to achieve optimized selection of interferometric image pairs in discontinuous coherence regions. The device includes:

[0015] The acquisition unit is used to acquire synthetic aperture radar SAR single-look complex images covering the study area during the study period;

[0016] The interferometric image pair determination unit is used to pair SAR single-look complex images with a preset time baseline as a threshold to obtain several interferometric image pairs.

[0017] The interference coherence coefficient map determination unit is used to calculate the interference coherence coefficient of each pixel based on the interference image pair to obtain the interference coherence coefficient map;

[0018] The coherence coefficient calculation unit is used to calculate the average coherence coefficient of each interferometric coherence coefficient image;

[0019] The classification calculation unit is used to classify the interferometric coherence coefficient maps by month according to the acquisition date of the main image, and calculate the total average coherence coefficient and the monthly average coherence coefficient for each month; the total average coherence coefficient is the mean of the average coherence coefficients of all interferometric coherence coefficient maps;

[0020] The coherence month determination unit is used to classify the interferometric coherence coefficient map into high coherence months and low coherence months on a monthly basis. Months with a monthly average coherence coefficient greater than the total average coherence coefficient are classified as high coherence months, and months with a monthly average coherence coefficient less than the total average coherence coefficient are classified as low coherence months.

[0021] The selection unit is used to select interferometric image pairs within high-coherence months using a high average coherence coefficient as a threshold, and to select interferometric image pairs within low-coherence months using a low average coherence coefficient as a threshold. The selected interferometric image pairs are used for time-series InSAR analysis. The high average coherence coefficient is the mean of the average coherence coefficients of all interferometric coherence coefficient maps within high-coherence months, and the low average coherence coefficient is the mean of the average coherence coefficients of all interferometric coherence coefficient maps within low-coherence months.

[0022] This invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the above-described method for selecting time-series InSAR interferometric image pairs.

[0023] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for selecting time-series InSAR interferometric image pairs.

[0024] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described method for selecting time-series InSAR interferometric image pairs.

[0025] In this embodiment of the invention, the selection scheme for time-series InSAR interferometric image pairs involves: acquiring synthetic aperture radar (SAR) single-look complex images covering the study area within the study period; pairing the SAR single-look complex images in pairs using a preset time baseline as a threshold to obtain several interferometric image pairs; calculating the interferometric coherence coefficient of each pixel based on the interferometric image pairs to obtain an interferometric coherence map; calculating the average coherence coefficient of each interferometric coherence map; classifying the interferometric coherence maps by month according to the acquisition date of the main image, and calculating the total average coherence coefficient and the monthly average coherence coefficient for each month; the total average coherence coefficient is the mean of the average coherence coefficients of all interferometric coherence maps; and classifying the interferometric coherence maps by month into high-coherence months and low-coherence months. Months are categorized as follows: months with a monthly average coherence coefficient greater than the total average coherence coefficient are classified as high-coherence months, and months with a monthly average coherence coefficient less than the total average coherence coefficient are classified as low-coherence months. Interferometric pairs are selected within high-coherence months using the high average coherence coefficient as a threshold, and within low-coherence months using the low average coherence coefficient as a threshold. These selected interferometric pairs are used for temporal InSAR analysis. The high average coherence coefficient is the mean of the average coherence coefficients of all interferometric coherence coefficient maps within high-coherence months, and the low average coherence coefficient is the mean of the average coherence coefficients of all interferometric coherence coefficient maps within low-coherence months. This scheme takes into account the monthly differences in coherence coefficients when selecting temporal InSAR interferometric pairs, enabling optimized selection of interferometric pairs in discontinuous coherence regions. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0027] Figure 1 A schematic diagram of the overall process for selecting time-series InSAR interferometric image pairs that takes into account the monthly differences in coherence coefficients is provided for this invention.

[0028] Figure 2 An interference coherence coefficient diagram is provided for an embodiment of the present invention;

[0029] Figure 3 This is a diagram showing the connection of interferometric baselines for all interferometric image pairs in this embodiment of the invention, where the time baseline threshold is 108 days.

[0030] Figure 4 This is a line graph showing the monthly average coherence coefficient and the total average coherence coefficient obtained in this embodiment of the invention.

[0031] Figure 5 This is an interference baseline connection diagram obtained after selecting interference image pairs, as provided in an embodiment of the present invention.

[0032] Figure 6 This is a flowchart illustrating the method for selecting temporal InSAR interferometric image pairs that takes into account the monthly differences in coherence coefficients in an embodiment of the present invention.

[0033] Figure 7 This is a schematic diagram of the temporal InSAR interferometric image pair selection device that takes into account the monthly differences in coherence coefficient in an embodiment of the present invention. Detailed Implementation

[0034] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0035] To address the shortcomings and deficiencies in existing technologies, this invention provides a selection scheme for temporal InSAR interferometric image pairs. This scheme takes into account the monthly differences in coherence coefficients, thereby solving the problem of optimizing the selection of interferometric image pairs in discontinuous coherence regions. The following is a detailed description of this temporal InSAR interferometric image pair selection scheme.

[0036] Figure 6 This is a flowchart illustrating the method for selecting temporal InSAR interferometric image pairs that takes into account monthly differences in coherence coefficients in an embodiment of the present invention. Figure 6 As shown, the method includes the following steps:

[0037] Step 101: Acquire synthetic aperture radar SAR single-look complex images covering the study area during the study period;

[0038] Step 102: Pair the SAR single-look complex images together with a preset time baseline as the threshold to obtain several interferometric image pairs;

[0039] Step 103: Calculate the interference coherence coefficient of each pixel based on the interference image pair to obtain the interference coherence coefficient map;

[0040] Step 104: Calculate the average coherence coefficient for each interferometric coherence coefficient map;

[0041] Step 105: Classify the interferometric coherence maps by month according to the acquisition date of the main image, and calculate the total average coherence coefficient and the monthly average coherence coefficient for each month; the total average coherence coefficient is the mean of the average coherence coefficients of all interferometric coherence maps;

[0042] Step 106: Divide the interference coherence coefficient map into high coherence months and low coherence months on a monthly basis. Months with a monthly average coherence coefficient greater than the total average coherence coefficient are classified as high coherence months, and months with a monthly average coherence coefficient less than the total average coherence coefficient are classified as low coherence months.

[0043] Step 107: Select interferometric image pairs within high-coherence months using high average coherence coefficient as the threshold, and select interferometric image pairs within low-coherence months using low average coherence coefficient as the threshold. The selected interferometric image pairs are used for time-series InSAR analysis. The high average coherence coefficient is the mean of the average coherence coefficients of all interferometric coherence coefficient maps within high-coherence months, and the low average coherence coefficient is the mean of the average coherence coefficients of all interferometric coherence coefficient maps within low-coherence months.

[0044] The temporal InSAR interferometric image pair selection method provided in this embodiment of the invention operates as follows: Acquire synthetic aperture radar (SAR) single-look complex images covering the study area within the study period; pair the SAR single-look complex images pairwise using a preset time baseline as a threshold to obtain several interferometric image pairs; calculate the interferometric coherence coefficient of each pixel based on the interferometric image pairs to obtain an interferometric coherence map; calculate the average coherence coefficient of each interferometric coherence map; classify the interferometric coherence maps by month according to the acquisition date of the main image, and calculate the total average coherence coefficient and the monthly average coherence coefficient for each month; the total average coherence coefficient is the mean of the average coherence coefficients of all interferometric coherence maps; and classify the interferometric coherence maps by month into high-coherence months and low-coherence months. Months with a monthly average coherence coefficient greater than the overall average coherence coefficient are classified as high-coherence months, while months with a monthly average coherence coefficient less than the overall average coherence coefficient are classified as low-coherence months. Interferometric pairs are selected within high-coherence months using the high average coherence coefficient as a threshold, and within low-coherence months using the low average coherence coefficient as a threshold. These selected interferometric pairs are used for temporal InSAR analysis. The high average coherence coefficient is the mean of the average coherence coefficients of all interferometric coherence coefficient maps within high-coherence months, and the low average coherence coefficient is the mean of the average coherence coefficients of all interferometric coherence coefficient maps within low-coherence months. By considering the monthly differences in coherence coefficients when selecting temporal InSAR interferometric pairs, optimal selection of interferometric pairs in discontinuous coherence regions can be achieved. A detailed explanation follows.

[0045] Currently, the main methods for selecting interferometric pairs in temporal InSAR are manual selection, selection based on short-spatial baseline thresholds, selection based on environmental factors of the study area, or selection based on fixed coherence coefficient thresholds. With the increasing use of temporal InSAR data, the problems with the first three methods have become more apparent. Coherence coefficient, because it can comprehensively reflect various coherence influencing factors and characterize the quality of interferometric pairs, has gradually been used for selection. However, in practice, especially in intermittent coherence regions where coherence coefficients vary monthly, using only a fixed coherence coefficient threshold can easily lead to broken interferometric baselines, redundancy, or the absence of key interferometric pairs, making it difficult to obtain a robust interferometric baseline network. Therefore, when using coherence coefficients to select interferometric pairs, the monthly variation of the coherence coefficient must be taken into account.

[0046] To address the problem that conventional interferometric image pair selection methods based on fixed coherence coefficients are prone to interferometric baseline breaks, redundancy, or missing data in intermittent coherence regions with monthly variations, thus reducing the accuracy of time-series InSAR surface deformation detection, this invention provides an interferometric image pair selection method that takes into account monthly differences in coherence coefficients. This method first acquires SAR single-look complex images covering the study area within the study period. Several interferometric image pairs are obtained by pairwise pairing of the SAR single-look complex images with a preset time baseline range, such as 100 to 115 days (preferably 108 days). The time baseline threshold of 108 days covers three months, reflecting the monthly changes in coherence coefficients and providing a more lenient alternative for interferometric image pair selection. Then, the coherence coefficient of each pixel is calculated based on the interferometric image pairs to obtain an interferometric coherence coefficient map. Next, the average coherence coefficient of each interferometric coherence coefficient map is calculated, and the interferometric baseline is optimized based on the average coherence coefficient. The interferometric coherence coefficient maps are categorized by month according to the acquisition date of the main image, and the overall average coherence coefficient λ is calculated. all (The mean of the average coherence coefficients of all interferometric coherence coefficient plots) and the monthly average coherence coefficient λ for each month. month , with λ all For the segmentation value, λ month Greater than λ all The months with high coherence are classified as λ months. month Less than λ all The months with low coherence are classified as low-coherence months. Then, the mean λ of the average coherence coefficient of all interferometric coherence coefficient maps within the high-coherence months is used. high Interferometric pairs within high-coherence months are selected as the threshold, and the mean λ of the average coherence coefficient of all interferometric coherence coefficient maps within low-coherence months is used. low Interference pairs within months with low coherence are selected based on the threshold to obtain the final selected interference pairs.

[0047] The embodiments of the present invention adopt the following solution:

[0048] S1. Obtain SAR single-look multiple images covering the study area during the study period. This step S1 is the same as step 101 above.

[0049] S2. Pair the SAR single-view multiple images with a preset time baseline (e.g., 100 to 115 days, preferably 108 days) as a threshold to obtain several interferometric image pairs. This step S2 corresponds to step 102 above.

[0050] S3. Calculate the coherence coefficient of each pixel based on the interference image pairs obtained above to obtain the interference coherence coefficient map. This step S3 corresponds to step 103 above.

[0051] Furthermore, the formula for calculating the interference coherence coefficient at pixel (i, j) in step S3 above is as follows: In one embodiment, the above-mentioned time-series InSAR interferometric image pair selection method may further include calculating the interference coherence coefficient of each pixel according to the following formula (1):

[0052]

[0053] In the formula, λ (i,j) is the interferometric coherence coefficient at pixel (i,j), Q and S are the acquired SAR single-look complex images, namely the master image and the slave image, respectively, * indicates complex conjugate multiplication, m and n are the local window sizes used to calculate the coherence coefficient, and (i,j) represents the position of the pixel.

[0054] S4. Calculate the average coherence coefficient of each interferometric coherence coefficient image. This step S4 corresponds to step 104 above.

[0055] Furthermore, the formula for calculating the average coherence coefficient of the interferometric coherence coefficient map in step S4 above is as follows: In one embodiment, the above-mentioned time-series InSAR interferometric image pair selection method may further include calculating the average coherence coefficient of each interferometric coherence coefficient map according to the following formula (2):

[0056]

[0057] In the formula, λ avg λ is the average coherence coefficient of the interferometric coherence coefficient map, where W and I are the width and length of the image, respectively. (i,j) It is the coherence coefficient at pixel (i, j).

[0058] S5. Categorize the interferometric coherence maps by month according to the acquisition date of the main image, and calculate the total average coherence coefficient λ. all (The mean of the average coherence coefficients of all interferometric coherence coefficient plots) and the monthly average coherence coefficient λ for each month. month This step S5 corresponds to step 105 above;

[0059] Furthermore, in step S5 above, the total average coherence coefficient λ all and monthly average coherence coefficient λ month The calculation formula is as follows: In one embodiment, it further includes calculating the total average coherence coefficient according to the following formula (3), and calculating the monthly average coherence coefficient according to the following formula (4):

[0060]

[0061]

[0062] In the formula, N is the number of all interferograms, and λ all It is the total average coherence coefficient; M is the number of interferograms per month, λ month It is the monthly average coherence coefficient, λ avg It is the average coherence coefficient of the interference coherence coefficient diagram, and t represents the number of interference pairs.

[0063] S6. Divide the interferogram into high-coherence months and low-coherence months on a monthly basis, and calculate the monthly average coherence coefficient λ. month Greater than λ all The months are divided into highly coherent months, λ month Less than λ all The months are divided into low coherence months, and this step S6 corresponds to the above step 106;

[0064] Furthermore, the expression for distinguishing between high-coherence months and low-coherence months in step S6 above can be:

[0065]

[0066] Furthermore, the calculation formula for the selection threshold of interferometric image pairs in different months in step S6 above can be, that is, in one embodiment, the above-mentioned time-series InSAR interferometric image pair selection method can also include calculating the high average coherence coefficient according to the following formula (5), and calculating the low average coherence coefficient according to the following formula (6):

[0067]

[0068]

[0069] In the formula, H represents the number of all interferograms for the highly coherent month, and λ high λ represents the high average coherence coefficient; L is the number of interferograms for all months with low coherence. low It has a low average coherence coefficient.

[0070] S7, with a high average coherence coefficient λ highInterferogram pairs within high-coherence months are selected using the mean of the average coherence coefficients of all interferometric coherence coefficient maps within the high-coherence month as the threshold, and the low average coherence coefficient λ is used as the threshold. low The mean of the average coherence coefficients of all interferometric coherence coefficient maps within the low coherence month is used as the threshold to select interferometric pairs within the low coherence month. The finally selected interferometric pairs are used for time-series InSAR analysis. High average coherence coefficient and low average coherence coefficient are the thresholds for selecting interferometric pairs in different months. This step S7 corresponds to step 107 above.

[0071] To facilitate understanding of how this invention is implemented, the following is combined with... Figures 1 to 5 Let me give an example to illustrate this in detail.

[0072] This invention discloses a method for selecting temporal InSAR interferometric image pairs that takes into account the monthly differences in coherence coefficients. The following describes the invention in further detail with reference to the accompanying drawings and specific embodiments, using the section from the Longchuan River estuary to the Xiaojiang River estuary in the Wudongde Reservoir area of ​​the Jinsha River Basin as an example area.

[0073] Figure 1 This invention provides an overall flowchart of a time-series InSAR interferometric image pair selection method that takes into account monthly differences in coherence coefficients. The specific method of this invention includes the following steps:

[0074] Step S1: Acquire 86 Sentinel-1A down-orbit single-view complex images covering the instance area from February 2019 to 2022.

[0075] Since the coverage area of ​​a single-view complex image of a Sentinel-1A down-orbiting image is larger than the instance area, the Sentinel-1A down-orbiting single-view complex image was cropped based on the instance area.

[0076] Step S2: Pair 86 Sentinel-1A single-view complex images with a time baseline of 108 days as the threshold to obtain 711 interferometric image pairs.

[0077] Step S3: Calculate the coherence coefficient of each pixel based on the interference image pairs obtained above, and obtain the interference coherence coefficient map.

[0078] The formula for calculating the coherence coefficient is:

[0079]

[0080] In the formula, Q and S are the acquired SAR single-look complex images, namely the main image and the secondary image, respectively; * indicates complex conjugate multiplication; m and n are the local window sizes used to calculate the coherence coefficient; and (i,j) represents the position of the pixel. In this embodiment, a local window size of 5×5 is used.

[0081] Figure 2An interference coherence coefficient diagram is provided for an embodiment of the present invention, with coherence coefficients ranging from 0.0 (completely decoherent) to 1.0 (completely coherent).

[0082] Step S4: Calculate the average coherence coefficient for each interferometric coherence coefficient graph.

[0083] The formula for calculating the average coherence coefficient is:

[0084]

[0085] In the formula, λ avg λ is the average coherence coefficient of the interferometric coherence coefficient map, where W and I are the width and length of the image, respectively. (i,j) It is the coherence coefficient at pixel (i, j).

[0086] Figure 3 This is a diagram showing the interferometric baseline connections for all interferometric image pairs with a time baseline threshold of 108 days, as per an embodiment of the present invention. The horizontal axis represents the acquisition time of the Sentinel-1A image, the vertical axis represents the spatial baseline of the interferometric image pairs, and the color bars represent the average coherence coefficient of the interferometric image pairs.

[0087] The next step is to analyze the average coherence coefficient value of the interferometric coherence coefficient diagram.

[0088] Step S5: Categorize the interferometric coherence maps by month according to the acquisition date of the main image, and calculate the total average coherence coefficient λ. all (The mean of the average coherence coefficients of all interferometric coherence coefficient plots) and the monthly average coherence coefficient λ for each month. month .

[0089] The formula for calculating the overall average coherence coefficient is:

[0090]

[0091] In the formula, N is the number of all interferograms, and λ all It is the overall average coherence coefficient, λ avg It is the average coherence coefficient of the interference coherence coefficient diagram. In this embodiment, N is 711, and the calculated total average coherence coefficient is 0.45.

[0092] The formula for calculating the monthly average coherence coefficient is:

[0093]

[0094] In the formula, M is the number of interferograms per month, and λ month It is the monthly average coherence coefficient. λ avg It is the average coherence coefficient of the interference coherence coefficient diagram.

[0095] Figure 4The line graphs of the monthly average coherence coefficient and the total average coherence coefficient calculated in this embodiment show that the coherence coefficient has obvious monthly variations. The monthly average coherence coefficient fluctuates around the total average coherence coefficient. The coherence coefficient is lower around August each year and higher around January, which is similar to the climate change characteristics of alternating dry and wet seasons in the example area.

[0096] Step S6: Divide the interferogram into high-coherence months and low-coherence months on a monthly basis, and calculate the monthly average coherence coefficient λ. month Greater than λ all The months are divided into highly coherent months, λ month Less than λ all The months are divided into low-coherence months.

[0097] The expression for interferogram classification is as follows:

[0098]

[0099] In this embodiment, the months with monthly average coherence coefficients higher than the overall average coherence coefficient are February, March, April, October, November, and December of 2019; January, February, March, April, November, and December of 2020; and January, February, March, November, and December of 2021. These months are classified as high coherence months, and the remaining months are classified as low coherence months.

[0100] Step S7: Take the mean value λ of the average coherence coefficient of all interferometric coherence coefficient maps within the high coherence month. high Interferometric pairs within high-coherence months are selected as the threshold, and the mean λ of the average coherence coefficient of all interferometric coherence coefficient maps within low-coherence months is used. low Interference pairs within months with low coherence were selected as the threshold.

[0101] The formulas for calculating high coherence coefficient and low coherence coefficient are as follows:

[0102]

[0103]

[0104] In the formula, H is the number of all interferometric image pairs in the highly coherent month, and λ high λ represents the high average coherence coefficient; L is the number of all interferometric pairs in the low coherence month; λ is the average coherence coefficient. low It has a low average coherence coefficient.

[0105] In this embodiment, there are 321 interference pairs in the high-coherence months, with a high average coherence coefficient of 0.51; and 390 interference pairs in the low-coherence months, with a low average coherence coefficient of 0.39. 156 interference pairs with an average coherence coefficient greater than 0.51 in the high-coherence months and 143 interference pairs with an average coherence coefficient greater than 0.39 in the low-coherence months are retained, and these are the final optimized selections of interference pairs.

[0106] Figure 5 The interference baseline connection diagram is obtained after optimizing the selection of interference image pairs according to an embodiment of the present invention.

[0107] The beneficial effects of the temporal InSAR interferometric image pair selection method considering the monthly differences in coherence coefficient provided by the embodiments of the present invention are as follows: The temporal InSAR interferometric image pair selection method considering the monthly differences in coherence coefficient of the present invention has good applicability in the intermittent coherence region. It can improve the overall coherence of the interferometric image pairs while reducing the redundancy of interferometric image pairs in high coherence months, increasing the number of interferometric pairs in low coherence months, reducing the phenomenon of discontinuity of interferometric baselines, obtaining a robust interferometric baseline network, and effectively improving the accuracy of temporal InSAR surface deformation inversion.

[0108] This invention also provides a temporal InSAR interferometric image pair selection device, as described in the following embodiments. Since the principle by which this device solves the problem is similar to that of the temporal InSAR interferometric image pair selection method, the implementation of this device can refer to the implementation of the temporal InSAR interferometric image pair selection method; repeated details will not be elaborated further.

[0109] Figure 7 This is a schematic diagram of the temporal InSAR interferometric image pair selection device that takes into account the monthly differences in coherence coefficient in an embodiment of the present invention, as shown below. Figure 7 As shown, the device includes:

[0110] Acquisition unit 01 is used to acquire synthetic aperture radar SAR single-look complex images covering the study area during the study period;

[0111] Interferometric image pair determination unit 02 is used to pair SAR single-look complex images with a preset time baseline as a threshold to obtain several interferometric image pairs;

[0112] Interference coherence coefficient map determination unit 03 is used to calculate the interference coherence coefficient of each pixel based on the interference image pair to obtain the interference coherence coefficient map;

[0113] Coherence coefficient calculation unit 04 is used to calculate the average coherence coefficient of each interferometric coherence coefficient image;

[0114] The classification calculation unit 05 is used to classify the interferometric coherence coefficient maps by month according to the acquisition date of the main image, and calculate the total average coherence coefficient and the monthly average coherence coefficient for each month; the total average coherence coefficient is the mean of the average coherence coefficients of all interferometric coherence coefficient maps;

[0115] The coherence month determination unit 06 is used to classify the interferometric coherence coefficient map into high coherence months and low coherence months on a monthly basis. Months with a monthly average coherence coefficient greater than the total average coherence coefficient are classified as high coherence months, and months with a monthly average coherence coefficient less than the total average coherence coefficient are classified as low coherence months.

[0116] Selection unit 07 is used to select interferometric image pairs within high-coherence months using a high average coherence coefficient as a threshold, and to select interferometric image pairs within low-coherence months using a low average coherence coefficient as a threshold. The selected interferometric image pairs are used for time-series InSAR analysis. The high average coherence coefficient is the mean of the average coherence coefficients of all interferometric coherence coefficient maps within high-coherence months, and the low average coherence coefficient is the mean of the average coherence coefficients of all interferometric coherence coefficient maps within low-coherence months.

[0117] In one embodiment, the aforementioned temporal InSAR interferometric image pair selection device that takes into account monthly differences in coherence coefficients may further include calculating the interferometric coherence coefficient of each pixel according to the following formula:

[0118]

[0119] In the formula, λ (i,j) is the interferometric coherence coefficient at pixel (i,j), Q and S are the acquired SAR single-look complex images, namely the master image and the slave image, respectively, * indicates complex conjugate multiplication, m and n are the local window sizes used to calculate the coherence coefficient, and (i,j) represents the position of the pixel.

[0120] In one embodiment, the aforementioned temporal InSAR interferometric image pair selection device that takes into account monthly differences in coherence coefficients may further include calculating the average coherence coefficient of each interferometric coherence image according to the following formula:

[0121]

[0122] In the formula, λ avg λ is the average coherence coefficient of the interferometric coherence coefficient map, W and I are the width and length of the image, respectively, (i,j) represents the position of the pixel, and λ is the average coherence coefficient of the interferometric coherence coefficient map. (i,j) It is the interference coherence coefficient at pixel (i,j).

[0123] In one embodiment, the aforementioned temporal InSAR interferometric image pair selection device that takes into account monthly differences in coherence coefficients may further include:

[0124] The overall average coherence coefficient is calculated using the following formula:

[0125]

[0126] In the formula, N is the number of all interferometric coherence coefficient maps, and λ all It is the overall average coherence coefficient, λ avg It is the average coherence coefficient of the interferometric coherence coefficient diagram;

[0127] The monthly average coherence coefficient is calculated using the following formula:

[0128]

[0129] In the formula, M is the number of interferometric coherence coefficient maps per month, and λ month It is the monthly average coherence coefficient, λ avg It is the average coherence coefficient of the interference coherence coefficient diagram.

[0130] In one embodiment, the aforementioned temporal InSAR interferometric image pair selection device that takes into account monthly differences in coherence coefficients may further include calculating the high average coherence coefficient according to the following formula:

[0131]

[0132] In the formula, H represents the number of all interferometric coherence coefficient maps for the highly coherent month, and λ high For a high average coherence coefficient, λ avg It is the average coherence coefficient of the interference coherence coefficient diagram.

[0133] In one embodiment, the aforementioned temporal InSAR interferometric image pair selection device that takes into account monthly differences in coherence coefficients may further include calculating the low average coherence coefficient according to the following formula:

[0134]

[0135] In the formula, L represents the number of all interferometric coherence coefficient maps for the low-coherence month, and λ low For low average coherence coefficient, λ avg It is the average coherence coefficient of the interference coherence coefficient diagram.

[0136] This invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the above-described time-series InSAR interferometric image pair selection method.

[0137] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described temporal InSAR interferometric image pair selection method.

[0138] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described temporal InSAR interferometric image pair selection method.

[0139] In this embodiment of the invention, the temporal InSAR interferometric image pair selection scheme involves: acquiring synthetic aperture radar (SAR) single-look complex images covering the study area within the study period; pairing the SAR single-look complex images in pairs using a preset time baseline as a threshold to obtain several interferometric image pairs; calculating the interferometric coherence coefficient of each pixel based on the interferometric image pairs to obtain an interferometric coherence map; calculating the average coherence coefficient of each interferometric coherence map; classifying the interferometric coherence maps by month according to the acquisition date of the main image, and calculating the total average coherence coefficient and the monthly average coherence coefficient for each month; the total average coherence coefficient is the mean of the average coherence coefficients of all interferometric coherence maps; and classifying the interferometric coherence maps by month into high-coherence months and low-coherence months. Months with a monthly average coherence coefficient greater than the overall average coherence coefficient are classified as high-coherence months, while months with a monthly average coherence coefficient less than the overall average coherence coefficient are classified as low-coherence months. Interferometric image pairs are selected within high-coherence months using the high average coherence coefficient as a threshold, and within low-coherence months using the low average coherence coefficient as a threshold. The selected interferometric image pairs are used for temporal InSAR analysis. The high average coherence coefficient is the mean of the average coherence coefficients of all interferometric coherence coefficient maps within high-coherence months, and the low average coherence coefficient is the mean of the average coherence coefficients of all interferometric coherence coefficient maps within low-coherence months. By taking into account the monthly differences in coherence coefficients when selecting temporal InSAR interferometric image pairs, optimal selection of interferometric image pairs in discontinuous coherence regions can be achieved.

[0140] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0141] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0142] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0143] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0144] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for selecting interferometric image pairs in temporal interferometric synthetic aperture radar (InSAR), characterized in that, include: Acquire synthetic aperture radar SAR single-look complex images covering the study area during the study period; Several interferometric image pairs are obtained by pairing SAR single-look complex images with a preset time baseline as a threshold. The interference coherence coefficient of each pixel is calculated based on the interference image pairs to obtain the interference coherence coefficient map; Calculate the average coherence coefficient for each interferometric coherence coefficient image; The interferometric coherence maps are categorized by month based on the acquisition date of the main image, and the overall average coherence coefficient and the monthly average coherence coefficient for each month are calculated; the overall average coherence coefficient is the mean of the average coherence coefficients of all interferometric coherence maps. The interferometric coherence coefficient map is divided into high coherence months and low coherence months on a monthly basis. Months with a monthly average coherence coefficient greater than the total average coherence coefficient are classified as high coherence months, and months with a monthly average coherence coefficient less than the total average coherence coefficient are classified as low coherence months. Interferometric pairs within high-coherence months are selected using a high average coherence coefficient as the threshold, and interferometric pairs within low-coherence months are selected using a low average coherence coefficient as the threshold. The selected interferometric pairs are used for time-series InSAR analysis. The high average coherence coefficient is the mean of the average coherence coefficients of all interferometric coherence coefficient maps within the high-coherence months, and the low average coherence coefficient is the mean of the average coherence coefficients of all interferometric coherence coefficient maps within the low-coherence months.

2. The method as described in claim 1, characterized in that, It also includes calculating the interference coherence coefficient for each pixel using the following formula: In the formula, λ (i,j) is the interferometric coherence coefficient at pixel (i,j), Q and S are the acquired SAR single-look complex images, namely the master image and the slave image, respectively, * indicates complex conjugate multiplication, m and n are the local window sizes used to calculate the coherence coefficient, and (i,j) represents the position of the pixel.

3. The method as described in claim 1, characterized in that, It also includes calculating the average coherence coefficient of each interferometric coherence coefficient map using the following formula: In the formula, λ avg λ is the average coherence coefficient of the interferometric coherence coefficient map, W and I are the width and length of the image, respectively, (i,j) represents the position of the pixel, and λ is the average coherence coefficient of the interferometric coherence coefficient map. (i,j) It is the interference coherence coefficient at pixel (i,j).

4. The method as described in claim 1, characterized in that, Also includes: The overall average coherence coefficient is calculated using the following formula: In the formula, N is the number of all interferometric coherence coefficient maps, and λ all It is the total average coherence coefficient, λ avg It is the average coherence coefficient of the interferometric coherence coefficient diagram; The monthly average coherence coefficient is calculated using the following formula: In the formula, M is the number of interferometric coherence coefficient maps per month, and λ month It is the monthly average coherence coefficient, λ avg It is the average coherence coefficient of the interference coherence coefficient diagram.

5. The method as described in claim 1, characterized in that, This also includes calculating the high average coherence coefficient using the following formula: In the formula, H represents the number of all interferometric coherence coefficient maps for the highly coherent month, and λ high For a high average coherence coefficient, λ avg It is the average coherence coefficient of the interference coherence coefficient diagram.

6. The method as described in claim 1, characterized in that, This also includes calculating the low average coherence coefficient using the following formula: In the formula, L represents the number of all interferometric coherence coefficient maps for the low-coherence month, and λ low For low average coherence coefficient, λ avg It is the average coherence coefficient of the interference coherence coefficient diagram.

7. A device for selecting temporal InSAR interferometric image pairs, characterized in that, include: The acquisition unit is used to acquire synthetic aperture radar SAR single-look complex images covering the study area during the study period; The interferometric image pair determination unit is used to pair SAR single-look complex images with a preset time baseline as a threshold to obtain several interferometric image pairs. The interference coherence coefficient map determination unit is used to calculate the interference coherence coefficient of each pixel based on the interference image pair to obtain the interference coherence coefficient map; The coherence coefficient calculation unit is used to calculate the average coherence coefficient of each interferometric coherence coefficient image; The classification calculation unit is used to classify the interferometric coherence coefficient maps by month according to the acquisition date of the main image, and calculate the total average coherence coefficient and the monthly average coherence coefficient for each month; the total average coherence coefficient is the mean of the average coherence coefficients of all interferometric coherence coefficient maps; The coherence month determination unit is used to classify the interferometric coherence coefficient map into high coherence months and low coherence months on a monthly basis. Months with a monthly average coherence coefficient greater than the total average coherence coefficient are classified as high coherence months, and months with a monthly average coherence coefficient less than the total average coherence coefficient are classified as low coherence months. The selection unit is used to select interferometric image pairs within high-coherence months using a high average coherence coefficient as a threshold, and to select interferometric image pairs within low-coherence months using a low average coherence coefficient as a threshold. The selected interferometric image pairs are used for time-series InSAR analysis. The high average coherence coefficient is the mean of the average coherence coefficients of all interferometric coherence coefficient maps within high-coherence months, and the low average coherence coefficient is the mean of the average coherence coefficients of all interferometric coherence coefficient maps within low-coherence months.

8. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method of any one of claims 1 to 6.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method of any one of claims 1 to 6.

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