SAR (Synthetic Aperture Radar) image interpretation method, device and equipment and storage medium

Abstract

The invention discloses an SAR (Synthetic Aperture Radar) image interpretation method, device and equipment and a storage medium, and relates to the technical field of image data processing. The method comprises the following steps: acquiring an SAR image of a disaster area and imaging information of the SAR image, wherein the imaging information at least indicates imaging time, data resolution, a lifting track, a side view direction and an incident angle; processing the SAR image by using image processing software to obtain a corrected image of the SAR image; on the basis of image features associated with image reference features in the corrected image, the corrected image is interpreted according to the imaging information, an interpretation result is obtained, and the image reference features indicate common image features convenient to interpret in the SAR image; the interpretation result is used for identifying the SAR image so as to draw a plotted image, the plotted image indicates the disaster situation of the disaster area, and the disaster situation at least comprises the specific position of the disaster area, the disaster range, the position and size of disaster facilities and multiple pieces of information of the surrounding mountain, river and road positions. According to the embodiment of the invention, the interpretation difficulty of the SAR image can be reduced.

Description

TECHNICAL FIELD

[0001] Example embodiments of the present disclosure generally relate to the technical field of image data processing, and in particular, to a SAR image interpretation method, device, equipment and computer readable storage medium. BACKGROUND

[0002] SAR (Synthetic Aperture Radar) is an active remote sensing technology, which mainly uses microwaves for imaging, and obtains ground information by transmitting microwave signals and receiving their reflected signals. Due to its characteristics of actively emitting electromagnetic energy, it is more sensitive to the physical properties and geometric shapes of the ground, and can be widely used in geological monitoring, especially in monitoring geological disasters.

[0003] For some places where geological disasters have occurred, there may be continuous rainy weather, which makes optical satellites unable to image, and SAR is the only reliable satellite data source. However, SAR images are obtained by coherent accumulation of complex electromagnetic scattering, and contain complex interactions between electromagnetic waves and the environment and targets, so SAR image interpretation is difficult. Whether SAR images can be accurately interpreted will have a great impact on disaster monitoring, disaster damage assessment, post-disaster rescue and post-disaster reconstruction.

[0004] The information disclosed in this Background section is only for the purpose of increasing the understanding of the general background of the application, and should not be taken as an acknowledgment or any form of suggestion that this information forms prior art that is already known to those skilled in the art. SUMMARY

[0005] In a first aspect of the present disclosure, a SAR image interpretation method is provided. The method comprises: obtaining a SAR image of a disaster area and imaging information of the SAR image, the imaging information at least indicating imaging time, data resolution, ascending / descending track, side-looking direction and incidence angle; processing the SAR image by using an image processing software to obtain a corrected image of the SAR image; interpreting the corrected image based on image features associated with image reference features in the corrected image according to the imaging information to obtain an interpretation result, the image reference features indicating common image features in the SAR image that are easy to interpret; and identifying the SAR image by using the interpretation result to draw a plot image, the plot image indicating a disaster situation of the disaster area, the disaster situation at least including multiple information of specific location of the disaster area, disaster range, disaster facility location and size, and surrounding mountain, river and road locations.

[0006] In a second aspect of the present disclosure, an apparatus for SAR image interpretation is provided. The apparatus comprises: an obtaining module configured to obtain a SAR image of a disaster area and imaging information of the SAR image, the imaging information at least indicating imaging time, data resolution, ascending / descending track, side-looking direction and incidence angle; a processing module configured to process the SAR image by using an image processing software to obtain a corrected image of the SAR image; an interpreting module configured to interpret the corrected image based on image features associated with image reference features in the corrected image according to the imaging information to obtain an interpretation result, the image reference features indicating common image features in the SAR image that are convenient for interpretation; and a plotting module configured to mark the SAR image by using the interpretation result to plot a plot image, the plot image indicating a disaster situation of the disaster area, the disaster situation at least including multiple information of specific location of the disaster area, disaster range, disaster facility location and size, and surrounding mountain, river and road locations.

[0007] In a third aspect of the present disclosure, a computing device is provided. The device comprises at least one processing unit; and at least one memory coupled to the at least one processing unit and storing instructions for execution by the at least one processing unit. The instructions, when executed by the at least one processing unit, cause the device to perform the method of the first aspect.

[0008] In a fourth aspect of the present disclosure, a computer-readable storage medium is provided. The computer-readable storage medium has stored thereon a computer program, which is executable by a processor to implement the method of the first aspect.

[0009] It should be understood that the content described in this section is not intended to limit the key features or important features of the embodiments of the present disclosure, nor is it used to limit the scope of the present disclosure. Other features of the present disclosure will become apparent through the following description. BRIEF DESCRIPTION OF DRAWINGS

[0010] The above and other features, advantages and aspects of embodiments of the present disclosure will become more apparent by describing in detail some embodiments thereof with reference to the annexed drawings in which:

[0011] Figure 1 A schematic diagram showing an example environment in which embodiments according to the present disclosure can be implemented is shown;

[0012] Figure 2 A flow chart showing an example interpretation process of a SAR image according to some embodiments of the present disclosure is shown;

[0013] Figure 3 A flow chart showing an example interpretation process of a SAR image according to some embodiments of the present disclosure is shown;

[0014] Figure 4 A schematic diagram showing an example structure of perspective shrink according to some embodiments of the present disclosure is shown;

[0015] Figure 5 A schematic diagram showing an example structure of overlay mask according to some embodiments of the present disclosure is shown;

[0016] Figure 6 A schematic diagram showing a SAR image according to some embodiments of the present disclosure is shown;

[0017] Figure 7 A schematic diagram showing an interpretation result according to some embodiments of the present disclosure is shown;

[0018] Figure 8 A schematic block diagram of an example apparatus for SAR image interpretation according to some embodiments of the present disclosure is shown; and

[0019] Figure 9 A block diagram of a computing device capable of implementing embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0020] Embodiments of the present disclosure will be described below in greater detail with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it is understood that the present disclosure can be embodied in various forms and should not be interpreted as being limited to the embodiments set forth herein; rather, these embodiments are provided so as to more completely and thoroughly understand the present disclosure. It is understood that the drawings and embodiments of the present disclosure are for exemplary purposes only and are not intended to limit the scope of protection of the present disclosure.

[0021] It is noted that the headings provided herein are not limitations of the disclosure. Various embodiments are described throughout this document and any type of embodiment can be included under any heading. Moreover, embodiments described in any heading can be combined with any other embodiment described in the same heading and / or in a different heading in any manner.

[0022] In the description of embodiments of the present disclosure, the term "includes" and its variants are to be read as open-ended terms that mean "includes, but is not limited to." The term "based on" is to be read as "based, at least in part, on." The term "one embodiment" or "an embodiment" are to be read as "at least one embodiment." The term "some embodiments" is to be read as "at least some embodiments." Other explicit and implicit definitions can also be included below. The terms "first," "second," etc. can refer to different or same objects. Other explicit and implicit definitions can also be included below.

[0023] The data of the user, the acquisition and / or use of the data, etc. can be involved in the embodiments of the present disclosure. These aspects comply with the corresponding laws and regulations and relevant provisions. In the embodiments of the present disclosure, the collection, acquisition, processing, processing, forwarding, use, etc. of all data are performed on the premise that the user is aware of and confirms. Accordingly, when implementing the embodiments of the present disclosure, the type, use range, use scenario, etc. of the data or information that can be involved should be informed to the user and the authorization of the user should be obtained through appropriate means according to the relevant laws and regulations. The specific informing and / or authorization manner can vary according to the actual situation and application scenario, and the scope of the present disclosure is not limited in this aspect.

[0024] In the present specification and embodiments, if the scheme involves processing of personal information, the processing is performed on the premise of having a legal basis (for example, obtaining the consent of the subject of the personal information, or being necessary for performing a contract, etc.) and is performed only within the prescribed or agreed range. The user refuses to process personal information other than the necessary information required for the basic function, which does not affect the user's use of the basic function.

[0025] As mentioned above, for some places where geological disasters have occurred, there can be continuous rainy weather, which makes it impossible for optical satellites to image, and SAR is the only reliable satellite data source. However, since SAR images are obtained by coherent accumulation of complex electromagnetic scattering, they contain complex interactions between electromagnetic waves and the environment and targets, so it is difficult to interpret SAR images. Whether SAR images can be accurately interpreted will have a great impact on disaster monitoring, disaster damage assessment, post-disaster rescue and post-disaster reconstruction.

[0026] Embodiments of the present disclosure provide a scheme of a SAR image interpretation method. The scheme includes: acquiring a SAR image of a disaster area and imaging information of the SAR image, the imaging information at least indicating imaging time, data resolution, ascending / descending track, side-looking direction and incidence angle; processing the SAR image by using an image processing software to obtain a corrected image of the SAR image; interpreting the corrected image according to the imaging information based on image features associated with image reference features in the corrected image to obtain an interpretation result, the image reference features indicating common image features in the SAR image that are easy to interpret; and identifying the SAR image by using the interpretation result to draw a plot image, the plot image indicating a disaster situation of the disaster area, the disaster situation at least including multiple information of a specific position of the disaster area, a disaster range, a disaster facility position and size, and a surrounding mountain, river and road position.

[0027] In this way, the embodiments of the present disclosure realize the interpretation of the corrected image by identifying the image features in the corrected image that can reflect facilities such as buildings and roads, in combination with the imaging information. The SAR image with a relatively high difficulty of interpretation is converted into a convenient and quantifiable feature through the above manner, which reduces the difficulty of SAR image interpretation, and meanwhile, the obtained interpretation result can also contain accurate results.

[0028] Various example implementations of the solution will be described in detail below with further reference to the accompanying drawings.

[0029] Example Environment

[0030] Figure 1 A schematic diagram of an example environment 100 in which embodiments of the present disclosure can be implemented is shown. As shown, the example environment 100 can include an electronic device 110 and an image acquisition device 120. Figure 1

[0031] In this example environment 100, the image acquisition device 120 can be configured to acquire SAR remote sensing images. As an example, the image acquisition device 120 can be a SAR satellite.

[0032] In some embodiments, the electronic device 110 is in communication with the image acquisition device 120. The electronic device 110 can be any type of mobile terminal, fixed terminal, or portable terminal including a mobile handset, a desktop computer, a laptop computer, a notebook computer, a netbook computer, a tablet computer, a media computer, a multimedia tablet, a palmtop computer, a portable gaming terminal, a VR / AR device, a Personal Communication System (PCS) device, a personal navigation device, a Personal Digital Assistant (PDA), an audio / video player, a digital camera / camcorder, a positioning device, a television receiver, a radio broadcast receiver, an electronic book device, a game device, or any combination thereof, including an accessory or peripheral device for any of these devices, or any combination thereof. In some embodiments, the electronic device 110 can also support any type of interface to a user (such as "wearable" circuitry, etc.).

[0033] It should be understood that the structure and function of the various elements in the environment 100 are described for illustrative purposes only, without implying any limitation on the scope of the present disclosure.

[0034] Some example embodiments of the present disclosure will be described below with further reference to the accompanying drawings.

[0035] Example Process

[0036] The following will be described below with further reference to the accompanying drawings. Figure 2 and​Figure 3 This describes the specific interpretation process of SAR images. Figure 2 A flowchart of an example interpretation process 200 for SAR images according to some embodiments of the present disclosure is shown. Figure 3 A flowchart illustrating an example interpretation process 300 for SAR images according to some embodiments of the present disclosure is shown. Process 300 can be implemented at electronic device 110. Reference is made below. Figure 1 and Figure 2 To describe process 300.

[0037] like Figure 3 As shown in block 310, electronic device 110 acquires SAR images of the disaster-stricken area and SAR image imaging information. In some embodiments, the imaging information at least indicates the imaging time, data resolution, ascent / descent trajectory, side-view direction, and incident angle. The data resolution can be the image resolution or the resolution of other devices, etc.

[0038] In some embodiments, when a geological disaster occurs in a region, the affected area can be the area where the geological disaster occurred, or it can be the area where the geological disaster occurred and the area of ​​human activity. As an example, for earthquake disasters, since the epicenter may not necessarily be damaged, it is necessary to infer the affected area of ​​the earthquake based on the latitude and longitude of the epicenter, the direction of seismic wave movement, and the distribution of cities, villages and roads around the epicenter.

[0039] In some embodiments, the electronic device 110 can determine the affected area of ​​a geological disaster through open-source intelligence information. For example, the approximate area of ​​the geological disaster can be determined first by using a web search engine. This method can narrow down the scope to the town or village level. Then, by using open-source media intelligence such as text, images, and videos, and other software such as Google Earth, the specific location of the disaster can be further determined, thereby determining the vector of the affected area.

[0040] In some embodiments, when acquiring SAR images of a disaster-stricken area, the electronic device 110 can acquire SAR images through the image acquisition device 120. As an example, the image acquisition device 120 may be a SAR satellite.

[0041] In some embodiments, the process of acquiring SAR images of the disaster area by the electronic device 110 using the image acquisition device 120 can be to control the SAR satellite imaging by programming. Specifically, the electronic device 110 can query the satellite overflight time and orbit information, and control the SAR satellite to image in the spotlight imaging mode. The electronic device 110 acquires SAR images in this way, which can have the following advantages: when geological disasters occur in mountainous areas, by controlling the SAR satellite to move, the SAR images acquired by the SAR satellite can avoid phenomena such as mountain perspective shrinkage, overlap inversion, shadow, etc., thereby reducing the difficulty of SAR image interpretation. At the same time, the electronic device 110 can also control the SAR satellite to adjust the left and right side views according to the ascending and descending orbit information, so that the radar waves can illuminate the disaster area, thereby acquiring high-quality SAR remote sensing images.

[0042] In addition, in some other embodiments, SAR images of the disaster area can also be acquired by purchasing remote sensing data of commercial SAR satellites. As an example, it can be selected to purchase post-disaster high-resolution SAR remote sensing images at sub-meter level, or to purchase post-disaster high-resolution SAR remote sensing images at sub-meter level and pre-disaster SAR historical images.

[0043] In block 320, the electronic device 110 processes the SAR images using image processing software to obtain corrected images of the SAR images.

[0044] In some embodiments, the processing of the SAR images by the electronic device 110 can include a plurality of different processing processes, such as one or more of the processing steps of data import, multi-view processing, filtering processing, geographic coding, etc. The following will take a specific example to introduce each processing step.

[0045] In a specific example, when the electronic device 110 acquires the SAR images, data import is first performed. Data import is to import the original binary data file recorded by the satellite (usually in the format of CEOS, SAFE, raw, etc.) into the ENVI software environment. Since the data formats and parameters of different satellites are different, the original binary data file needs to be converted into an image file by configuring according to the type of the satellite. As an example, when configuring according to the type of the satellite, the polarization mode and / or imaging mode, etc. can be configured. Among them, the polarization mode is to specify the polarization state of radar wave transmission and reception (such as HH-horizontal transmission and horizontal reception, HV-horizontal transmission and vertical reception, VV-vertical transmission and vertical reception, VH-vertical transmission and horizontal reception). The imaging mode is to specify the imaging mode of the SAR (such as Stripmap-stripe mode, spotlight-spotlight mode, ScanSAR-scan mode, etc.).

[0046] Thereafter, the electronic device 110 performs a multi-look processing on the SAR image. The multi-look processing is to average a plurality of pixels in the azimuth direction (along the flight direction) and the range direction (perpendicular to the flight direction, i.e. the radar wave emission direction) of the imported generated image file, respectively. It can be appreciated that there is speckle noise in the SAR image, which is caused by the coherence of the radar wave and is presented as randomly distributed bright and dark spots on the image. The multi-look processing takes advantage of the randomness of the speckle noise, and by averaging a plurality of pixels, part of the random noise can be offset to improve the image quality and facilitate subsequent interpretation. As an example, this step can be implemented in the ENVI software.

[0047] Further, the electronic device 110 performs a filtering processing on the SAR image. The filtering processing is to apply a specific image filtering algorithm to the image after the multi-look processing. For example, Lee filtering can be used. Lee filtering is mainly based on the statistical characteristics (mainly mean and variance) of the local region (usually a small window, such as 5x5 or 7x7) of the image. Specifically, if the value of the center pixel of the window is considered to be a "uniform" region (small variance) in the local statistics, the filtering tends to be smoothed (taking the mean) to suppress noise. If the pixel value is considered to be an "edge" or "strong point target" (large variance) in the local statistics, the filtering will retain the original value of the pixel or make a small degree of modification. That is, Lee filtering can effectively reduce noise while preserving the boundaries of ground objects, linear features (roads, rivers), and important texture information (such as forest canopy, texture of urban building groups), thereby obtaining a SAR image with higher visual quality and more conducive to information extraction, to facilitate subsequent interpretation.

[0048] Finally, the electronic device 110 performs a geocoding on the SAR image. The geocoding is to convert the SAR image in the slant range coordinate system to an image in the standard geographic coordinate system (such as WGS84). Specifically, since the original SAR image coordinates are based on the slant distance from the radar antenna to the target. Therefore, the geocoding first converts it to the horizontal distance on the ground, and then converts the ground range coordinate system, i.e. the horizontal distance on the ground, to the latitude and longitude coordinates (such as WGS84) or the projection coordinates (such as UTM). At the same time, by combining with the DEM data, the terrain distortion can be eliminated to form an accurate SAR image to facilitate subsequent interpretation. As an example, this processing step can be implemented through the ENVI software.

[0049] However, it is worth noting that when the SAR image involves mountains, interference caused by the terrain slope and the radar incidence angle is likely to occur. That is, this situation mainly applies to SAR images taken by SAR satellites in geological disasters of the disaster type of mountain landslide or debris flow. This interference will increase the difficulty of interpreting the SAR image, and therefore, the SAR image needs to be corrected to obtain a corrected image.

[0050] In some embodiments, the electronic device 110 processes SAR images using image processing software to obtain a corrected SAR image, which can be achieved through the following process:

[0051] First, in response to a disaster type of landslide or debris flow, electronic device 110 determines imaging features contained in the SAR image. In some embodiments, the imaging features indicate interference caused by terrain slope and radar incident angle. As examples, imaging features may include perspective contraction, overlay inversion, and shadows. Perspective contraction means that the slope facing the radar is compressed; overlay inversion means that the mountain peak or high ground appears closer to the radar in the image than its actual location; shadows mean that the slope facing away from the radar has no signal at all.

[0052] In some embodiments, since different imaging features are corrected in different ways, the electronic device 110 can identify the imaging features contained in the SAR image by recognizing the SAR image processed by the image processing software, so as to correct the SAR image.

[0053] Then, electronic equipment 110 constructs a calibration model corresponding to the imaging features. It is understood that different imaging features require different correction methods, therefore different calibration models must be constructed for different imaging features. Of course, the calibration model applicable to each disaster-stricken area is also different. The following section uses different imaging features as examples to explain in detail the construction process of the corresponding calibration models.

[0054] In some embodiments, the specific process by which the electronic device 110 constructs a calibration model corresponding to the imaging features may include: in response to the imaging features being perspective-contracted, establishing a first calibration model, the first calibration model indicating the relationship between a first slant range and a first ground distance in the contracted area, the first calibration model including the radar platform height and a first elevation of the ground target relative to a reference surface; determining a first reference ground distance based on a first preset value of the first elevation according to the first calibration model; and correcting the first preset value based on the difference between the first reference ground distance and the first ground distance, so that the relationship between the first slant range and the first ground distance satisfies the error condition, thereby obtaining the calibration model.

[0055] like Figure 4 As shown, it can be understood that the principle of perspective contraction is that when the radar beam reaches the top, middle, and bottom of the slope at slopes R, respectively... T R M and R N Because of R T >R M >R N, the radar beam first illuminates the slope bottom and then illuminates the slope top, the slope bottom is imaged first and the slope top is imaged later, the slant range of the slope is displayed on the image as a distance ΔR1, ΔR1 is obviously smaller than the slope length L, thus the length of the slope is obviously shortened. In other words, in the geological disaster scene of the mountain landslide or debris flow, the mountain landslide area in the SAR image is smaller than the actual mountain landslide range. Moreover, the degree of perspective contraction is directly related to the terrain slope (θ) and the radar incidence angle (α) (α is the angle between the radar beam and the ground normal). For the upslope (the slope towards the radar), the smaller θ (the gentler the slope), the weaker the contraction; the larger θ (the steeper the slope), the more significant the contraction (when θ is close to α, the contraction reaches the maximum).

[0056] Based on this, a first calibration model can be established, i.e., the relationship between the first slant range R and the first ground range G indicating the contracted area. In some embodiments, the relationship between the first slant range R and the first ground range G can be expressed by the following relationship:

[0057]

[0058] wherein H is the radar platform height, α is the radar incidence angle, and h is the first elevation of the ground target relative to the reference surface.

[0059] It can be understood that in the above relationship, the first elevation h is not an explicit value, thus when determining the relationship between the first slant range R and the first ground range G, a first preset value of the first elevation can be first determined, and then the first preset value is substituted into the above relationship to determine the first reference ground range. In order to be able to determine the true value of the first elevation, the first reference ground range needs to be infinitely close to the first ground range G. Therefore, when there is a difference between the first reference ground range and the first ground range G, the size of the first preset value can be adjusted based on the difference between the first reference ground range and the first ground range G. The above steps of substituting the first preset value into the relationship between the first slant range R and the first ground range G and adjusting the first preset value based on the difference between the first reference ground range and the first ground range G can be repeatedly performed to derive the explicit relationship between the first slant range R and the first ground range G.

[0060] In some embodiments, the number of times of repeated execution of the step can be configured, or the condition for stopping iteration can be determined by pre-setting. As an example, the condition for stopping iteration can be an error condition, such as that the mapping error between the first slant range R and the first ground range G is less than 0.5 pixels. When the mapping error between the first slant range R and the first ground range G is less than 0.5 pixels, i.e., the error condition is met, iteration is not needed, and the first calibration model at this time is the required calibration model. Conversely, when the mapping error between the first slant range R and the first ground range G is not less than 0.5 pixels, i.e., the error condition is not met, iteration needs to be continued to reduce the mapping error between the first slant range R and the first ground range G.

[0061] In some embodiments, the specific process of the electronic device 110 constructing a calibration model corresponding to the imaging features may include: in response to the imaging features being overlayed, establishing a second calibration model, the second calibration model indicating the relationship between a second slant distance and a second ground distance in the overlay region, the second calibration model including a second elevation of the ground target relative to a reference surface; determining a second reference ground distance based on a second preset value of the second elevation according to the second calibration model; and correcting the second preset value based on the difference between the second reference ground distance and the second ground distance to obtain the calibration model.

[0062] like Figure 5 As shown, it can be understood that the principle of overlay inversion is that SAR images will exhibit overlay when depicting steep slopes with varying local terrain angles. The overlay at the top of a mountain has a closer slant distance than at the base, resulting in severe image distortion. When R... T <R M <R N In this scenario, the image of the mountaintop appears before the image of the base. The radar beam illuminates the ground at a certain angle of depression (α). When the terrain slope (θ) is greater than the radar depression angle (θ>α), nearby high points will be illuminated by the radar beam before distant low points, causing the echo signal of the high point to overlay the echo signal of the low point in the image, resulting in overlay. The slope range of this slope is shown as distance ΔR2 in the image. ΔR2 is obviously greater than the slope length L, therefore, the echo of the top of the slope appears before the bottom. This phenomenon makes the terrain features in the image appear to bend upwards. In other words, in geological disaster scenarios such as landslides or debris flows, the landslide area in the SAR image will be larger than the actual landslide area. Moreover, the degree of overlay is affected by many factors, including the radar incident angle, the slope and direction of the terrain, and the radar wavelength. The larger the incident angle or the steeper the terrain, the more severe the overlay phenomenon.

[0063] Based on this, a second calibration model can be established, which indicates the relationship between the second slope distance R and the second ground distance R0 of the overlapping area. In some embodiments, the relationship between the second slope distance R and the second ground distance R0 can be expressed by the following formula:

[0064]

[0065] Where α is the radar depression angle, R0 is the slant range of the radar to the ground reference point, and H is the second elevation of the ground target relative to the reference surface.

[0066] It can be understood that the second elevation H is not a definite value in the above relationship, and thus a second preset value of the second elevation can be determined first when determining the relationship between the second slant range R and the second ground range R0, and then the second preset value is substituted into the above relationship to determine the second reference ground range. In order to determine the real value of the second elevation, the second reference ground range needs to be infinitely close to the second ground range R0. Therefore, when there is a difference between the second reference ground range and the second ground range R0, the size of the second preset value can be adjusted based on the difference between the second reference ground range and the second ground range R0. The above steps of substituting the second preset value into the relationship between the second slant range R and the second ground range R0 and adjusting the second preset value based on the difference between the second reference ground range and the second ground range R0 can be repeatedly performed to derive the definite relationship between the second slant range R and the second ground range R0.

[0067] In some embodiments, the number of times of repeated execution of the steps can be configured, and the condition for stopping iteration can also be determined by pre-setting. As an example, the condition for stopping iteration can be an error condition, such as that the mapping error between the second slant range R and the second ground range R0 is less than 0.5 pixels. When the mapping error between the second slant range R and the second ground range R0 is less than 0.5 pixels, i.e., the error condition is met, iteration is not needed, and the second calibration model at this time is the required calibration model. Conversely, when the mapping error between the second slant range R and the second ground range R0 is not less than 0.5 pixels, i.e., the error condition is not met, iteration needs to be continued to reduce the mapping error between the second slant range R and the second ground range R0.

[0068] It can be understood that the disaster area caused by geological disasters such as landslides or mudslides involving mountains generally occurs only on one side of the mountain. At this time, if there is a shadow in the SAR image, it means that the SAR satellite collects the image of the other side of the mountain. In some embodiments, for such a shadow, the SAR satellite can be moved to a position where the radar wave can irradiate the side of the disaster area when the SAR image is acquired, so as to avoid the appearance of the shadow and reduce the difficulty of interpretation.

[0069] As shown in FIG. 13, the electronic device 110 obtains a SAR image of a disaster area, and then performs image processing on the SAR image to obtain a processed image. Figure 1 and Figure 2 As shown in FIG. 13, the electronic device 110 obtains a SAR image of a disaster area, and then performs image processing on the SAR image to obtain a processed image.

[0070] At block 330, the electronic device 110 interprets the corrected image according to the imaging information based on the image features associated with the image reference features in the corrected image, to obtain an interpretation result. In some embodiments, the image reference features indicate common image features in the SAR image that are easy to interpret. These common image features are features that are induced based on the SAR imaging principle. The SAR imaging principle, i.e., using a side-looking imaging mode (non-vertically observing the ground), relies on the emission, reflection and reception of electromagnetic waves and signal processing techniques, and mainly utilizes the synthetic aperture principle in space to form a radar photo with resolution through multiple focus reflections at corresponding spatial positions.

[0071] In some embodiments, the image reference features at least include a first reference tonal feature and a reference shadow feature indicating a building, and a second reference tonal feature indicating a road. In some other embodiments, the image reference features can also include features indicating the size, shape, tonal, location, activity, shadow, etc. of other facilities. The following takes buildings and roads as examples and makes a detailed description in combination with the SAR imaging principle.

[0072] For buildings, the tonal feature of the building in the SAR image will show obvious straight line or L-shaped bright line characteristics, because the roof of the building is usually smooth. When the radar wave irradiates to the roof, mirror reflection occurs, so the roof generally shows dark tonal. However, the wall of the building and the ground form a dihedral structure, which has a focusing effect on the electromagnetic signal, and will produce secondary scattering, i.e., in the SAR image, it appears as a linear structure with very high brightness, generally as a straight line or L-shaped fold line. This straight line or L-shaped fold line bright line structure is the first reference tonal feature of the building. The shadow feature of the building in the SAR image will also be highlighted. The radar electromagnetic wave propagates along a straight line, is blocked by the wall and roof of the building, and the side facing away from the radar cannot be irradiated by the electromagnetic wave, so the corresponding position cannot receive the echo, forming a shadow area. For buildings damaged after geological disasters, because the roof collapses, the wall collapses, and some are even flattened into ruins, the damaged building will show a diffuse bright color area without rules and tend to noise compared with normal buildings. For some buildings flattened into ruins, the scattered signal in the entire building collapse area is not blocked, so the satellite can receive the signal intensity of the area to be averaged; and the debris accumulated on the ground after the building collapse, the surface is very rough and irregular, which will produce a relatively strong reflection signal, and the radar wave shows bright color. The above shadow features are the reference shadow features of the building.

[0073] For roads, the hue feature of the road in the SAR image will show obvious dark hue, because the road surface is relatively smooth, similar to mirror reflection, most of the electromagnetic waves will be reflected parallel to the ground, only a small amount of energy returns to the SAR sensor, resulting in low return intensity, so it is usually represented as a darker area on the SAR image. The shape feature of the road in the SAR image will show obvious linear target characteristics, because the length of the road is much greater than the width, and the linearity is obvious. For the damaged road after the geological disaster, the linearity of the road in the SAR image is destroyed, and obvious gaps or interruptions appear, in addition, the damaged road surface becomes rough, which will have obvious changes in the hue feature on the SAR image. The above hue features are the second reference hue features of the road.

[0074] In some embodiments, in addition to using the above features, the interpretation of the SAR impact can also be combined with the imaging information. As an example, for the imaging time, it can be specific to the minute level, so as to accurately grasp the disaster situation at the specific imaging time; for the data resolution, it needs to be clear that it is 1 meter, 0.5 meter, or other resolution, so as to measure the length of the damaged facility in the image.

[0075] In some embodiments, the interpretation result can at least include the damaged length and the damaged area. By accurately calculating the damaged length and the damaged area of the building or road or other facility, people can further understand and evaluate the disaster situation of the disaster area.

[0076] In some embodiments, for buildings, the specific process of the electronic device 110 interpreting the corrected image according to the imaging information based on the image features associated with the image reference features in the corrected image to obtain the interpretation result can include:

[0077] First, the electronic device 110 identifies the strong line feature pixels in the image features, and determines the damaged length of the building based on the strong line feature pixels and the image resolution in the imaging information. Wherein, the image features associated with the image reference features in the corrected image are the features close to the image reference features in the corrected image, through which the damaged area of the building or road or other equipment can be determined.

[0078] In some embodiments, when the flight orbit direction of the SAR satellite is consistent with the house, the two are easy to form an angle reflection effect, thereby forming a strong line feature. At this time, the damaged length of the building can be determined based on the strong line feature. As an example, the damaged length of the building = strong line feature pixel x image resolution.

[0079] Then, the electronic device 110 identifies a first number of pixels of the damaged area of the building using a radar cross section measurement technique, and determines a damaged area of the building based on the first number of pixels and the image resolution. As an example, the damaged area of the building = the first number of pixels x the image resolution x the image resolution.

[0080] In some embodiments, for a road, the specific process of interpreting the corrected image according to the imaging information based on the image features associated with the image reference features in the corrected image to obtain an interpretation result can include:

[0081] First, the electronic device 110 identifies a linear target feature pixel in the image feature, and determines a damaged length of the road based on the linear target feature pixel and the image resolution in the imaging information.

[0082] In some embodiments, the linear target feature pixel is a linear feature that appears to have continuous gaps or interruptions, which can reflect a damaged road section. Based on these linear target features, the damaged length of the road can be determined. As an example, the damaged length of the road = the linear target feature pixel x the image resolution.

[0083] Then, the electronic device 110 identifies a second number of pixels of the damaged area of the road using a radar cross section measurement technique, and determines a damaged area of the road based on the second number of pixels and the image resolution. As an example, the damaged area of the road = the second number of pixels x the image resolution x the image resolution.

[0084] In some embodiments, for the case of lift tracks and side views, the SAR image can be rotated first, and then interpreted. As an example, when interpreting, the light source (radar beam) can be made to come from the front (up), i.e. the target shadow on the image is directed towards oneself (the shadow is downward), which can obtain the best interpretation angle and can more easily extract information in the disaster image.

[0085] In some embodiments, during interpretation, multi-data source images can also be used to assist in identification. For example, according to high-resolution Google images of the disaster area of a geological disaster, features of the ground object are identified, the number of buildings in the disaster area, the outline, the spatial distribution position, the length of the road, the direction and the spatial distribution position, and the information of rivers and mountains are obtained, the ground object information of the disaster area before the disaster is truly restored, and the SAR image after the disaster is identified.

[0086] At block 340, the electronic device 110 identifies the SAR image with the interpretation result to draw a mapping image. In some embodiments, the mapping image indicates the disaster situation of the disaster area, which includes at least the specific location of the disaster area, the disaster range, the disaster facility location and size, and the surrounding mountain, river, road location, and other information. As an example, a professional mapping software (e.g., PS) can be used to draw a thematic map on the satellite remote sensing image of the geological disaster area according to the interpretation result by marking points, lines, surfaces, and other symbols, as well as text and other information. The mapping image can fully display the overall situation of the disaster area. Specifically, as shown in FIG. 2, the mapping image can be drawn. Figure 6

[0087] In some embodiments, when the mapping image is completed, the disaster area and spatial distribution location can also be counted based on the interpretation result and the mapping image using software such as ARCGIS, ENVI, etc., including the number and degree of damaged buildings, the length, accessibility, and repair difficulty of road damage, the overall disaster area range, area, etc., to form a report.

[0088] Figure 7 A schematic diagram of the interpretation result according to some embodiments of the present disclosure is shown. A specific interpretation process is described below in conjunction with Figure 7

[0089] First, the specific disaster location information of the Sichuan Yibin landslide area is obtained using network information technology means, and a vector is formed by Google Earth software. No available satellite data was found at the time of the above-mentioned geological disaster event, so the AS-01 SAR satellite was used for emergency programming imaging. The AS-01 satellite overflight time and imaging parameter information were queried using the vector geographic coordinate information, and the observation imaging was performed using the appropriate incident angle and the disaster area facing the radar wave side view direction to obtain the best post-disaster high-resolution SAR image.

[0090] Then, the ENVI software is used to pre-process the obtained post-disaster SAR image, and the steps include data import, multi-view processing, filtering processing, and geographic coding. The obtained original SAR data is imported into the ENVI software, and the parameters (such as polarization mode, imaging mode, etc.) are set according to the sensor type to output the image file. After the data import processing, the file is processed by multi-view, the image speckle noise is reduced by the multi-view average of the azimuth and range directions, the signal-to-noise ratio is improved, the Lee filtering method is used to filter the multi-view processed image to suppress speckle noise and retain texture information. The slant range coordinate system of the filtered image is converted to the geographic coordinate system in the ENVI software, and the DEM data is combined to eliminate the terrain distortion to generate the ortho corrected image.

[0091] ​​The SAR image data of the landslide area in Yibin, Sichuan, is in 0.5-meter swath mode, with a descending right-looking imaging mode and an incidence angle of 39.7 degrees. During the interpretation process, the image needs to be rotated clockwise by about 45 degrees (radar wave direction upwards, shadow direction downwards). The interpretation clearly identifies the affected area as a landslide that has caused damage to buildings and roads. In the SAR remote sensing image, the surface features of the landslide area show significant changes: the surface tends to be smooth after the landslide, appearing as a dark tone in the image; the debris accumulated by the landslide makes the surface texture uniform, appearing as a smooth area in the image, and the boundaries of the landslide are clearly identifiable, with the boundaries of the undamaged roads and the outlines of the buildings remaining intact. For the interpretation of buildings, normal buildings have typical strong reflection characteristics in SAR images: the roof produces specular reflection due to its smooth surface, and the two-angle structure formed by the wall and the ground produces a focusing effect on the electromagnetic signal and forms secondary scattering, so it appears as a high-brightness linear structure (straight line or L-shaped broken line) in the image. The damaged buildings have changed their reflection characteristics due to the collapse of the roof and walls (some even reduced to ruins), compared with normal buildings, their reflection characteristics have changed to irregular diffuse bright areas (tending to noise characteristics). The collapsed area of the buildings flattened has a double reflection characteristic: on the one hand, the scattered signal of the collapsed area is unobstructed, and the signal strength received by the satellite tends to be uniform; on the other hand, the rubble accumulated after the collapse significantly increases the surface roughness and distributes irregularly, producing strong reflection signals, which appear as bright colors in the radar image. The interpretation of roads also has obvious differences: normal roads appear as long strip-like features in SAR images, with a relatively flat surface, uniform echo intensity, and no obvious texture changes or spot-like distribution; the boundaries of damaged road sections and normal road sections are clearly identifiable, and their radar wave reflection shows a chaotic and irregular pattern due to the destruction of the road's linear continuity.

[0092] Due to the rugged terrain and complex slope changes in the affected area, the perspective shrinkage and overlap inversion phenomena in SAR images are particularly pronounced: the upslope area of steep mountains shows significant perspective shrinkage due to the slant-range compression effect of radar side-looking imaging, causing spatial scale distortion of the terrain in the image; and the high and steep slopes near the radar side show overlap inversion due to the advance superposition of echo signals, causing the terrain height relationship to be inversely mapped in the image. These geometric distortions directly affect the accurate identification and geometric parameter measurement of disaster damage targets. Before conducting quantitative analysis, the image is preprocessed based on the DEM correction model, the inverted terrain relationship in the overlap area is corrected through the elevation remapping algorithm, and the scale bias caused by perspective shrinkage is eliminated through the R-D conversion model to ensure the geometric accuracy of the subsequent measurement data.

[0093] Finally, the interpretation results of the post-disaster SAR image are integrated, and ARCGIS software analysis shows that the overall SAR image of the landslide in Yibin, Sichuan is in the northwest-southeast direction, and is affected by the terrain, the landslide body turns to the northeast direction after sliding into the valley, and finally forms a "V" shaped landslide area. Based on the RCS reflection characteristics of the damaged target and the resolution parameters of the SAR image, it is accurately calculated that the landslide caused about 280 meters of road damage, a total of 10 houses were damaged (the total damaged area is about 3000 square meters), and a debris accumulation body about 1.2 kilometers long and about 100 meters wide was formed. Combined with the above interpretation and analysis results, relevant text labeling and symbol plotting are completed on the image, and finally a post-disaster area thematic map is made, which provides intuitive spatial information support for disaster assessment and subsequent disposal.

[0094] In summary, the embodiments of the present disclosure identify the image features in the corrected image that can reflect facilities such as buildings and roads, and combine the imaging information to realize the interpretation of the corrected image. In the above manner, the SAR image with high interpretation difficulty is converted into a convenient and quantifiable feature, reducing the SAR image interpretation difficulty.

[0095] Example Devices and Apparatus

[0096] Embodiments of the present disclosure also provide a corresponding device for implementing the above method or process. Figure 8 A schematic structural block diagram of an example device 800 for SAR image interpretation according to certain embodiments of the present disclosure is shown. The device 800 can be implemented as or included in the electronic device 110. Various modules / components in the device 800 can be implemented by hardware, software, firmware, or any combination thereof.

[0097] As Figure 8 shown, the device 800 includes an acquisition module 810 configured to acquire a SAR image of a disaster area and imaging information of the SAR image, the imaging information at least indicating imaging time, data resolution, ascending / descending track, side-looking direction, and incidence angle; a processing module 820 configured to process the SAR image using image processing software to obtain a corrected image of the SAR image; an interpretation module 830 configured to interpret the corrected image based on image features associated with image reference features in the corrected image according to the imaging information to obtain an interpretation result, the image reference features indicating common image features that are easy to interpret in the SAR image; and a plotting module 840 configured to use the interpretation result to mark the SAR image to plot a marked image, the marked image indicating a disaster situation of the disaster area, the disaster situation at least including multiple information such as specific location, disaster range, disaster facility location and size, and surrounding mountain, river, and road location of the disaster area.

[0098] In some embodiments, the image reference features include at least a first reference tonal feature and a reference shadow feature indicative of a building, and a second reference tonal feature indicative of a road.

[0099] In some embodiments, the interpretation result includes at least a damaged length and a damaged area, the corrected image includes a building, and the interpreting the corrected image according to the imaging information based on the image features associated with the image reference features in the corrected image to obtain the interpretation result includes: identifying strong line feature pixels in the image features; determining the damaged length of the building based on the strong line feature pixels and an image resolution in the imaging information; identifying a first number of pixels of a damaged area of the building using a radar cross section measurement technique; and determining the damaged area of the building based on the first number of pixels and the image resolution.

[0100] In some embodiments, the corrected image includes a road, and the interpreting the corrected image according to the imaging information based on the image features associated with the image reference features in the corrected image to obtain the interpretation result includes: identifying line target feature pixels in the image features; determining the damaged length of the road based on the line target feature pixels and an image resolution in the imaging information; identifying a second number of pixels of a damaged area of the road using a radar cross section measurement technique; and determining the damaged area of the road based on the second number of pixels and the image resolution.

[0101] In some embodiments, processing the SAR image using the image processing software to obtain the corrected image of the SAR image includes: in response to the disaster type being a landslide or a debris flow, determining imaging features contained in the SAR image, the imaging features being indicative of interference caused by a terrain slope and an incident angle; constructing a calibration model corresponding to the imaging features; and correcting the image processed by the image processing software using the calibration model to obtain the corrected image.

[0102] In some embodiments, constructing the calibration model corresponding to the imaging features includes: in response to the imaging features being perspective contraction, establishing a first calibration model, the first calibration model indicating a relationship between a first slant range and a first ground range of a contraction area, the first calibration model including a radar platform height and a first elevation of a ground target relative to a reference surface; determining a first reference ground range according to the first calibration model based on a first preset value of the first elevation; and correcting the first preset value based on a difference between the first reference ground range and the first ground range, such that the relationship between the first slant range and the first ground range satisfies an error condition, to obtain the calibration model.

[0103] In some embodiments, constructing a calibration model corresponding to an imaging feature includes: in response to an imaging feature being an overlay inversion, establishing a second calibration model, the second calibration model indicating the relationship between a second slant distance and a second ground distance in the overlay region, the second calibration model including a second elevation of the ground target relative to a reference surface; determining a second reference ground distance based on a second preset value of the second elevation according to the second calibration model; and correcting the second preset value based on the difference between the second reference ground distance and the second ground distance to obtain the calibration model.

[0104] like Figure 9 As shown, the computing device 900 is in the form of a general-purpose electronic device. Components of the computing device 900 may include, but are not limited to, one or more processors or processing units 910, memory 920, storage devices 930, one or more communication units 940, one or more input devices 950, and one or more output devices 960. The processing unit 910 may be a physical or virtual processor and is capable of performing various processes according to programs stored in the memory 920. In a multiprocessor system, multiple processing units execute computer-executable instructions in parallel to improve the parallel processing capability of the computing device 900.

[0105] Computing device 900 typically includes multiple computer storage media. Such media can be any accessible media that is accessible to computing device 900, including but not limited to volatile and non-volatile media, removable and non-removable media. Memory 920 can be volatile memory (e.g., registers, cache, random access memory (RAM)), non-volatile memory (e.g., read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory), or some combination thereof. Storage device 930 can be removable or non-removable media and can include machine-readable media, such as flash drives, disks, or any other media that can be used to store information and / or data and can be accessed within computing device 900.

[0106] The computing device 900 may further include additional removable / non-removable, volatile / non-volatile storage media. Although not explicitly stated... Figure 9 As shown, disk drives for reading from or writing to removable, non-volatile disks (e.g., "floppy disks") and optical disk drives for reading from or writing to removable, non-volatile optical disks can be provided. In these cases, each drive can be connected to a bus (not shown) via one or more data media interfaces. Memory 920 may include computer program product 925 having one or more program modules configured to perform various methods or actions of various embodiments of this disclosure.

[0107] The communication unit 940 enables communications with other electronic devices over a communication medium. Additionally, the functionality of the components of the computing device 900 can be implemented in a single computing cluster or a plurality of computer machines that are capable of communicating over a communication connection. Thus, the computing device 900 can operate in a networked environment using logical connections to one or more other servers, network personal computers (PCs), or another network node in the networking environment.

[0108] The input device 950 can be one or more input devices, such as a mouse, a keyboard, a trackball, etc. The output device 960 can be one or more output devices, such as a display, a speaker, a printer, etc. The computing device 900 can also communicate with one or more external devices (not shown), such as a storage device, a display device, etc., through the communication unit 940, as needed, communicate with one or more devices that enable a user to interact with the computing device 900, or communicate with any devices (e.g., a network card, a modem, etc.) that enable the computing device 900 to communicate with one or more other electronic devices. Such communication can be carried out via an input / output (I / O) interface (not shown).

[0109] According to an example implementation of the present disclosure, there is provided a computer-readable storage medium having computer-executable instructions stored thereon, where the computer-executable instructions are executed by a processor to implement the method described above. According to an example implementation of the present disclosure, there is also provided a computer program product tangibly stored on a non-transitory computer-readable medium and comprising computer-executable instructions, where the computer-executable instructions are executed by a processor to implement the method described above.

[0110] Various aspects of the disclosure are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatuses, and computer program products according to this disclosure. 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-readable program instructions.

[0111] These computer readable program instructions can be provided to a processor of a general purpose computer, special purpose computer, 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, create means for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks. These computer readable program instructions can also be stored in a computer readable storage medium that can include a non-transitory computer readable storage medium that can direct a computer, a programmable data processing apparatus, and / or other devices to function in a particular manner, such that the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function / act specified in the flowchart and / or block diagram block or blocks.

[0112] The computer readable program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus or other device to produce a computer implemented process such that the instructions which execute on the computer, other programmable data processing apparatus, or other device implement the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0113] The flow diagrams and the block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various implementations of the present disclosure. In this regard, each block in the flow diagrams and the block diagrams can represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logic functions (s). In some alternative implementations, the functions noted in the blocks can occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks can sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and / or flow diagrams, and combinations thereof, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and

[0114] implementations have been described above, the description is intended to be illustrative, and not restrictive, and is not intended to exclude other implementations from the scope of the implementations disclosed herein. Many modifications and variations to the implementations described herein are possible and are within the scope of the implementations described herein. The order in which the operations of various implementations are illustrated and described is not essential, for example, unless specifically stated, the order of the operations can differ from that described. Also, some operations can be optional.

[0115] The foregoing description of specific exemplary implementations of the application has been presented for the purposes of illustration and description. It is not intended to be exhaustive or to limit the application to the precise forms disclosed, and various modifications and variations are possible in light of the above teaching. It is intended that the scope of the application be limited not with reference to the specific implementations described, but rather to the breadth of equivalents, apparat us, and modifications that are encompassed by the present application.

Claims

1. A SAR image interpretation method, characterized in that, The method includes: Acquire SAR images of the disaster-stricken area and imaging information of the SAR images, wherein the imaging information indicates at least the imaging time, data resolution, ascent and descent orbit, side-view direction, and incident angle; The SAR image is processed using image processing software to obtain a corrected image of the SAR image; Based on image features associated with image reference features in the corrected image, the corrected image is interpreted according to the imaging information to obtain an interpretation result. The image reference features indicate commonly used image features in the SAR image that are easy to interpret. The SAR image is labeled using the interpretation results to create a plotted image. The plotted image indicates the disaster situation in the disaster-stricken area. The disaster situation includes at least the specific location of the disaster-stricken area, the scope of the disaster, the location and size of the disaster-stricken facilities, and multiple other information such as the location of surrounding mountains, rivers, and roads.

2. The method according to claim 1, characterized in that, The image reference features include at least a first reference tone feature and a reference shadow feature indicating a building, and a second reference tone feature indicating a road.

3. The method according to claim 2, characterized in that, The interpretation result includes at least the damaged length and damaged area. The corrected image includes buildings. The interpretation result obtained by interpreting the corrected image based on the image features associated with image reference features in the corrected image and according to the imaging information includes: Identify strong line feature pixels in the image features; The damaged length of the building is determined based on the strong line feature pixels and the image resolution in the imaging information; The number of first pixels used to identify the damaged area of ​​the building using radar cross section measurement technology; and The damaged area of ​​the building is determined based on the first number of pixels and the image resolution.

4. The method according to claim 2, characterized in that, The corrected image includes roads, and the interpretation of the corrected image based on image features associated with image reference features in the corrected image, according to the imaging information, yields the following interpretation results: Identify linear target feature pixels in the image features; The damaged length of the road is determined based on the linear target feature pixels and the image resolution in the imaging information; The number of second pixels used to identify the damaged area of ​​the road using radar cross section measurement technology; and The damaged area of ​​the road is determined based on the second number of pixels and the image resolution.

5. The method according to claim 1, characterized in that, The process of processing the SAR image using image processing software to obtain a corrected image of the SAR image includes: In response to a disaster type of landslide or debris flow, imaging features contained in the SAR image are determined, the imaging features indicating interference caused by terrain slope and incident angle; Construct a calibration model corresponding to the imaging features; and The image processed by the image processing software is corrected using the calibration model to obtain the corrected image.

6. The method according to claim 5, characterized in that, The construction of the calibration model corresponding to the imaging features includes: In response to the imaging feature being perspective shrinkage, a first calibration model is established. The first calibration model indicates the relationship between a first slant range and a first ground distance in the shrinkage region. The first calibration model includes the radar platform height and the first elevation of the ground target relative to the reference plane. Based on a first preset value of the first elevation, a first reference ground distance is determined according to the first calibration model; and Based on the difference between the first reference distance and the first distance, the first preset value is corrected so that the relationship between the first slope distance and the first distance satisfies the error condition, thereby obtaining the calibration model.

7. The method according to claim 5, characterized in that, The construction of the calibration model corresponding to the imaging features includes: In response to the imaging feature being overlayed, a second calibration model is established, the second calibration model indicating the relationship between the second slant range and the second ground distance of the overlay region, the second calibration model including the second elevation of the ground target relative to the reference surface; Based on the second preset value of the second elevation, the second reference ground distance is determined according to the second calibration model; and Based on the difference between the second reference distance and the second distance, the second preset value is corrected to obtain the calibration model.

8. An apparatus for interpreting SAR images, characterized in that, include: The acquisition module is configured to acquire SAR images of the disaster-stricken area and imaging information of the SAR images, wherein the imaging information indicates at least the imaging time, data resolution, ascent and descent rail, side-view direction, and incident angle. The processing module is configured to process the SAR image using image processing software to obtain a corrected image of the SAR image; The interpretation module is configured to interpret the correction image based on the imaging information according to the image features associated with the image reference features in the correction image, and obtain the interpretation result, wherein the image reference features indicate commonly used image features in the SAR image that are easy to interpret; as well as The drawing module is configured to use the interpretation results to identify the SAR image to draw a plotted image, which indicates the disaster situation of the disaster area. The disaster situation includes at least the specific location of the disaster area, the scope of the disaster, the location and size of the disaster facilities, and multiple other information such as the location of surrounding mountains, rivers, and roads.

9. A computing device, comprising: At least one processing unit; as well as At least one memory coupled to the at least one processing unit and storing instructions for execution by the at least one processing unit, the instructions causing the computing device to perform the method according to any one of claims 1 to 7 when executed by the at least one processing unit.

10. A computer-readable storage medium having a computer program stored thereon, the computer program being executable by a processor to implement the method according to any one of claims 1 to 7.

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