CN115061136B - SAR image-based river and lake shoreline change point detection method and system - Google Patents
SAR image-based river and lake shoreline change point detection method and system Download PDFInfo
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- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
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Abstract
The invention discloses a river and lake shoreline change point detection method and system based on SAR images, which adopt high-resolution SAR image interference pairs in different periods to generate a coherence coefficient map, utilize the characteristics of different features with different coherence to make difference on the coherence coefficient map for two years, acquire a coherence coefficient difference map, extract suspected change point map spots of the river and lake shoreline by a threshold method, and verify by combining high-resolution visible light images, so as to timely master the change condition of the river and lake shoreline and provide powerful support for treatment. The SAR image adopted by the technology is not affected by weather conditions, can normally acquire images like the daytime at night, and has a stable data source; and researching the phase coherence change of SAR images of different years by utilizing the phase information contained in the SAR image data, so as to realize automatic monitoring of the change point of the river and lake shoreline.
Description
Technical Field
The invention relates to the technical field of river shoreline monitoring, in particular to a river and lake shoreline change point detection method and system based on SAR images.
Background
For the change monitoring of the river, lake and shoreline, the traditional method is based on manual inspection of vehicles and vessels in a management range, and the method has large workload and is easy to cause untimely and incomplete inspection results; with the development of remote sensing technology, at present, a high-resolution optical remote sensing image is mostly applied to find a change point map spot by means of manual visual interpretation, and manual inspection is assisted to perform investigation, so that timeliness of inspection results is guaranteed, working efficiency is improved, but the method is still limited by manual subjective judgment, and extreme weather such as overcast and rainy, haze and the like can influence an optical remote sensing imaging effect.
Disclosure of Invention
Therefore, the invention provides a river and lake shoreline change point detection method and system based on SAR images, which are used for solving the problems that the existing river and lake shoreline change monitoring method is limited by artificial subjective judgment, and extreme weather such as overcast, rainy, haze and the like can influence the optical remote sensing imaging effect.
In order to achieve the above object, the present invention provides the following technical solutions:
according to a first aspect of an embodiment of the present invention, a method for detecting a change point of a river and lake shoreline based on an SAR image is provided, the method comprising:
carrying out coherence computation based on SAR image data of river and lake shorelines in different periods, obtaining coherence coefficient graphs in different periods, and carrying out difference to obtain a coherence coefficient difference graph;
and extracting a change point map spot from the coherence coefficient difference map according to a preset threshold interval.
Further, the coherence computation is performed based on the SAR image data of different periods, so as to obtain coherence coefficient diagrams of different periods, which specifically comprise:
and obtaining coherence coefficient graphs of different periods according to the high-resolution SAR interference pairs of different periods, wherein SAR image data of different years are needed to be adjacent month image data.
Further, the method further comprises threshold analysis, specifically comprising:
selecting reference data, wherein the reference data comprises ground change pattern spots drawn through field investigation in the past year, and front-and-back image change pattern spots drawn through optical image contrast in the past year;
and superposing the reference data serving as sample data on a coherence coefficient difference map, analyzing coherence characteristics of the position of the image corresponding to the variation map spot, and statistically analyzing a coherence coefficient difference range of the position corresponding to the variation map spot, and setting a threshold interval according to the coherence coefficient difference range.
Further, extracting a variogram spot from the coherence coefficient difference map specifically includes:
extracting grids in the threshold range of the coherence coefficient difference map by using an ROI wave band threshold extraction tool, and classifying according to different threshold ranges to obtain a change heat point map spot.
Further, the method further comprises: verifying the extraction result, specifically comprising the following steps:
and (3) based on the extracted change pattern spots, overlapping and comparing the high-resolution optical images of different years, and verifying whether the corresponding positions of the pattern spots extracted automatically are actually changed.
Further, the method further comprises:
and comparing the erroneously extracted and the missed extracted pattern spots according to the verification result, summarizing the coherence features of the corresponding positions, and optimizing the extraction result.
Further, the method further comprises:
preprocessing SAR image data, including: baseline estimation, interference and interference flattening, adaptive filtering.
According to a second aspect of an embodiment of the present invention, there is provided a system for detecting a change point of a river and lake shoreline based on a SAR image, the system comprising:
the coherence coefficient difference value diagram acquisition module is used for carrying out coherence computation based on SAR image data of river and lake shoreline in different periods, acquiring coherence coefficient diagrams in different periods, and carrying out difference to obtain the coherence coefficient difference value diagram;
and the change point map spot extraction module is used for extracting the change point map spot from the coherence coefficient difference map according to a preset threshold interval.
Further, the system also comprises a threshold analysis module, which is specifically configured to:
selecting reference data, wherein the reference data comprises ground change pattern spots drawn through field investigation in the past year, and front-and-back image change pattern spots drawn through optical image contrast in the past year;
and superposing the reference data serving as sample data on a coherence coefficient difference map, analyzing coherence characteristics of the position of the image corresponding to the variation map spot, and statistically analyzing a coherence coefficient difference range of the position corresponding to the variation map spot, and setting a threshold interval according to the coherence coefficient difference range.
Further, the system also comprises a result analysis module, which is specifically used for:
and (3) based on the extracted change pattern spots, overlapping and comparing the high-resolution optical images of different years, and verifying whether the corresponding positions of the pattern spots extracted automatically are actually changed.
The invention has the following advantages:
according to the river and lake shoreline change point detection method and system based on the SAR image, the high-resolution SAR image interference pair in different periods is adopted to generate the coherence coefficient map, the two-year coherence coefficient map is differed by utilizing the characteristics of different features with different coherence, the coherence coefficient difference map is obtained, the suspected change point map of the river and lake shoreline is extracted by a threshold method, the high-resolution visible light image is combined for verification, the change condition of the river and lake shoreline is mastered in time, a powerful support is provided for treatment, and the accuracy, the comprehensiveness and the timeliness of river and lake shoreline change monitoring are ensured. The SAR image adopted by the technology is not affected by weather conditions, can normally acquire images like the daytime at night, and has a stable data source; and researching the phase coherence change of SAR images of different years by utilizing the phase information contained in the SAR image data, so as to realize automatic monitoring of the change point of the river and lake shoreline.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It will be apparent to those of ordinary skill in the art that the drawings in the following description are exemplary only and that other implementations can be obtained from the extensions of the drawings provided without inventive effort.
Fig. 1 is a schematic flow chart of a method for detecting a change point of a river and lake shoreline based on a SAR image according to embodiment 1 of the present invention;
fig. 2 is a schematic diagram of a research area in a method for detecting a change point of a river and lake shoreline based on a SAR image according to embodiment 1 of the present invention;
fig. 3 is a schematic flow chart of a specific implementation of a method for detecting a change point of a river and lake shoreline based on a SAR image according to embodiment 1 of the present invention;
fig. 4 is a 2019 year coherence coefficient diagram in a method for detecting a change point of a river and lake shoreline based on a SAR image according to embodiment 1 of the present invention;
fig. 5 is a 2020 year coherence coefficient diagram in a method for detecting a change point of a river and lake shoreline based on a SAR image according to embodiment 1 of the present invention;
fig. 6 is a diagram of a difference value of coherence coefficients in 2019-2020 in a method for detecting a change point of a river and lake shoreline based on a SAR image according to embodiment 1 of the present invention;
fig. 7 is a difference diagram of coherence coefficients corresponding to newly added building pattern spots in 2020 and corresponding to 2019 high-resolution optical images and 2020 high-resolution optical images in the method for detecting a change point of a river and lake shoreline based on an SAR image according to the embodiment 1 of the present invention;
fig. 8 is a diagram of a difference value of coherence coefficients corresponding to a reduction of building pattern spots in 2020 and corresponding to a 2019 high-resolution optical image and a 2020 high-resolution optical image in the method for detecting a change point of a river and lake shoreline based on a SAR image according to embodiment 1 of the present invention.
Detailed Description
Other advantages and advantages of the present invention will become apparent to those skilled in the art from the following detailed description, which, by way of illustration, is to be read in connection with certain specific embodiments, 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 be within the scope of the invention.
Example 1
As shown in fig. 1, this embodiment proposes a method for detecting a change point of a river and lake shoreline based on a SAR image, where the method includes:
s100, carrying out coherence computation based on SAR image data of river and lake shorelines in different periods, obtaining coherence coefficient graphs in different periods, and carrying out difference to obtain a coherence coefficient difference graph;
and S200, extracting a change point map spot from the coherence coefficient difference map according to a preset threshold value interval.
In this embodiment, the Jiangsu section of the Yangtze river is selected as the research area, and the change points of 2019-2020 in the Yangtze river management range line are extracted, and the research range is shown in fig. 2. The specific implementation process is as shown in fig. 3:
(1) Data download
In the data preparation stage, when high-resolution SAR interference image pairs in different periods are downloaded, the same-year images need to be guaranteed to have short time intervals and small space base lines in the downloading process so as to reduce the coherent influence of time and space, and SAR image data in different years need to be adjacent month image data to guarantee the similarity of vegetation coverage.
And selecting 4-year-4 SAR image data of Sentinel_1A satellites 2019-03-18, 2019-04-23, 2020-03-24 and 2020-04-17 as research data, and referencing the DEM as ASTER GDEM M resolution digital elevation data.
TABLE 1 Sentinel-1 data base parameters
(2) Data preprocessing
The sensor positions of SAR images in different periods are not consistent during imaging, so that position offset exists between the same-name points of the images, the images need to be precisely registered before interferometry, and an interference image is generated from the registered images; the application of the data processing methods such as interference leveling, self-adaptive filtering and the like is to remove the flat ground phase difference and reserve the elevation phase difference in the interference diagram, then the coherence coefficient diagram is obtained through coherence calculation and combined with geocoding, and finally the coherence coefficient difference diagram is obtained through calculating the coherence coefficient diagrams of different years by using a difference method.
SAR data of 2019-03-18 and 2020-03-24 are taken as main images, SAR data of 2019-4-23 and 2020-4-17 are taken as auxiliary images, baseline estimation is carried out on the main images and the auxiliary images by using Saracape software to evaluate the quality of interference pairs, the interferometry of data is guaranteed, interference and interference flattening are carried out on images of the same year 2, coherence calculation is carried out by using a formula (1), a 2019 and 2020 coherence coefficient diagram is obtained, as shown in fig. 4 and 5, and finally a coherence coefficient difference diagram is calculated by using a bandmath tool, as shown in fig. 6.
Wherein S is 1 And S is equal to 2 For the filtered single vision complex SAR image, x represents the conjugate complex, ρ represents the coherence coefficient, its value is between 0 and 1, 0 represents the incoherence, and 1 represents the safety coherence.
(3) Threshold analysis
Different ground features have different coherence characteristics, the coherence of artificial buildings such as buildings, factories and steel plate houses is generally higher than that of natural vegetation, bare land and the like, through the characteristics, a coherence coefficient difference image can be utilized, a change pattern spot drawn based on field investigation and partial optical images is used as sample data, a sample pattern spot is sampled in a vectorization mode, the sample pattern spot is superimposed on the coherence coefficient difference image, the interference coherence characteristics of different ground features are judged, the coherence coefficient difference range of the position corresponding to the change pattern spot is obtained through statistical analysis, a set threshold interval is used as a basis, grids in the coherence coefficient difference image threshold range are extracted by using an ROI wave band threshold extracting tool, and the change pattern spot is classified according to different threshold ranges.
In this embodiment, in combination with earlier-stage reference data, including ground variation image spots drawn through field investigation over the past year, and earlier-stage image variation image spots drawn through optical image contrast over the past year, reference data is used as sample data, superimposed to a coherence coefficient difference map, coherence characteristics of image positions corresponding to the image spots are analyzed, it is summarized that when a new building is found in the next year compared with the previous year, the coherence coefficient difference at the position of the variation point corresponding to the image spot is between 0.15 and 1, when a demolished building is found in the next year compared with the previous year, the coherence coefficient difference at the position of the variation point corresponding to the image spot is between-1 and-0.15, based on the threshold interval obtained by the generalization, a grid and vector image spot within the threshold range of the whole coherence coefficient difference map is extracted in batch by using a region of interest (ROI) band threshold value extracting tool.
The partial extraction results are shown in fig. 7 and 8, the A, B image spots are newly added buildings in 2020, the C, D image spots are reduced buildings in 2020, and the corresponding 2019 high-resolution optical images and 2020 high-resolution optical images are shown in the figures.
(4) Analysis of results
The threshold range selection of the change pattern spot is obtained according to manual experience, the change pattern spot is required to be extracted, the comparison verification is carried out on the high-resolution visible light images corresponding to the front and back stages, the effectiveness of the extraction result is analyzed, meanwhile, the pattern spots which are extracted in error and are not extracted are compared, the coherence characteristics of the corresponding positions are summarized, and the extraction result is optimized.
In this embodiment, the high-resolution optical image refers to a satellite image obtained by remote sensing of visible light, and the spatial resolution is 0.5 m, so that the ground feature on the image can be intuitively browsed. Based on the automatically extracted changing pattern spots of the SAR image, the high-resolution optical images of different years are subjected to superposition comparison to verify whether the corresponding positions of the automatically extracted pattern spots are actually changed.
Example 2
Corresponding to the above embodiment 1, this embodiment proposes a river and lake shoreline change point detection system based on SAR images, which includes:
the coherence coefficient difference value diagram acquisition module is used for carrying out coherence computation based on SAR image data of river and lake shoreline in different periods, acquiring coherence coefficient diagrams in different periods, and carrying out difference to obtain the coherence coefficient difference value diagram;
and the change point map spot extraction module is used for extracting the change point map spot from the coherence coefficient difference map according to a preset threshold interval.
Further, the system also comprises a threshold analysis module, which is specifically configured to:
selecting reference data, wherein the reference data comprises ground change pattern spots drawn through field investigation in the past year, and front-and-back image change pattern spots drawn through optical image contrast in the past year;
and superposing the reference data serving as sample data on a coherence coefficient difference map, analyzing coherence characteristics of the position of the image corresponding to the variation map spot, and statistically analyzing a coherence coefficient difference range of the position corresponding to the variation map spot, and setting a threshold interval according to the coherence coefficient difference range.
Further, the system also comprises a result analysis module, which is specifically used for:
and (3) based on the extracted change pattern spots, overlapping and comparing the high-resolution optical images of different years, and verifying whether the corresponding positions of the pattern spots extracted automatically are actually changed.
The functions executed by each module in the river and lake shore line change point detection system based on the SAR image provided by the embodiment of the invention are described in detail in the above embodiment 1, so that redundant description is omitted here.
While the invention has been described in detail in the foregoing general description and specific examples, it will be apparent to those skilled in the art that modifications and improvements can be made thereto. Accordingly, such modifications or improvements may be made without departing from the spirit of the invention and are intended to be within the scope of the invention as claimed.
Claims (7)
1. A method for detecting a river and lake shoreline change point based on an SAR image, the method comprising:
carrying out coherence computation based on SAR image data of river and lake shorelines in different periods, obtaining coherence coefficient graphs in different periods, and carrying out difference to obtain a coherence coefficient difference graph;
extracting a change point map spot from the coherence coefficient difference map according to a preset threshold interval;
based on SAR image data of different periods, carrying out coherence computation to obtain coherence coefficient diagrams of different periods, wherein the method specifically comprises the following steps:
obtaining coherence coefficient graphs of different periods according to the high-resolution SAR interference pairs of different periods, wherein SAR image data of different years are needed to be adjacent month image data;
extracting a variation point map spot from the coherence coefficient difference map specifically includes:
extracting grids in a threshold range of the coherence coefficient difference value diagram by using an ROI wave band threshold extracting tool, and classifying according to different threshold ranges to obtain a change heat point diagram spot;
verifying the extraction result, specifically comprising the following steps:
and (3) based on the extracted change pattern spots, overlapping and comparing the high-resolution optical images of different years, and verifying whether the corresponding positions of the pattern spots extracted automatically are actually changed.
2. The method for detecting a river and lake shoreline change point based on an SAR image according to claim 1, wherein the method further comprises threshold analysis, and specifically comprises:
selecting reference data, wherein the reference data comprises ground change pattern spots drawn through field investigation in the past year, and front-and-back image change pattern spots drawn through optical image contrast in the past year;
and superposing the reference data serving as sample data on a coherence coefficient difference map, analyzing coherence characteristics of the position of the image corresponding to the variation map spot, and statistically analyzing a coherence coefficient difference range of the position corresponding to the variation map spot, and setting a threshold interval according to the coherence coefficient difference range.
3. The SAR image-based river and lake shoreline change point detection method of claim 1, further comprising:
and comparing the erroneously extracted and the missed extracted pattern spots according to the verification result, summarizing the coherence features of the corresponding positions, and optimizing the extraction result.
4. The SAR image-based river and lake shoreline change point detection method of claim 1, further comprising:
preprocessing SAR image data, including: baseline estimation, interference and interference flattening, adaptive filtering.
5. A river-lake shoreline change point detection system based on SAR images, the system comprising:
the coherence coefficient difference value diagram acquisition module is used for carrying out coherence computation based on SAR image data of river and lake shoreline in different periods, acquiring coherence coefficient diagrams in different periods, and carrying out difference to obtain the coherence coefficient difference value diagram;
the change point map spot extraction module is used for extracting change point map spots from the coherence coefficient difference map according to a preset threshold interval;
based on SAR image data of different periods, carrying out coherence computation to obtain coherence coefficient diagrams of different periods, wherein the method specifically comprises the following steps:
obtaining coherence coefficient graphs of different periods according to the high-resolution SAR interference pairs of different periods, wherein SAR image data of different years are needed to be adjacent month image data;
extracting a variation point map spot from the coherence coefficient difference map specifically includes:
extracting grids in a threshold range of the coherence coefficient difference value diagram by using an ROI wave band threshold extracting tool, and classifying according to different threshold ranges to obtain a change heat point diagram spot;
verifying the extraction result, specifically comprising the following steps:
and (3) based on the extracted change pattern spots, overlapping and comparing the high-resolution optical images of different years, and verifying whether the corresponding positions of the pattern spots extracted automatically are actually changed.
6. The SAR image-based river and lake shoreline change point detection system of claim 5, further comprising a threshold analysis module, specifically configured to:
selecting reference data, wherein the reference data comprises ground change pattern spots drawn through field investigation in the past year, and front-and-back image change pattern spots drawn through optical image contrast in the past year;
and superposing the reference data serving as sample data on a coherence coefficient difference map, analyzing coherence characteristics of the position of the image corresponding to the variation map spot, and statistically analyzing a coherence coefficient difference range of the position corresponding to the variation map spot, and setting a threshold interval according to the coherence coefficient difference range.
7. The SAR image-based river and lake shoreline change point detection system of claim 6, further comprising a result analysis module, specifically configured to:
and (3) based on the extracted change pattern spots, overlapping and comparing the high-resolution optical images of different years, and verifying whether the corresponding positions of the pattern spots extracted automatically are actually changed.
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