A method and system for monitoring lake and reservoir water levels based on radar satellite imagery and corner reflectors

Abstract

This invention provides a method for monitoring lake and reservoir water levels based on radar satellite imagery and corner reflectors, comprising: acquiring slope parameters of a straight slope pre-constructed along the shore of a lake or reservoir area under study, and the absolute elevation of a corner reflector installed at the top of the straight slope; acquiring radar satellite imagery of the lake or reservoir area for the study period, and extracting the water body area and the water surface area of ​​the straight slope from the radar satellite imagery by employing radar satellite imagery polarization combination and thresholding methods, and extracting the elevation calibration point of the corner reflector from the radar satellite imagery; the radar satellite imagery contains the complete water surface area of ​​the straight slope; extracting the water body boundary line between the water body area and the water surface area of ​​the straight slope from the radar satellite imagery, and based on the virtual water gauge, calculating the distance between the water body boundary line and the elevation calibration point of the corner reflector, and performing mathematical conversion to obtain the monitoring water level of the lake or reservoir area for the study period.

Description

Technical Field

[0001] This invention belongs to the field of hydrological measurement or water conservancy monitoring, and specifically relates to a method and system for monitoring lake and reservoir water levels based on radar satellite imagery and corner reflectors. Background Technology

[0002] Water level refers to the elevation of the free water surface above a designated datum. It is the most fundamental observation item in hydrological observation and holds a very important position. On the one hand, water level serves as a basic basis for engineering construction planning and design, providing hydrological information for hydrological forecasting and other work. On the other hand, it provides indirect data for inferring other hydrological data. Traditional water level observation methods include manual observation, recording by self-recording water level gauges, encoded storage of water level data, and automatic water level monitoring systems. In recent years, with the development of satellite remote sensing technology, the method of inferring water level using satellite remote sensing imagery has gradually become a popular water level measurement method.

[0003] Traditional lake and river water level monitoring primarily relies on hydrological stations to obtain water level information, which requires significant manpower, material resources, and financial investment. Furthermore, many lakes and rivers are located in remote areas, making it difficult to establish observation points. In addition, the current level of data sharing among hydrological stations is low, making data acquisition challenging. Compared to traditional monitoring methods, radar satellites offer the advantages of rapid, all-weather observation and the ability to monitor river and lake water level changes globally, particularly in remote areas lacking data. However, existing methods for inferring water levels using satellite remote sensing are still immature, lacking readily available ground-based comparison data to verify the reliability of the inversion results.

[0004] On the one hand, satellite imagery makes it easy to interpret planar dimensions but difficult to determine vertical dimensions; on the other hand, the accuracy of water level observations needs to meet operational requirements. In general water level observations, the water level value should be accurate to 0.01 m; in large flood observations, the water level value should be accurate to 0.1 m, but commonly used high-resolution radar satellite imagery is approximately 1 m. Therefore, it is difficult to obtain the water level directly from radar satellite imagery by reading the water gauge. Summary of the Invention

[0005] To overcome the problem that existing technologies cannot intuitively read water level readings from radar satellite images, this invention provides a method and system for monitoring lake and reservoir water levels based on radar satellite images and corner reflectors. By obtaining the slope of a straight ramp constructed in advance along the shore of the lake or reservoir area and the absolute elevation of the corner reflector installed at the top of the ramp, a virtual water level gauge is designed. This transforms water level monitoring, which involves interpreting the vertical dimensions of satellite images, into a more easily understood problem of interpreting the planar dimensions of satellite images. By adjusting the slope, the required water level accuracy can be obtained. This saves on the manpower and material costs of constructing water level observation stations while providing more intuitive and accurate water level measurement results using satellite imagery.

[0006] According to one aspect of the present invention, a method for monitoring lake and reservoir water levels based on radar satellite imagery and corner reflectors is provided, comprising:

[0007] Obtain the slope parameters of a straight ramp pre-constructed along the shore of the lake / reservoir area, as well as the absolute elevation of the corner reflector installed at the top of the straight ramp, and construct a virtual water gauge.

[0008] The radar satellite images of the lake / reservoir area for the study period are acquired. By employing radar satellite image polarization combination and thresholding methods, the water body area and the water area above the straight slope in the radar satellite images are extracted, and the corner reflector elevation calibration points in the radar satellite images are also extracted. The radar satellite images contain the complete water area above the straight slope.

[0009] The water boundary line between the water area in the radar satellite image and the water area above the straight slope is extracted. Based on the virtual water gauge, the distance between the water boundary line and the elevation calibration point of the corner reflector is calculated and mathematically converted to obtain the monitoring water level of the lake / reservoir area during the study period.

[0010] As a further technical solution, the surface of the straight ramp is covered with a radar-reflective layer.

[0011] As a further technical solution, the radar wave high reflectivity layer is configured to exhibit high backscattering characteristics compared to water in radar satellite imagery, so as to form a preset grayscale contrast with the backscattering characteristics of water.

[0012] As a further technical solution, the parameters of the straight ramp are configured as preset geometric parameters, including width, top elevation and slope;

[0013] The slope i of a straight ramp satisfies the following relationship:

[0014]

[0015] Where δ represents the target water level identification accuracy, and D represents the spatial resolution of the radar satellite image.

[0016] As a further technical solution, the virtual water gauge consists of the slope of the straight ramp and the absolute elevation of the corner reflector.

[0017] As a further technical solution, the steps for extracting water areas from radar satellite images by employing radar satellite image polarization combination and thresholding include:

[0018] The RVI value is calculated using the backscattering coefficients of the HH, HV, and VV polarization channels of radar satellite imagery, and an RVI feature image is generated.

[0019] A grayscale histogram distribution is generated based on the RVI feature image, and the water extraction threshold is determined by the Osti thresholding method.

[0020] Pixels with RVI values ​​less than the water body extraction threshold are identified as water body pixels, and water body areas are extracted from radar satellite images.

[0021] As a further technical solution, based on the virtual water gauge, the monitoring water level of the study lake / reservoir area for the study period is obtained by calculating the distance between the water body boundary line and the elevation calibration point of the corner reflector and performing mathematical conversion. The steps include:

[0022] The number of pixels from the water surface boundary line to the corner reflector elevation calibration point in the radar satellite imagery is extracted. Based on the radar satellite imagery resolution, the horizontal projected distance from the water surface boundary line to the corner reflector elevation calibration point is calculated.

[0023] Based on the virtual water gauge, the monitored water level value z is calculated and mathematically expressed as:

[0024] z = Zx × i;

[0025] Where Z is the absolute elevation of the corner reflector, and x is the horizontal projection distance from the water surface boundary line to the elevation calibration point of the corner reflector.

[0026] According to another aspect of this specification, a lake / reservoir water level monitoring system based on radar satellite imagery and corner reflectors is provided, comprising:

[0027] The virtual water gauge construction module is used to obtain the slope parameters of a straight ramp pre-constructed on the shore of the water area in the study lake reservoir, as well as the absolute elevation of the corner reflector installed at the top of the straight ramp.

[0028] The radar satellite imagery region extraction module is used to acquire radar satellite images of the lake / reservoir area for the study period. By employing radar satellite imagery polarization combination and thresholding methods, it extracts the water body area and the water area above the straight slope in the radar satellite images, and extracts the corner reflector elevation calibration points in the radar satellite images. The radar satellite images contain the complete water area above the straight slope.

[0029] The water level monitoring module is used to extract the water boundary line between the water area in the radar satellite image and the water area above the straight slope. Based on the virtual water gauge, the module calculates the distance between the water boundary line and the elevation calibration point of the corner reflector and performs mathematical conversion to obtain the monitoring water level of the lake / reservoir area during the study period.

[0030] According to another aspect of this specification, an electronic device is provided, including a memory and a processor, the memory storing program instructions executed by the processor, the processor invoking the program instructions to perform a method for monitoring lake and reservoir water levels based on radar satellite imagery and corner reflectors.

[0031] According to another aspect of this specification, a non-transitory computer-readable storage medium is provided, the non-transitory computer-readable storage medium storing computer instructions that cause the computer to execute a method for monitoring lake and reservoir water levels based on radar satellite imagery and corner reflectors.

[0032] Compared with existing technologies, the advantages of this invention are as follows: By obtaining the slope of a straight ramp constructed in advance along the shore of the lake / reservoir area and the absolute elevation of a corner reflector installed at the top of the ramp, a virtual water gauge is designed. Combined with satellite remote sensing technology and projection magnification methods, and taking advantage of the small surface fluctuations of the lake / reservoir water, which cause specular reflection of radar waves resulting in weak echoes that appear dark in radar satellite images, specific characteristic values ​​are calculated using radar satellite image polarization combination and thresholding methods to identify water bodies. Simultaneously, the strong reflection characteristics of the corner reflector on the radar beam are utilized to perform radar satellite image mapping. The calibration and identification of elevation points transforms water level monitoring, which involves interpreting the vertical dimensions of satellite imagery, into a simpler problem of interpreting the planar dimensions of satellite imagery. This allows for intuitive identification of water bodies and reading of virtual water gauges. The invention utilizes a projection magnification method, amplifying the water gauge reading by a factor of (L / H) (where L and H represent the planar projection length and total vertical height of the straight slope, respectively) at a radar satellite imagery resolution of D×D. This not only transforms the identification of planar dimensions from radar satellite imagery into the identification of vertical dimensions but also ensures that the water level accuracy meets operational requirements, ultimately achieving the goal of intuitive satellite-based water level monitoring. This invention is simple, effective, and highly adaptable. It readily utilizes radar satellite imagery to intuitively obtain water level data that meets accuracy requirements. By adjusting the slope, the required water level accuracy can be achieved. This saves on the manpower and material costs of constructing water level observation stations while providing more intuitive and accurate water level measurement results using satellite imagery. Attached Figure Description

[0033] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0034] Figure 1 A schematic diagram illustrating a method for monitoring lake and reservoir water levels based on radar satellite imagery and corner reflectors, provided in an embodiment of the present invention;

[0035] Figure 2 This is a top view of the virtual water gauge layout in this invention;

[0036] Figure 3 This is a front view of the virtual water gauge layout in this invention;

[0037] Figure 4 A schematic diagram illustrating a method for monitoring lake and reservoir water levels based on radar satellite imagery and corner reflectors, provided in an embodiment of the present invention;

[0038] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0039] In the diagram: ① represents the river channel; ② represents the above-water portion of the straight slope; ③ represents the corner reflector; ④ represents the underwater portion of the straight slope; ⑤ represents the water surface boundary line; H represents the total vertical height of the straight slope; S represents the total length of the slope; α represents the angle between the slope surface and the horizontal plane; L represents the planar projection length of the straight slope; W represents the slope width; z represents the monitored water level; Z represents the absolute elevation of the corner reflector; x represents the horizontal projection distance between the water surface boundary line and the elevation calibration point of the corner reflector; h represents the vertical projection distance between the water surface line and the elevation calibration point of the corner reflector. Detailed Implementation

[0040] It should be noted that:

[0041] The terms “comprising” and “having”, and any variations thereof, in the specification, claims, and accompanying drawings of this invention are intended to cover a non-exclusive inclusion, such as a process, method, system, product, or apparatus that includes a series of steps or units, not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0042] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices. The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be decomposed, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0043] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. In addition, the technical features of the various embodiments or individual embodiments provided by the present invention can be arbitrarily combined to form new technical solutions. Such combinations are not bound by the order of steps and / or structural composition patterns, but must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by the present invention.

[0044] like Figure 1 As shown, a method for monitoring lake and reservoir water levels based on radar satellite imagery and corner reflectors includes:

[0045] Step 1: Obtain the slope parameters of the straight ramp constructed in advance on the shore of the lake area under study, as well as the absolute elevation of the corner reflector installed at the top of the straight ramp, and construct a virtual water gauge.

[0046] Step 2: Obtain radar satellite images of the lake / reservoir area for the study period. By using radar satellite image polarization combination and thresholding method, extract the water body area and the water area above the straight slope in the radar satellite image, and extract the corner reflector elevation calibration points in the radar satellite image; the radar satellite image contains the complete water area above the straight slope.

[0047] Step 3: Extract the water boundary line between the water area and the water area above the straight slope in the radar satellite image. Based on the virtual water gauge, calculate the distance between the water boundary line and the elevation calibration point of the corner reflector, and perform mathematical conversion to obtain the monitoring water level of the lake / reservoir area during the study period.

[0048] like Figure 2 , Figure 3 As shown, in step 1, the surface of the straight ramp is covered with a radar wave highly reflective layer.

[0049] Specifically, a straight ramp is constructed along the shore in the water area where water levels need to be measured during low water periods, or an existing hydraulic structure is modified into a regular ramp. The straight ramp is long enough and its bottom is submerged in the water of the lake or reservoir area being studied to ensure that the ramp can cover the lowest possible water level.

[0050] The radar wave high reflectivity layer is configured to exhibit high backscattering characteristics compared to water in radar satellite imagery, so as to form a preset grayscale contrast with the backscattering characteristics of water.

[0051] This is because calm water bodies typically exhibit specular reflection in SAR images, with most of the energy reflected into the sky. The echo received by the satellite is extremely weak, appearing black in the image. The radar wave high reflectivity layer in this application is designed as a diffuse reflector, scattering radar waves in all directions. The satellite receives a strong echo, appearing bright white (high brightness) in the image, artificially creating a significant difference in radar cross-section between the ramp and the water body. This strong 'bright-dark' boundary allows subsequent image processing algorithms to pinpoint the water surface boundary with sub-pixel accuracy. Optionally, the radar wave high reflectivity layer in this application is constructed using a gravel layer.

[0052] Furthermore, the straight ramp parameters are configured with preset geometric parameters, including width, top elevation, and slope;

[0053] Firstly, under the spatial resolution conditions of radar satellite imagery, the width of the straight ramp in the radar imagery is not less than 3 pixels in length. Specifically, assuming the spatial resolution of the radar satellite imagery is D×D, the minimum width of the ramp for the virtual water level gauge is theoretically D. Preferably, in practical applications, to achieve a better water level extraction effect, the ramp width is greater than or equal to 3D. This width is configured to occupy at least 3 pixels in the radar satellite imagery to eliminate edge effects and improve the signal-to-noise ratio of water body boundary extraction.

[0054] Secondly, the top elevation of the ramp is configured to be no lower than the historical highest water level of the monitored water area to ensure that the ramp can provide an effective observation reference surface throughout the entire range of water level fluctuations.

[0055] Third, the slope of the ramp satisfies the following relationship:

[0056]

[0057] Where δ represents the target water level identification accuracy, and D represents the spatial resolution of the radar satellite image.

[0058] Preferably, the slope of the ramp should be as small as possible, as a smaller slope means a longer ramp and a more precise virtual water gauge; to achieve a water level recognition accuracy of 0.1m, the slope of the ramp should be less than or equal to 0.1 times D.

[0059] In step 1, the virtual water gauge consists of the slope of the straight ramp and the absolute elevation of the corner reflector.

[0060] Optionally, the absolute elevation of the corner reflector is obtained by field measurement using a high-precision GPS (such as RTK) or a level.

[0061] In Step 2, the elevation calibration point of the corner reflector is the foot position of the center point of the corner reflector installation on the ramp surface (i.e., the ramp point directly below the corner reflector), and its absolute elevation is Z.

[0062] In Step 2, the steps of extracting the water body area in the radar satellite image by using the radar satellite image polarization combination and threshold method include:

[0063] Calculate the RVI (Radar Vegetation Index) value by using the backscattering coefficients of the HH (horizontal polarization transmission, horizontal polarization reception), HV (horizontal polarization transmission, vertical polarization reception), and VV (vertical polarization transmission, vertical polarization reception) polarization channels of the radar satellite image, and generate the RVI characteristic image;

[0064] Generate the gray histogram distribution based on the RVI characteristic image, and determine the water body extraction threshold by the Otsu threshold method;

[0065] Determine the pixels with RVI values less than the water body extraction threshold as water body pixels, and extract the water body area in the radar satellite image.

[0066] Specifically, in Step 2, the backscattering coefficients of the HH polarization, HV polarization, and VV polarization of the radar satellite image in the target water area (the backscattering coefficient of the HH polarization channel , the backscattering coefficient of the HV polarization channel , and the backscattering coefficient of the HH polarization channel ), calculate the water body characteristic index RVI = . Through the water body extraction threshold t, the pixels that are water bodies in the radar satellite image satisfy RVI < t, so as to distinguish the water body from the non-water body (ramp).

[0067] As a supplementary explanation, the surface of the lake and reservoir water body fluctuates little, resulting in a specular reflection of the radar wave, weak echo, and a dark black appearance in the radar satellite image (that is, the water body is darker in the HH polarization of the radar satellite image than in the HV / VV polarization), but in the SAR image, relying only on the HH intensity threshold is prone to misjudgment. In Step 2 of this application, the method of combining the HH, HV, and VV radar satellite image polarizations can more stably identify the water body.

[0068] On this basis, by calculating the RVI index, the physical difference (smoothness difference) between the water body and the ramp is converted into a drastic jump in the index value. The RVI of the water body is close to 0, and the RVI of the ramp is close to 1 (or a higher value), and the two form obvious double peaks on the histogram, making the threshold segmentation more accurate.

[0069] In step 3, based on a virtual water gauge, the distance between the water body boundary line and the elevation calibration point of the corner reflector is calculated and mathematically converted to obtain the monitoring water level of the lake / reservoir area during the study period. The steps include:

[0070] The number of pixels from the water surface boundary line to the corner reflector elevation calibration point in the radar satellite imagery is extracted. Based on the radar satellite imagery resolution, the horizontal projected distance from the water surface boundary line to the corner reflector elevation calibration point is calculated.

[0071] Based on the virtual water gauge, the monitored water level value z is calculated and mathematically expressed as:

[0072] z = Zx × i;

[0073] Where Z is the absolute elevation of the corner reflector, and x is the horizontal projection distance from the water surface boundary line to the elevation calibration point of the corner reflector.

[0074] Specifically, assuming the slope of the straight ramp is i, the total vertical height (top elevation) is H, and the planar projection length is L, then the slope i = H / L, the resolution of the radar satellite image is D×D, and the absolute elevation of the corner reflector is Z.

[0075] When the water surface intersects with a straight slope, assuming the water level is z, the horizontal projection of the distance from the boundary line to the standard line of the corner reflector at the top of the slope is x (the corner reflector is a high-brightness point in the radar satellite image and is easily identified; extract the number of pixels n between the water body and the boundary line of the slope and the calibration point of the corner reflector; under the radar satellite image resolution of D×D, then x=n×D). According to the proportional relationship, we get: i=H / L=h / x, where h is the vertical distance from the water surface boundary line to the calibration point. Then we can calculate the water level value z=Zh=Zx×i.

[0076] Using this projection method, the reading of the monitored water level is magnified to L / H times. Therefore, the accuracy of the water level z is determined by the total vertical height H and the horizontal projection length L of the ramp, which is determined by the slope. The smaller the slope, the higher the accuracy. By adjusting the slope, the required water level accuracy can be obtained. Combined with the absolute elevation of the corner reflector, the effect of a virtual water gauge is achieved.

[0077] Optionally, taking a radar satellite image resolution of 1m×1m as an example, with a total vertical height of H=1m, a planar projection length of L=10m, and a width of W=1m, the accuracy of the horizontal projection length x of the distance from the boundary line to the standard line of the corner reflector at the top of the ramp is 1m, which is also the accuracy of the virtual water gauge.

[0078] The implementation of the various embodiments of the present invention is based on programmed processing through a system with processor functionality. Therefore, in practical engineering, the technical solutions and functions of the various embodiments of the present invention are encapsulated into various modules. Based on this reality, and building upon the above embodiments, the embodiments of the present invention provide a lake / reservoir water level monitoring system based on radar satellite imagery and corner reflectors. This system is used to execute a lake / reservoir water level monitoring method based on radar satellite imagery and corner reflectors from the above method embodiments.

[0079] See Figure 4 The system includes:

[0080] The virtual water gauge construction module is used to obtain the slope parameters of a straight ramp pre-constructed on the shore of the lake area under study, as well as the absolute elevation of the corner reflector installed at the top of the straight ramp, and to construct a virtual water gauge.

[0081] The radar satellite imagery region extraction module is used to acquire radar satellite images of the lake / reservoir area for the study period. By employing radar satellite imagery polarization combination and thresholding methods, it extracts the water body area and the water area above the straight slope in the radar satellite images, and extracts the corner reflector elevation calibration points in the radar satellite images. The radar satellite images contain the complete water area above the straight slope.

[0082] The water level monitoring module is used to extract the water boundary line between the water area in the radar satellite image and the water area above the straight slope. Based on the virtual water gauge, the module calculates the distance between the water boundary line and the elevation calibration point of the corner reflector and performs mathematical conversion to obtain the monitoring water level of the lake / reservoir area during the study period.

[0083] It should be noted that the system embodiments provided by the present invention are used not only to implement the methods in the above method embodiments, but also to implement the methods in other method embodiments provided by the present invention. The only difference is that corresponding functional modules are set. The principle is basically the same as that of the above system embodiments provided by the present invention. As long as those skilled in the art can improve the modules in the above system embodiments by referring to the specific technical solutions in other method embodiments and combining technical features to obtain corresponding technical means and technical solutions composed of these technical means, on the basis of the above system embodiments, and on the premise of ensuring the practicality of the technical solutions, they can obtain corresponding system-like embodiments for implementing the methods in other method-like embodiments.

[0084] The method in this embodiment of the invention is implemented using an electronic device; therefore, it is necessary to introduce the relevant electronic device. For this purpose, embodiments of the present invention provide an electronic device, such as... Figure 5As shown, the electronic device includes: at least one processor, a communication interface, at least one memory, and a communication bus, wherein the at least one processor, the communication interface, and the at least one memory communicate with each other via the communication bus. The at least one processor invokes logical instructions stored in the at least one memory to execute all or part of the steps of the methods provided in the foregoing method embodiments.

[0085] Furthermore, when the logical instructions in at least one of the aforementioned memories are implemented as software functional units and sold or used as independent products, they are stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, is embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (a personal computer, server, or network device) to execute all or part of the steps of the methods described in the various method embodiments of the present invention. The aforementioned storage medium includes: USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks—various media for storing program code.

[0086] The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, located in one place, or distributed across multiple network units. The purpose of this embodiment is achieved by selecting some or all of the modules according to actual needs. Those skilled in the art will understand and implement this without any inventive effort.

[0087] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0088] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0089] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0090] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0091] Based on the same technical concept as the foregoing embodiments, the present invention provides a non-transitory computer-readable storage medium that stores computer instructions that cause the computer to execute a method for monitoring lake and reservoir water levels based on radar satellite imagery and corner reflectors.

[0092] In summary, this invention proposes a method for monitoring lake and reservoir water levels based on radar satellite imagery and corner reflectors. A virtual water gauge is designed and implemented, combining satellite remote sensing technology and projection magnification methods. Utilizing the characteristic that the surface fluctuations of lake and reservoir water are small, resulting in specular reflection of radar waves and weak echoes appearing dark in radar satellite imagery, specific feature values ​​are calculated using radar satellite image polarization combination and thresholding methods to identify water bodies. Simultaneously, the strong reflection characteristics of radar beams by corner reflectors are used to calibrate and identify ground elevation points in radar satellite imagery. Combined with projection magnification, the water gauge reading is magnified (L / H) times at a radar satellite image resolution of D×D, and then converted to obtain the water level. This invention can intuitively identify water bodies and read virtual water gauge values, not only transforming the identification of planar dimensions from radar satellite imagery to the identification of vertical dimensions, but also ensuring that the water level accuracy meets usage requirements, ultimately achieving the goal of intuitive satellite water level monitoring. This invention is simple, effective, highly adaptable, and readily utilizes radar satellite imagery to intuitively obtain water level data that meets accuracy requirements.

[0093] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the technical solutions of the embodiments of the present invention.

Claims

1. A method for monitoring lake and reservoir water levels based on radar satellite imagery and corner reflectors, characterized in that, include: Obtain the slope parameters of the straight ramps pre-constructed in the research lake and reservoir area, as well as the absolute elevation of the corner reflectors installed at the top of the straight ramps, and construct a virtual water gauge; The radar satellite images of the lake / reservoir area for the study period are acquired. By employing radar satellite image polarization combination and thresholding methods, the water body area and the water area above the straight slope in the radar satellite images are extracted, and the corner reflector elevation calibration points in the radar satellite images are also extracted. The radar satellite images contain the complete water area above the straight slope. The water boundary line between the water area in the radar satellite image and the water area above the straight slope is extracted. Based on the virtual water gauge, the distance between the water boundary line and the elevation calibration point of the corner reflector is calculated and mathematically converted to obtain the monitoring water level of the lake / reservoir area during the study period.

2. The method for monitoring lake and reservoir water levels based on radar satellite imagery and corner reflectors as described in claim 1, characterized in that, The straight ramp was built on the shore of the lake during the low water level period, and the surface of the ramp is covered with a radar-reflective layer.

3. A method for monitoring water level of a lake or reservoir based on radar satellite imagery and corner reflectors as claimed in claim 1, wherein, The radar wave high reflectivity layer is configured to exhibit high backscattering characteristics compared to water in radar satellite imagery, so as to form a preset grayscale contrast with the backscattering characteristics of water.

4. The method of claim 1, wherein the method is based on radar satellite imagery and corner reflectors. The parameters of the straight ramp are configured as preset geometric dimensions, including width, top elevation, and slope; The slope i of the straight ramp satisfies the following relationship: Where δ represents the target water level identification accuracy, and D represents the spatial resolution of the radar satellite image.

5. A method for monitoring water level of a lake or reservoir based on radar satellite imagery and corner reflectors as claimed in claim 1, wherein, The virtual water gauge consists of the slope of the straight ramp and the absolute elevation of the corner reflector.

6. A method for monitoring water level of a lake or reservoir based on radar satellite imagery and corner reflectors as claimed in claim 1, wherein, The steps for extracting water bodies from radar satellite images using polarimetric combination and thresholding include: The RVI value is calculated using the backscattering coefficients of the HH, HV, and VV polarization channels of radar satellite imagery, and an RVI feature image is generated. A grayscale histogram distribution is generated based on the RVI feature image, and the water extraction threshold is determined by the Osti thresholding method. Pixels with RVI values ​​less than the water extraction threshold are identified as water pixels. Water areas are extracted from radar satellite images, and non-water areas with linear geometric features of straight slopes and adjacent to water areas are identified from the neighborhood of the water areas as the water areas above the straight slopes.

7. A method for monitoring water level of a lake or reservoir based on radar satellite imagery and corner reflectors as claimed in claim 1, wherein, Based on the virtual water gauge, the monitoring water level of the lake / reservoir area during the study period is obtained by calculating the distance between the water boundary line and the elevation calibration point of the corner reflector and performing mathematical conversion. The steps include: The number of pixels from the water surface boundary line to the corner reflector elevation calibration point in the radar satellite imagery is extracted. Based on the radar satellite imagery resolution, the horizontal projected distance from the water surface boundary line to the corner reflector elevation calibration point is calculated. Based on the virtual water gauge, the monitored water level value z is calculated and mathematically expressed as: z = Zx × i; Where Z is the absolute elevation of the corner reflector, and x is the horizontal projection distance from the water surface boundary line to the elevation calibration point of the corner reflector.

8. A lake and reservoir water level monitoring system based on radar satellite imagery and corner reflectors, characterized by, include: The virtual water gauge construction module is used to obtain the slope parameters of a straight ramp pre-constructed on the shore of the lake area under study, as well as the absolute elevation of the corner reflector installed at the top of the straight ramp, and to construct a virtual water gauge. The radar satellite imagery region extraction module is used to acquire radar satellite images of the lake / reservoir area for the study period. By employing radar satellite imagery polarization combination and thresholding methods, it extracts the water body area and the water area above the straight slope in the radar satellite images, and extracts the corner reflector elevation calibration points in the radar satellite images. The radar satellite images contain the complete water area above the straight slope. The water level monitoring module is used to extract the water boundary line between the water area in the radar satellite image and the water area above the straight slope. Based on the virtual water gauge, the module calculates the distance between the water boundary line and the elevation calibration point of the corner reflector and performs mathematical conversion to obtain the monitoring water level of the lake / reservoir area during the study period.

9. An electronic device, comprising: The method includes a memory and a processor, the memory storing program instructions that are executed by the processor, the processor invoking the program instructions to perform the method according to any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium, comprising: The non-transitory computer-readable storage medium stores computer instructions that cause the computer to perform the method described in any one of claims 1 to 7.

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