Satellite remote sensing water level determination method and device for complex river environment

Abstract

The application relates to a satellite remote sensing water level determination method and device for a complex river environment. The method comprises the following steps: acquiring a plurality of water body waveforms in a target river region, wherein the water body waveforms are determined according to echo data of a target observation period; for each water body waveform, performing sub-waveform identification according to the water body waveform to determine effective sub-waveforms in the water body waveform; for each water body waveform, if the number of effective sub-waveforms is greater than or equal to 2, a candidate sub-waveform group is determined according to the effective sub-waveforms, a target sub-waveform is determined according to a wave peak power difference value of the candidate sub-waveform group, wherein the candidate sub-waveform group is composed of two continuous effective sub-waveforms, corresponding re-tracking points are determined according to the target sub-waveforms, and a plurality of water level values of the target river region in the target observation period are determined according to the re-tracking points. The method can accurately determine the water level in the complex river environment.

Description

Technical Field

[0001] The present application relates to the field of hydrological remote sensing measurement technology, and in particular to a method and device for determining water levels using satellite remote sensing in complex river environments. Background Art

[0002] Satellite-borne altimeters utilize microwave pulse technology to enable large-scale spatial observation of river water levels. Specifically, they track the time interval between pulse transmission and reception, measure the distance between the satellite and the water surface, and then determine elevation based on the satellite's position above a reference ellipsoid. However, due to the complex and variable echo signals reflected from actual water bodies such as rivers, the waveforms received by satellite-borne altimeters are prone to exhibiting multiple peaks, and the preset tracking gate often exhibits significant deviations. Therefore, the echo signals from the water body must be re-tracked to determine the exact distance correction between the midpoint of the waveform's actual leading edge (the re-tracking point) and the preset tracking gate to improve inversion accuracy.

[0003] Existing technologies use full-waveform tracking algorithms, such as the center-of-gravity offset method and the threshold method, to identify re-tracking points and thereby determine water levels. However, existing technologies have poor overall adaptability and resistance to complex interference, resulting in low accuracy in determining water levels in complex river environments. Summary of the Invention

[0004] Based on this, it is necessary to provide a satellite remote sensing water level determination method and device for complex river environments to address the above technical problems.

[0005] In a first aspect, the present application provides a method for determining water levels using satellite remote sensing in complex river environments, comprising:

[0006] Acquire multiple water waveforms in the target river area, where the water waveforms are determined based on echo data from the target observation period;

[0007] For each water waveform, sub-waveform identification is performed according to the water waveform to determine the valid sub-waveform in the water waveform;

[0008] For each water waveform, if the number of valid sub-waveforms is greater than or equal to 2, a candidate sub-waveform group is determined based on the valid sub-waveforms, and a target sub-waveform is determined based on the peak power difference of the candidate sub-waveform group, where the candidate sub-waveform group consists of two consecutive valid sub-waveforms.

[0009] The corresponding re-tracking point is determined according to each target sub-waveform, and multiple water level values ​​of the target river area within the target observation period are determined according to each re-tracking point.

[0010] In one embodiment, performing sub-waveform identification based on the water waveform to determine a valid sub-waveform in the water waveform includes:

[0011] The sub-waveform search starting point is determined according to a preset power threshold; forward and backward searches are conducted based on the sub-waveform search starting point to determine at least one minimum point of the water waveform; multiple initial sub-waveforms are determined based on each minimum point, and the minimum point is the starting point of the leading edge of an initial sub-waveform and the ending point of the trailing edge of other initial selected sub-waveforms adjacent to the initial sub-waveform; and the valid sub-waveforms in the water waveform are determined based on the peak power of each initial sub-waveform and the power of the corresponding leading edge starting point.

[0012] In one embodiment, if the number of valid sub-waveforms is greater than 2, determining a candidate sub-waveform group based on the valid sub-waveforms includes:

[0013] A candidate sub-waveform group is determined based on the effective sub-waveform with the largest peak power and other effective sub-waveforms adjacent to the effective sub-waveform.

[0014] In one embodiment, determining a target sub-waveform based on a peak power difference of a group of candidate sub-waveforms includes:

[0015] If the difference in peak power between two candidate sub-waveforms in the candidate sub-waveform group is less than a preset threshold, the target sub-waveform is the first candidate sub-waveform; if the difference in peak power between the two candidate sub-waveforms is not less than the preset threshold, the target sub-waveform is the second candidate sub-waveform, where, in the water waveform, the first candidate sub-waveform is located before the second candidate sub-waveform.

[0016] In one embodiment, the satellite remote sensing water level determination method for a complex river environment further includes:

[0017] An initial water level time series of a target river area is obtained, where the initial water level time series includes multiple water level values ​​of the target river area within multiple observation periods. A preset water level range is obtained, where the preset water level range is determined based on the wet season water level, dry season water level, and prior water level of the target river area. Water level values ​​in the initial water level time series are screened for outliers based on the preset water level range to determine a valid water level time series, where in the valid water level time series, one observation period includes at least one valid water level value.

[0018] In one embodiment, the satellite remote sensing water level determination method for a complex river environment further includes:

[0019] The median absolute deviation of the water level value corresponding to each time window in the effective water level time series is determined by the sliding time window method, where a time window includes multiple observation periods; for the center of each time window, the abnormal water level value is identified and eliminated according to the median absolute deviation, and at least one effective water level value of the observation period corresponding to the center of the time window is determined.

[0020] In one embodiment, the satellite remote sensing water level determination method for a complex river environment further includes:

[0021] For each observation period, if the number of valid water level values ​​is greater than the preset number, a quadratic function fitting water level curve is determined based on each valid water level value. The horizontal coordinate of the quadratic function fitting water level curve is the serial number of the satellite footprint point in the target river area, and the vertical coordinate of the quadratic function fitting water level curve is the water level value corresponding to the satellite footprint point; according to each quadratic function fitting water level curve, each valid water level value of each observation period is corrected respectively; for each observation period, the target water level value of the target river area in the observation period is determined based on the multiple corrected valid water level values; and the target water level time series is determined based on the target water level value of the target river area in each observation period.

[0022] In one embodiment, obtaining multiple water waveforms in a target river area includes:

[0023] Obtain radar echo data corresponding to each satellite footprint point in the target river area; determine the peak sharpness of each radar echo data based on the maximum power value of each radar echo data; for each radar echo data, if the peak sharpness of the radar echo data is greater than the preset sharpness, determine the radar echo data as a water waveform in the target river area.

[0024] In a second aspect, the present application also provides a satellite remote sensing water level determination device for complex river environments, comprising:

[0025] An acquisition module is used to acquire multiple water waveforms in the target river area, where the water waveforms are determined based on the echo data of the target observation period;

[0026] An identification module is used to identify sub-waveforms of each water waveform according to the water waveform and determine valid sub-waveforms in the water waveform;

[0027] a first determination module configured to, for each water body waveform, determine a candidate sub-waveform group based on the valid sub-waveforms if the number of valid sub-waveforms is greater than or equal to 2, and determine a target sub-waveform based on a peak power difference of the candidate sub-waveform group, wherein the candidate sub-waveform group consists of two consecutive valid sub-waveforms;

[0028] The second determining module is used to determine the corresponding re-tracking point according to each target sub-waveform, and determine multiple water level values ​​of the target river area within the target observation period according to each re-tracking point.

[0029] In one embodiment, the identification module is specifically used to determine the sub-waveform search starting point based on a preset power threshold; search forward and backward based on the sub-waveform search starting point to determine at least one minimum point of the water body waveform; determine multiple initial sub-waveforms based on each minimum point, the minimum point being the leading edge starting point of an initial sub-waveform and the trailing edge ending point of other initial selected sub-waveforms adjacent to the initial sub-waveform; and determine the effective sub-waveform in the water body waveform based on the peak power of each initial sub-waveform and the power of the corresponding leading edge starting point.

[0030] In one embodiment, the identification module is specifically configured to determine a candidate sub-waveform group based on the effective sub-waveform with the largest peak power and other effective sub-waveforms adjacent to the effective sub-waveform.

[0031] In one embodiment, the first determination module is specifically configured to determine that if the difference in peak power between two candidate sub-waveforms in the candidate sub-waveform group is less than a preset threshold, the target sub-waveform is the first candidate sub-waveform; if the difference in peak power between the two candidate sub-waveforms is not less than the preset threshold, the target sub-waveform is the second candidate sub-waveform, wherein, in the candidate sub-waveform group, the first candidate sub-waveform is located before the second candidate sub-waveform.

[0032] In one embodiment, the second determination module is further used to obtain an initial water level time series of the target river area, the initial water level time series includes multiple water level values ​​of the target river area within multiple observation periods, and obtain a preset water level range, which is determined based on the wet season water level, dry season water level and prior water level of the target river area; the water level values ​​in the initial water level time series are screened for outliers according to the preset water level range to determine a valid water level time series, wherein in the valid water level time series, one observation period includes at least one valid water level value.

[0033] In one embodiment, the second determination module is also used to determine the median absolute deviation of the water level value corresponding to each time window in the effective water level time series through a sliding time window method, wherein a time window includes multiple observation periods; for the center of each time window, abnormal water level values ​​are identified and eliminated based on the median absolute deviation, and at least one effective water level value of the observation period corresponding to the center of the time window is determined.

[0034] In one embodiment, the second determination module is also used to, for each observation period, if the number of valid water level values ​​is greater than a preset number, determine a quadratic function fitting water level curve based on each valid water level value, the horizontal coordinate of the quadratic function fitting water level curve is the serial number of the satellite footprint point in the target river area, and the vertical coordinate of the quadratic function fitting water level curve is the water level value corresponding to the satellite footprint point; correct each valid water level value of each observation period according to each quadratic function fitting water level curve; for each observation period, determine the target water level value of the target river area in the observation period based on the multiple corrected valid water level values; and determine the target water level time series based on the target water level value of the target river area in each observation period.

[0035] In one embodiment, the acquisition module is specifically used to obtain radar echo data corresponding to each satellite footprint point in the target river area; determine the peak sharpness of each radar echo data based on the maximum power value of each radar echo data; for each radar echo data, if the peak sharpness of the radar echo data is greater than the preset sharpness, determine the radar echo data as a water waveform in the target river area.

[0036] In a third aspect, the present application further provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements any of the methods described in the first aspect when executing the computer program.

[0037] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the methods described in the first aspect above.

[0038] In a fifth aspect, the present application also provides a computer program product, comprising a computer program, which implements any of the methods described in the first aspect when executed by a processor.

[0039] The above-mentioned satellite remote sensing water level determination method and device for complex river environments obtains multiple water waveforms in the target river area, and the water waveforms are determined based on the echo data of the target observation period. For each water waveform, sub-waveform identification is performed based on the water waveform to determine the valid sub-waveforms in the water waveform. For each water waveform, if the number of valid sub-waveforms is greater than or equal to 2, a candidate sub-waveform group is determined based on the valid sub-waveforms, and the target sub-waveform is determined based on the peak power difference of the candidate sub-waveform group, wherein the candidate sub-waveform group consists of two consecutive valid sub-waveforms. The corresponding re-tracking point is determined based on each target sub-waveform, and multiple water level values ​​of the target river area within the target observation period are determined based on each re-tracking point. In this way, by identifying sub-waveforms and determining re-tracking points based on multi-wavelet analysis, the interference of environmental noise is reduced, the target sub-waveforms caused by river surface reflections are effectively identified, and the re-tracking points are accurately determined. When determining the water level, the method has good overall adaptability and resistance to complex interference, and can accurately determine the water level in a complex river environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments of the present application or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying any creative work.

[0041] Figure 1 1 is a flow chart of a method for determining water levels using satellite remote sensing in a complex river environment according to an embodiment;

[0042] Figure 2 A schematic flow chart of the step of obtaining a water waveform in one embodiment;

[0043] Figure 3 1 is a flow chart of the steps of determining a valid sub-waveform in a water waveform in one embodiment;

[0044] Figure 4 FIG1 is a flow chart of a step of determining a target sub-waveform based on a peak power difference of a group of candidate sub-waveforms in one embodiment;

[0045] Figure 5 Schematic diagram of a flow chart of a method for determining water levels using satellite remote sensing in a complex river environment according to another embodiment;

[0046] Figure 6 Schematic diagram of a flow chart of a method for determining water levels using satellite remote sensing in a complex river environment according to another embodiment;

[0047] Figure 7Schematic diagram of a flow chart of a method for determining water levels using satellite remote sensing in a complex river environment according to another embodiment;

[0048] Figure 8 This is a schematic diagram of a time series of target water levels in multiple observation periods in one embodiment;

[0049] Figure 9 Schematic diagram of a flow chart of a method for determining water levels using satellite remote sensing in a complex river environment according to another embodiment;

[0050] Figure 10 A schematic diagram of the geographical location of a test area in one embodiment;

[0051] Figure 11 A schematic diagram of determining a re-tracking point in one embodiment;

[0052] Figure 12 This is a structural block diagram of a satellite remote sensing water level determination device for a complex river environment in one embodiment;

[0053] Figure 13 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0054] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0055] Satellite-borne altimeters can achieve range-of-space observation of river water levels by using microwave pulse technology. Specifically, they can measure the distance between the satellite and the water surface by tracking the time interval between pulse emission and reception, and then determine the elevation measurement based on the satellite's position above the reference ellipsoid. However, due to the complexity and variability of the echo signals received by the reflecting surfaces of actual water bodies such as lakes, the preset tracking gates of satellite-borne altimeters often have deviations or waveforms with multiple peaks. It is necessary to re-track the echo signals of the water body to determine the exact distance correction between the midpoint of the actual leading edge of the waveform (re-tracking point) and the preset tracking gate to improve the inversion accuracy.

[0056] Existing technologies use full-waveform tracking algorithms, such as the center-of-gravity offset method and the threshold method, to identify re-tracking points and thereby determine water levels. However, existing technologies have poor overall adaptability and resistance to complex interference, resulting in low accuracy in determining water levels in complex river environments.

[0057] In view of this, the present application provides a method for determining water levels via satellite remote sensing in a complex river environment. The embodiment of the present application provides a method for determining water levels via satellite remote sensing in a complex river environment, the execution subject of which may be a device for determining water levels via satellite remote sensing in a complex river environment. The device may be implemented in the form of software, hardware, or a combination of software and hardware. The device may be embedded in or independent of a processor in a computer device in the form of hardware, or may be stored in a memory in a computer device in the form of software. In the following method embodiments, the execution subject is a computer device as an example for explanation, wherein the computer device may be a server, and the embodiment of the present application does not limit the specific type of the computer device.

[0058] In an exemplary embodiment, Figure 1 As shown, a method for determining water level using satellite remote sensing in a complex river environment is provided, comprising the following steps 101 to 104.

[0059] Step 101: Acquire multiple water waveforms in a target river area, where the water waveforms are determined based on echo data of a target observation period.

[0060] Optionally, a virtual hydrological station and buffer zone can be created at the intersection of the satellite ground orbit and the river channel, and the radar waveform corresponding to the satellite footprint point in the buffer zone during the target observation period, that is, the echo data of the target observation period, can be extracted. The target observation period can be one month, one day or one hour, which is not limited in the embodiments of the present application.

[0061] Optionally, in the embodiment of the present application, the satellite-borne altimeter is taken as an example of a radar altimeter. The radar altimeter can be carried on a spacecraft such as a satellite. It is a sensor that uses radar technology to transmit and receive signals to measure the distance from the satellite to the target river area. The water waveform can be determined by obtaining the echo data received by the radar altimeter during the target observation period.

[0062] Optionally, the water waveform may be the reflection echo data of radar waves from the water surface. In the embodiment of the present application, there is no constraint on the boundary setting of the buffer zone. A larger range may be defined near the virtual station as the buffer zone, which may include a large land area. The satellite footprint may touch both the water surface and the land. It is understandable that the echo data within the target observation period may contain not only water waveforms but also land waveforms. Therefore, the echo data needs to be screened to determine multiple water waveforms.

[0063] Optionally, the water waveform and the land waveform may be distinguished based on their waveform characteristics, thereby obtaining multiple water waveforms in the target river area.

[0064] Step 102 : For each water waveform, perform sub-waveform identification based on the water waveform to determine a valid sub-waveform in the water waveform.

[0065] Optionally, sub-waveform identification is performed on each water waveform to determine the valid sub-waveforms in each water waveform, so that waveform "small bumps" caused by environmental noise can be filtered out.

[0066] In one possible implementation, a preset energy threshold may be used to define a portion above the preset energy threshold as a possible sub-waveform region, and then a valid sub-waveform may be determined in combination with the width or slope of the waveform.

[0067] In another possible implementation method, based on a deep learning model, the peak height, width, rising and falling edge slopes of the water waveform can be extracted as characteristic parameters to identify the sub-waveforms in the water waveform and determine the valid sub-waveforms in the water waveform.

[0068] Step 103 : For each water waveform, if the number of valid sub-waveforms is greater than or equal to 2, a candidate sub-waveform group is determined based on the valid sub-waveforms, and a target sub-waveform is determined based on the peak power difference of the candidate sub-waveform group, wherein the candidate sub-waveform group consists of two consecutive valid sub-waveforms.

[0069] Optionally, in an embodiment of the present application, if the number of valid sub-waveforms determined by a water body waveform is 1, step 103 may not be performed, the valid sub-waveform may be determined as the target sub-waveform, and then step 104 may be performed. It can be understood that this step in the embodiment of the present application is for a water body waveform having 2 or more valid sub-waveforms.

[0070] Optionally, if the number of valid sub-waveforms determined by a water body waveform is equal to 2, the two valid sub-waveforms are determined as a candidate sub-waveform group.

[0071] Optionally, if the number of valid sub-waveforms determined by a water body waveform is greater than 2, two sub-waveforms need to be screened out as candidate sub-waveforms, and the two candidate sub-waveforms form a candidate sub-waveform group.

[0072] In one possible implementation, a candidate sub-waveform may be determined from multiple valid sub-waveforms based on the peak power of each valid sub-waveform, and then another valid sub-waveform adjacent to the candidate sub-waveform may also be determined as a candidate sub-waveform.

[0073] In another possible implementation, adjacent effective sub-waveforms in the water waveform may be grouped in pairs to form multiple effective sub-waveform groups, and then candidate sub-waveform groups may be determined from the multiple effective sub-waveform groups based on the peak power and value of each effective sub-waveform group.

[0074] Optionally, when determining a target sub-waveform of a water body waveform, the target sub-waveform can be determined based on the difference in peak power of two candidate sub-waveforms of the water body waveform. For example, the candidate sub-waveform with larger peak power among the two candidate sub-waveforms can be determined as the target sub-waveform based on the positive or negative value of the difference in peak power; or the target sub-waveform can be determined from the two candidate sub-waveforms by comparing the difference in peak power with a preset threshold.

[0075] Step 104 : determining corresponding re-tracking points according to each target sub-waveform, and determining a plurality of water level values ​​of the target river area within a target observation period according to each re-tracking point.

[0076] Optionally, for each water waveform, a re-tracking point corresponding to the water waveform may be determined based on the target sub-waveform and a preset re-tracking algorithm. The preset re-tracking algorithm may include a center of gravity offset method or a threshold method.

[0077] Optionally, the following introduces the process of determining the re-tracking point based on the target sub-waveform and the center of gravity offset method: based on the amplitude A, width W and center OCG of the target sub-waveform, a rectangular boundary is determined, and the tracking gate corresponding to the first intersection of the rectangular boundary and the target sub-waveform is the re-tracking point, wherein the amplitude A, width W and center OCG of the target sub-waveform are determined based on the total number of tracking gates in the target sub-waveform and the echo power on the i-th tracking gate.

[0078] Optionally, the following describes the process of determining the re-tracking point based on the target sub-waveform and threshold method: when the echo power in the target sub-waveform reaches the amplitude calculated by the center of gravity offset method or the product of the maximum amplitude of the target sub-waveform and the set threshold, the re-tracking point is determined by linear interpolation of the echo power of the previous gate of the tracking gate corresponding to the power.

[0079] Exemplarily, when using the threshold method to determine the re-tracking points, the threshold transformation method can be adopted according to the season, that is, the 50% threshold method is used when the target observation period is in the wet season (for example, May to October), and the 30% threshold method is used when the target observation period is in the dry season (for example, November to April of the following year).

[0080] Optionally, the distance from the satellite to the river surface can be corrected based on the re-tracking points. The correction formula is as follows:

[0081]

[0082] in, 、 are the subsatellite distances after and before re-tracking, respectively; is the width of the corrugated gate; For the re-tracking point, It is the preset tracking gate.

[0083] For example, the altimeter satellite is Sentinel-6A, and the level surface is EGM2008. is 257, is 0.1899 m.

[0084] Optionally, after the correction, the radar waves emitted by the satellite altimeter will be affected by water vapor, ionospheric ions, etc. when propagating in the atmosphere. Therefore, it is necessary to further correct the altimeter distance based on geophysical and propagation effects, including corrections for dry and wet troposphere, ionosphere, solid tide, and extreme tide. The specific water level value can be calculated according to the following formula:

[0085]

[0086] Among them, WSE is the water level value, that is, the river surface elevation, is the altitude of the satellite relative to the reference ellipsoid; dry, wet, iono, set, and pt correspond to the correction terms for the dry troposphere, wet troposphere, ionosphere, earth solid tide, and polar tide, respectively; is the height of the level surface relative to the reference ellipsoid.

[0087] Optionally, during the target observation period, for a water body waveform, after determining the re-tracking point based on its target sub-waveform, the corresponding water level value of the water body waveform in the target river area can be calculated according to the above method. For multiple water body waveforms, there are multiple water level values.

[0088] The above-mentioned satellite remote sensing water level determination method for complex river environments obtains multiple water waveforms in the target river area, and the water waveforms are determined based on the echo data of the target observation period. For each water waveform, sub-waveforms are identified based on the water waveform to determine the valid sub-waveforms in the water waveform. For each water waveform, if the number of valid sub-waveforms is greater than or equal to 2, a candidate sub-waveform group is determined based on the valid sub-waveforms, and the target sub-waveform is determined based on the peak power difference of the candidate sub-waveform group. The candidate sub-waveform group consists of two consecutive valid sub-waveforms. The corresponding re-tracking point is determined based on each target sub-waveform, and multiple water level values ​​of the target river area within the target observation period are determined based on each re-tracking point. In this way, by identifying sub-waveforms and determining re-tracking points based on multi-wavelet analysis, the interference of environmental noise is reduced, the target sub-waveforms caused by river surface reflections are effectively identified, and the re-tracking points are accurately determined. When determining the water level, the method has good overall adaptability and resistance to complex interference, and can accurately determine the water level in complex river environments.

[0089] In an exemplary embodiment, Figure 2As shown, optionally, obtaining multiple water waveforms in the target river area includes the following steps 201 to 203. Among them:

[0090] Step 201: Acquire radar echo data corresponding to each satellite footprint point in the target river area.

[0091] Optionally, the radar echo data corresponding to each footprint point in the buffer zone received by the satellite-borne altimeter can be obtained. If there are other water bodies along the satellite ground track in the buffer zone, a rough latitude boundary can be added to finely filter out multiple radar echo data in the target river area from the above radar echo data.

[0092] Optionally, the radar echo data may be high-resolution radar echo data, such as synthetic aperture radar data.

[0093] Step 202: Determine the peak sharpness of each radar echo data according to the maximum power value of each radar echo data.

[0094] Optionally, unlike the land surface, the reflection of radar waves by the water surface is similar to mirror reflection, and the echo received by the satellite altimeter contains at least one narrow and high pulse. Therefore, the water waveform can be determined from multiple radar echo data based on the characteristics of the radar echo data of the water surface.

[0095] Optionally, the peak sharpness of the radar echo data may measure the sharpness or steepness of a peak in the radar echo data. For a piece of radar echo data, the pulse peakness value (PP) corresponding to the radar echo data may be determined according to the following formula:

[0096]

[0097] in, is the maximum power of radar echo data; n is the total number of waveform tracking gates; is the waveform power of the i-th tracking gate. For most radar echo data, the waveform powers of the first four gates and the last four gates are caused by environmental noise and are therefore not included in the total power.

[0098] Exemplarily, n may be 512, corresponding to the total number of gates in the Sentinel-6A synthetic aperture radar mode.

[0099] Step 203 : For each radar echo data, if the peak sharpness of the radar echo data is greater than a preset sharpness, the radar echo data is determined to be a water waveform in the target river area.

[0100] For example, taking the preset sharpness as 1.5 as an example, the peak sharpness of each radar echo data can be calculated separately, and the radar echo data with a peak sharpness greater than 1.5 can be determined as the water waveform in the target river area.

[0101] Optionally, the horizontal axis of the water waveform is the tracking gate, and the vertical axis is the power of the radar echo data. Due to the complex surface conditions of the water body, the radar echo signal may appear at different times and locations. The tracking gate can be used to determine within which time range or distance range to search for and analyze a specific radar echo signal, that is, to determine the range for capturing and processing the radar echo signal.

[0102] Optionally, the maximum power value of the radar echo data can be compared with a preset power threshold. If the maximum power value of the radar echo data is greater than the preset power threshold, the corresponding radar echo data will be determined as the water waveform in the target river area. For example, the preset power threshold can be 1000W.

[0103] Due to the complex conditions of the water body's reflecting surface, the above-mentioned screening of radar echo data based on peak sharpness eliminates radar echo data affected by the surrounding terrain environment and radar echo data that does not belong to the target river area. This can accurately obtain the water body waveform in the target river area, thereby improving the accuracy of subsequent water level determination.

[0104] In an exemplary embodiment, Figure 3 As shown, optionally, performing sub-waveform identification based on the water waveform to determine a valid sub-waveform in the water waveform includes the following steps 301 to 303. In which:

[0105] Step 301: Determine a sub-waveform search starting point according to a preset power threshold.

[0106] Optionally, a preset power threshold can be obtained, and the tracking gate in the water waveform with power greater than the preset power threshold can be used as the starting point of the sub-waveform search. For example, 90% of the maximum power in the water waveform can be determined as the preset power threshold.

[0107] Optionally, in the water body waveform, there may be a tracking gate whose power is greater than a preset power threshold. Within the horizontal axis range, the first tracking gate in the water body waveform whose power is greater than the preset power threshold can be used as the starting point of the sub-waveform search, or the last tracking gate whose power is greater than the preset power threshold can be used as the starting point of the sub-waveform search, or the tracking gate in the middle whose power is greater than the preset power threshold can be used as the starting point of the sub-waveform search, or all tracking gates whose power is greater than the preset power threshold can be used as the starting point of the sub-waveform search. The embodiments of the present application do not limit this.

[0108] Step 302: Search forward and backward based on the sub-waveform search starting point to determine at least one minimum point of the water waveform.

[0109] Alternatively, the minimum point may be a point where the waveform of the water body changes from descending to ascending.

[0110] In one possible implementation, the process of determining a minimum point based on a water waveform may include: starting from the sub-waveform search starting point, traversing the tracking gates in the water waveform forward or backward; when the power corresponding to a certain tracking gate is less than a preset search threshold, and the powers of the tracking gates adjacent to the tracking gate are all higher than the preset search threshold, the tracking gate may be determined as a minimum point.

[0111] Optionally, in the above determination process, the preset search threshold may be a fixed value, or may be dynamically calculated based on the statistical characteristics of the water body waveform data, which is not limited in the embodiment of the present application.

[0112] In another possible implementation method, it is also possible to start from the sub-waveform search starting point, and approximately calculate the derivative of the partial water waveform based on the difference method forward or backward, and then further determine the minimum point in combination with the second-order difference.

[0113] Optionally, since water reflects radar waves more strongly than land, during the traversal process, if the power of the tracking gate drops to the minimum power threshold, the minimum point can no longer be determined. The minimum power threshold can be 0.05P max , where P max is the maximum power value of the water waveform.

[0114] Step 303 : determining a plurality of initial sub-waveforms according to the minimum points. The minimum points are the starting point of the leading edge of an initial sub-waveform and the ending points of the trailing edges of other initial sub-waveforms adjacent to the initial sub-waveform.

[0115] Optionally, the waveform between two adjacent minimum values ​​can be determined as an initial sub-waveform, the waveform between the first minimum point in the water body waveform and the starting tracking gate of the water body waveform can be determined as an initial sub-waveform, and the waveform between the last minimum point in the water body waveform and the ending tracking gate of the water body waveform can also be determined as an initial sub-waveform.

[0116] Optionally, the initial sub-waveforms with peak power less than a preset threshold value generally do not come from water bodies and can be eliminated.

[0117] Step 304 : Determine the effective sub-waveforms in the water waveform according to the peak power of each initial sub-waveform and the power of the corresponding leading edge starting point.

[0118] Optionally, for each initial sub-waveform, if the peak power of the initial sub-waveform and the power at the starting point of the leading edge of the initial sub-waveform meet a preset condition, the initial sub-waveform is determined as a valid sub-waveform in the water waveform.

[0119] Optionally, the power difference between the peak power of the initial sub-waveform and the peak power of the leading edge starting point, and / or the power slope can be calculated; if the power difference and / or the power slope meet the preset conditions, the initial sub-waveform can be determined as a valid sub-waveform; if the conditions are not met, the initial sub-waveform is considered to be a small "bump" caused by environmental noise, and is included in the previous valid sub-waveform without being considered separately.

[0120] Optionally, the preset condition may be that the power slope is not less than a preset slope threshold, or the power difference is not less than a preset power difference. The slope threshold is determined according to the peak power of the initial sub-waveform and the width of a tracking gate. For example, the slope threshold may be 0.05 P max / bin, where bin is the width of a tracking gate, and the preset power difference is determined according to the peak power of the initial sub-waveform. For example, the preset power difference can be 0.2P max ; The preset condition may be that the power slope is not less than a preset slope threshold and the power difference is not less than a preset power difference.

[0121] The above method determines at least one minimum point based on the water body waveform, determines multiple initial sub-waveforms based on each minimum point, filters out small bumps caused by environmental noise based on the peak power of each initial sub-waveform and the power of the corresponding leading edge starting point, and determines the effective sub-waveform in the water body waveform.

[0122] In an embodiment of an embodiment, optionally, when the number of valid sub-waveforms is greater than 2, determining a candidate sub-waveform group according to the valid sub-waveforms includes:

[0123] The candidate sub-waveform group is determined according to the effective sub-waveform with the largest peak power and other effective sub-waveforms adjacent to the effective sub-waveform.

[0124] Optionally, an effective sub-waveform with the largest peak power among multiple effective sub-waveforms is determined as one of the candidate sub-waveforms. After determining a candidate sub-waveform, another candidate sub-waveform can be determined from one or two effective sub-waveforms adjacent to the effective sub-waveform. One of the adjacent effective sub-waveforms can be selected as another candidate sub-waveform in the candidate sub-waveform group, or an adjacent effective sub-waveform with a larger peak power can be determined as another candidate sub-waveform.

[0125] The candidate sub-waveform group is determined based on the effective sub-waveform with the largest peak power and other effective sub-waveforms adjacent to the effective sub-waveform. Since reflection peaks with higher power usually correspond to water bodies or bright objects on land (such as building roofs), the candidate sub-waveform group can be accurately determined based on the peak power.

[0126] In an exemplary embodiment, Figure 4 As shown, optionally, determining the target sub-waveform according to the peak power difference of the candidate sub-waveform group includes the following steps 401 to 402. In which:

[0127] Step 401: If the difference between the peak powers of two candidate sub-waveforms in the candidate sub-waveform group is less than a preset threshold, the target sub-waveform is the first candidate sub-waveform.

[0128] Step 402: If the difference between the peak powers of the two candidate sub-waveforms is not less than a preset threshold, the target sub-waveform is the second candidate sub-waveform.

[0129] Among them, in the candidate sub-waveform group, the first candidate sub-waveform is located before the second candidate sub-waveform.

[0130] Optionally, the preset threshold value can be determined based on the maximum power of the water waveform, for example, 0.15P max .

[0131] For example, the peak power difference between the two candidate sub-waveforms is less than 0.15 P max , the first candidate sub-waveform is determined as the target sub-waveform, and the 50% threshold method is used at the trailing edge of the first candidate sub-waveform to determine the re-tracking point; the peak power difference between the two candidate sub-waveforms is not less than 0.15 P max , the second candidate sub-waveform is determined as the target sub-waveform, and the 20% threshold method is used on the leading edge of the second candidate sub-waveform.

[0132] If the difference in peak power between two candidate sub-waveforms in the candidate sub-waveform group is less than a preset threshold, the target sub-waveform is the first candidate sub-waveform; if the difference in peak power between the two candidate sub-waveforms is not less than the preset threshold, the target sub-waveform is the second candidate sub-waveform. In this way, by using multiple sub-waveforms to determine the target sub-waveform by comparing the power of each sub-waveform, and thus determining the re-tracking point based on the target sub-waveform, the re-tracking point can be accurately determined, reducing the impact of environmental noise.

[0133] In an exemplary embodiment, Figure 5 As shown, optionally, the satellite remote sensing water level determination method for complex river environments further includes the following steps 501 to 503. Among them:

[0134] Step 503: Acquire an initial water level time series of the target river area, where the initial water level time series includes multiple water level values ​​of the target river area within multiple observation periods.

[0135] Optionally, water level values ​​of multiple observation periods can be obtained from the database, or radar echo data of multiple observation periods can be obtained to determine the corresponding water level values, which will not be described in detail in the embodiments of the present application.

[0136] It is understandable that one observation period may include water level values ​​corresponding to multiple satellite footprint points, and the initial water level time series of the target river area may be determined based on the multiple water level values ​​of each observation period.

[0137] For example, taking an observation period of 1 day as an example, multiple observation periods may include every day from 2023 to 2024, and the initial water level time series may include the water level value of every day from 2023 to 2024.

[0138] Step 502: Obtain a preset water level range.

[0139] Among them, the preset water level range is determined based on the wet season water level, dry season water level and prior water level of the target river area.

[0140] Optionally, the wet season water level may be a median or average value of a plurality of water level values ​​in the target river region during the wet season. Similarly, the dry season water level may be a median or average value of a plurality of water level values ​​in the target river region during the dry season.

[0141] Optionally, the preset water level range can be determined based on the Digital Elevation Model (DEM) of the target river area. First, the water level difference between the wet season water level and the dry season water level is calculated, and the preset water level range is determined based on the prior water level and the water level difference. The range of the preset water level can be determined as a range of one-times the difference above and below the prior water level. The expression is as follows:

[0142] [DEM- WSE ̿ wet - WSE ̿ dry , DEM+ WSE ̿ wet - WSE ̿ dry ]

[0143] in, represents the prior water level, represents the median water level in the wet season, represents the median of the dry season water level. The prior water level can be obtained from Google Earth. The median of the wet season water level and the median of the dry season water level can be determined based on the initial water level sequence. For example, the prior water level can be 2917 m.

[0144] Step 503 , screening the water level values ​​in the initial water level time series for abnormal values ​​according to a preset water level range to determine a valid water level time series, wherein in the valid water level time series, one observation period includes at least one valid water level value.

[0145] Optionally, the water level values ​​of each observation period in the initial time series can be screened for outliers. For one observation period, multiple water level values ​​of the observation period can be compared with a preset water level range. If the water level value is within the preset water level range, the water level value is determined to be a valid water level value. If it is not within the preset water level range, it is considered an outlier and is removed. For example, when three water body waveforms are determined from the radar echo data of one observation period, the water level values ​​corresponding to the three water body waveforms are calculated according to the steps in the above embodiment, and then the three water level values ​​are screened for outliers according to the preset water level range. Taking the existence of one outlier as an example, by removing the outlier, two valid water level values ​​that meet the preset water level range can be obtained.

[0146] Optionally, the water level values ​​of each observation period may be screened to obtain valid water level values ​​that meet the requirements, and further, a valid water level time series may be determined based on the valid water level values ​​of each observation period.

[0147] The above-mentioned screening of outliers in the water level values ​​in the initial water level time series by presetting the water level range can effectively eliminate outliers.

[0148] In an exemplary embodiment, Figure 6 As shown, optionally, the satellite remote sensing water level determination method for complex river environment further includes the following steps 601 to 602. Among them:

[0149] Step 601 : Determine the median absolute deviation of the water level value corresponding to each time window in the effective water level time series by a sliding time window method, wherein one time window includes multiple observation periods.

[0150] Optionally, a preset time window size and a preset step size may be obtained, and the effective water level time series may be slid to process water level values ​​in different time periods.

[0151] Optionally, the time window size can be the length of the time range covered by the window, which determines the amount of data analyzed each time. For example, the time window size can be two months, including at least five Sentinel-6A observation cycles.

[0152] Optionally, in a time window, the median of multiple water level values ​​over multiple observation periods in the time window can be calculated. The absolute value of the difference between each water level value in the time window and the median is then calculated to obtain the absolute deviation of each water level value from the median. The median of the multiple absolute deviations is then determined to obtain the median absolute deviation. The median absolute deviation (MAD) of a time window can be expressed by the following formula:

[0153]

[0154] Among them, WSE is the water level value in a time window, is the median of multiple water level values ​​in a time window, The median of the absolute deviations of the water level values ​​from the median in a time window. For example, in a time window, the valid water level values ​​include {12, 15, 18, 100, 25, 30,}. First, the median water level is calculated to be 20. Then, the absolute deviations of the valid water level values ​​from the median water level are calculated to be {8, 5, 2, 80, 5, 10, 0}. The median of these absolute deviations, the median absolute deviation (MAD), is 5.

[0155] Step 602 : For the center of each time window, identify and eliminate abnormal water level values ​​based on the median absolute deviation, and determine at least one valid water level value of the observation period corresponding to the center of the time window.

[0156] Optionally, the center of the time window can correspond to an observation period with multiple valid water level values. The product of the median absolute deviation and a preset multiple can be determined as the deviation threshold, and then the absolute deviation between each valid water level value and the median water level value of the observation period is calculated. If the absolute deviation of a valid water level value is greater than the deviation threshold, the valid water level value is regarded as an abnormal water level value and is eliminated.

[0157] Exemplarily, the deviation threshold may be 3MAD, that is, the preset multiple may be 3. For example, in the effective water level values ​​of the above time window, the deviation threshold is 15, and the effective water level values ​​corresponding to the observation period at the center of the time window include {18, 100, 25}, wherein the absolute deviation between the effective water level value 100 and the water level median 20 is 80, which is greater than the deviation threshold 15. Therefore, the effective water level value 100 is regarded as an abnormal water level value and is eliminated. At this time, the effective water level values ​​of the observation period include {18, 25}.

[0158] The above method determines the median absolute deviation of the water level value corresponding to each time window in the effective water level time series through the sliding time window method, wherein a time window includes multiple observation periods; for the center of each time window, the abnormal water level value is identified and eliminated according to the median absolute deviation, and at least one effective water level value of the observation period corresponding to the center of the time window is determined. In this way, the continuity of the change of the water level series is used to further identify the outliers, and the identification of outliers is achieved through two median calculations. It is not easily affected by extreme values ​​and can robustly and effectively eliminate outliers.

[0159] In another possible implementation, outliers can be eliminated using the double standard deviation criterion.

[0160] In an exemplary embodiment, Figure 7 As shown, optionally, the satellite remote sensing water level determination method for complex river environments further includes the following steps 701 to 704. Among them:

[0161] Step 701: For each observation period, if the number of valid water level values ​​is greater than a preset number, a quadratic function fitting water level curve is determined according to each valid water level value.

[0162] Among them, the horizontal coordinate of the quadratic function fitting water level curve is the serial number of the satellite footprint point in the target river area, and the vertical coordinate of the quadratic function fitting water level curve is the water level value corresponding to the satellite footprint point.

[0163] It can be understood that for an observation period in the effective water level time series, when determining the quadratic function fitting water level curve based on the effective water level values ​​of the observation period, since at least 3 data points are required for quadratic function fitting, the preset number can be 2, and the number of effective water level values ​​needs to be greater than 2; when the number of effective water level values ​​is 2, there is no need to perform the correction process in the embodiment of the present application, and the median / average of the target water level value can be used as the target water level value of the target river area within the observation period; when the number of effective water level values ​​is 1, the effective water level value is determined as the target water level value of the target river area within the observation period.

[0164] Optionally, when performing quadratic function fitting based on the effective water level values ​​within an observation period, the fitting can be performed using the least squares method or the matrix method to obtain a quadratic function fitting curve corresponding to the observation period, the expression of which is as follows:

[0165]

[0166] in, is the quadratic function fitting water level, s0 is the number of the footprint point of the river channel profile along the satellite track; a, b, c are the parabola coefficients of the least squares fitting method. It can be understood that the fitting water level determined by the quadratic fitting curve is There is a difference between the effective water level value WSE corresponding to the footprint point during the observation period.

[0167] Step 702: Correct each effective water level value in each observation period according to each quadratic function fitting water level curve.

[0168] It can be understood that if the number of valid water level values ​​in an observation period is greater than 2, the quadratic function fitting curve corresponding to the observation period can be determined based on the valid water level values, and then the valid water level values ​​in the observation period can be corrected based on the quadratic function fitting curve.

[0169] Optionally, in river surface elevation observations, the hanging effect often occurs, especially for narrow and wide rivers. Under this effect, the water levels on both sides will be lower than the water level in the center of the river. A quadratic function can be used to fit the effective water level value within an observation period, and the effective water level value within the observation period can be geometrically corrected based on the median reference plane of the original water level profile.

[0170] Optionally, when correcting the effective water level value within an observation period, the median value of multiple effective water level values ​​within the observation period may be determined first. Then, for an effective water level value, the effective water level value may be corrected by the difference between the effective water level value and the corresponding fitted water level value and the median value of the effective water level value within the observation period, which may be expressed by the following formula:

[0171]

[0172] in, is one of the valid water level values ​​within the observation period, is the fitted water level value corresponding to the effective water level value, is the median of the effective water level values ​​during the observation period, It is a valid water level value after modification.

[0173] Step 703: For each observation period, determine the target water level value of the target river area within the observation period according to the corrected multiple effective water level values.

[0174] Optionally, for an observation period, the target water level value of the target river area within the observation period can be determined based on the median of the multiple corrected valid water level values, or the target water level value of the target river area within the observation period can be determined based on the average of the multiple corrected target water level values. This embodiment of the present application does not limit this.

[0175] Step 704 : determining a target water level time series according to the target water level value of the target river area in each observation period.

[0176] Optionally, the above steps 701 to 703 may be performed for each observation period in the effective water level time series to determine the target water level value of each observation period, and then a target water level time series may be constructed according to the target water level value of each observation period.

[0177] For the above-mentioned observation period, if the number of valid water level values ​​is greater than the preset number, a quadratic function fitting water level curve is determined according to each valid water level value, each valid water level value is corrected according to the quadratic function fitting water level curve, and the target water level value of the target river area within the observation period is determined based on the corrected multiple valid water level values. In this way, the hanging effect can be corrected and the accuracy of the water level determination of the target river area can be improved.

[0178] As an optional implementation, Figure 8 As shown, the satellite remote sensing water level determination method for a complex river environment provided in the embodiment of the present application may include the following specific steps:

[0179] Step 801: Acquire radar echo data corresponding to each satellite footprint point in the target river area.

[0180] Step 802: Determine the peak sharpness of each radar echo data according to the maximum power value of each radar echo data.

[0181] Step 803 : For each radar echo data, if the peak sharpness of the radar echo data is greater than a preset sharpness, the radar echo data is determined to be a water waveform in the target river area.

[0182] Step 804: For each water body waveform, determine a sub-waveform search starting point according to a preset power threshold.

[0183] Step 805: For each water waveform, search forward and backward based on the sub-waveform search starting point to determine at least one minimum point of the water waveform.

[0184] Step 806 : For each water waveform, multiple initial sub-waveforms are determined based on the minimum points. The minimum points are the starting point of the leading edge of an initial sub-waveform and the ending points of the trailing edges of other initial selected sub-waveforms adjacent to the initial sub-waveform.

[0185] Step 807 : For each water waveform, determine the effective sub-waveform in the water waveform according to the peak power of each initial sub-waveform and the power of the corresponding leading edge starting point.

[0186] Step 808 : For each water waveform, if the number of valid sub-waveforms is greater than 2, a candidate sub-waveform group is determined based on the valid sub-waveform with the largest peak power and other valid sub-waveforms adjacent to the valid sub-waveform, wherein the candidate sub-waveform group consists of two consecutive valid sub-waveforms.

[0187] Step 809 : For each water body waveform, if the number of valid sub-waveforms is equal to 2, the valid sub-waveform is determined as a candidate sub-waveform group.

[0188] In step 810 , if the difference between the peak powers of two candidate sub-waveforms in the candidate sub-waveform group is less than a preset threshold, the target sub-waveform is the first candidate sub-waveform.

[0189] Step 811 : If the difference in peak power between the two candidate sub-waveforms is not less than a preset threshold, the target sub-waveform is the second candidate sub-waveform, wherein the first candidate sub-waveform is located before the second candidate sub-waveform in the candidate sub-waveform group.

[0190] Step 812: For each water body waveform, if the number of valid sub-waveforms is 1, the valid sub-waveform is determined as the target sub-waveform.

[0191] Step 813 , determining corresponding re-tracking points according to each target sub-waveform, and determining multiple water level values ​​of the target river area within the target observation period according to each re-tracking point.

[0192] Step 814 , obtaining an initial water level time series of the target river area, where the initial water level time series includes multiple water level values ​​of the target river area in multiple observation periods.

[0193] Step 815 , obtaining a preset water level range, where the preset water level range is determined based on the wet season water level, dry season water level, and prior water level of the target river area.

[0194] Step 816 , screening the water level values ​​in the initial water level time series for abnormal values ​​according to a preset water level range, and determining a valid water level time series, wherein in a valid water level time series, one observation period includes at least one valid water level value.

[0195] Step 817 , determining the median absolute deviation of the water level value corresponding to each time window in the effective water level time series by a sliding time window method, wherein one time window includes multiple observation periods.

[0196] Step 818 : For the center of each time window, identify and eliminate abnormal water level values ​​based on the median absolute deviation, and determine at least one valid water level value of the observation period corresponding to the center of the time window.

[0197] Step 819: For each observation period, if the number of valid water level values ​​is greater than a preset number, a quadratic function fitting water level curve is determined based on each valid water level value.

[0198] Among them, the horizontal coordinate of the quadratic function fitting water level curve is the serial number of the satellite footprint point in the target river area, and the vertical coordinate of the quadratic function fitting water level curve is the water level value corresponding to the satellite footprint point;

[0199] Step 820: Correct each effective water level value of each observation period according to each quadratic function fitting water level curve.

[0200] Step 821 : For each observation period, determine the target water level value of the target river area within the observation period according to the corrected multiple effective water level values.

[0201] Step 822 : determining a target water level time series according to the target water level value of the target river area in each observation period.

[0202] For example, the area near the Yarlung Zangbo River Nuxia Hydrological Station can be selected as the test area. This area is located in the southeastern part of the Qinghai-Tibet Plateau, with complex topography, deep river valleys, cliffs on both sides, and winding rivers. The average altitude of the survey area is 2900m, and the average width of the river is 300m. The complex terrain of the high mountain canyons and the changeable underlying surface provide a good test site for verifying the performance of the embodiments of the present application in a complex river environment. A virtual hydrological station (94.85°E, 29.52°N) and a buffer zone are created at the intersection of the Sentinel-6A ground track and the river, such as Figure 9 As shown, the geographical location of the buffer zone and satellite footprint points are included.

[0203] Optional, Figure 10 (a) and (b) are the re-tracking points of the complex radar echo data determined according to the embodiment of the present application, where the dotted line represents the real tracking point inferred based on the measured water level, and the vertical solid line represents the re-tracking point determined according to the embodiment of the present application. It can be seen from the figure that the difference between the re-tracking point and the real tracking point is very small. Figure 11 This is a possible time series of target water levels in the target river area within multiple observation periods. As can be seen from the figure, the corrected water level value is close to the actual measured water level value, with a root mean square error of 0.20 m. The satellite remote sensing water level determination method for complex river environments provided in the embodiment of the present application has high accuracy.

[0204] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0205] Based on the same inventive concept, the present application also provides a device for determining water levels using satellite remote sensing in complex river environments. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations in one or more device embodiments provided below can be found in the aforementioned limitations of the method for determining water levels using satellite remote sensing in complex river environments, and will not be further elaborated here.

[0206] In an exemplary embodiment, Figure 12 As shown, a satellite remote sensing water level determination device 1200 for a complex river environment is provided, comprising: an acquisition module 1201, an identification module 1202, a first determination module 1203 and a second determination module 1204, wherein:

[0207] An acquisition module 1201 is configured to acquire multiple water waveforms in a target river area, where the water waveforms are determined based on echo data of a target observation period.

[0208] Identification module 1202, for performing sub-waveform identification on each water waveform according to the water waveform, and determining a valid sub-waveform in the water waveform;

[0209] A first determining module 1203 is configured to, for each water waveform, determine a candidate sub-waveform group based on the valid sub-waveforms if the number of valid sub-waveforms is greater than or equal to 2, and determine a target sub-waveform based on the peak power difference of the candidate sub-waveform group, wherein the candidate sub-waveform group consists of two consecutive valid sub-waveforms;

[0210] The second determining module 1204 is configured to determine a corresponding re-tracking point according to each target sub-waveform, and determine a plurality of water level values ​​of the target river area within a target observation period according to each re-tracking point.

[0211] In one embodiment, the identification module 1202 is specifically used to determine the sub-waveform search starting point based on a preset power threshold; search forward and backward based on the sub-waveform search starting point to determine at least one minimum point of the water body waveform; determine multiple initial sub-waveforms based on each minimum point, the minimum point being the starting point of the leading edge of an initial sub-waveform and the ending point of the trailing edge of other initial selected sub-waveforms adjacent to the initial sub-waveform; and determine the valid sub-waveform in the water body waveform based on the peak power of each initial sub-waveform and the power of the corresponding leading edge starting point.

[0212] In one embodiment, the identification module 1202 is specifically configured to determine a candidate sub-waveform group based on the valid sub-waveform with the largest peak power and other valid sub-waveforms adjacent to the valid sub-waveform.

[0213] In one embodiment, the first determination module 1203 is specifically configured to determine, if the difference in peak power between two candidate sub-waveforms in the candidate sub-waveform group is less than a preset threshold, that the target sub-waveform is the first candidate sub-waveform; and if the difference in peak power between the two candidate sub-waveforms is not less than the preset threshold, that the target sub-waveform is the second candidate sub-waveform, wherein, in the candidate sub-waveform group, the first candidate sub-waveform is located before the second candidate sub-waveform.

[0214] In one embodiment, the second determination module 1204 is further used to obtain an initial water level time series of the target river area, the initial water level time series includes multiple water level values ​​of the target river area within multiple observation periods, and obtain a preset water level range, which is determined based on the wet season water level, dry season water level and prior water level of the target river area; the water level values ​​in the initial water level time series are screened for outliers according to the preset water level range to determine a valid water level time series, wherein in the valid water level time series, one observation period includes at least one valid water level value.

[0215] In one embodiment, the second determination module 1204 is also used to determine the median absolute deviation of the water level value corresponding to each time window in the effective water level time series through a sliding time window method, wherein a time window includes multiple observation periods; for the center of each time window, abnormal water level values ​​are identified and eliminated based on the median absolute deviation, and at least one effective water level value of the observation period corresponding to the center of the time window is determined.

[0216] In one embodiment, the second determination module 1204 is also used to, for each observation period, if the number of valid water level values ​​is greater than a preset number, determine a quadratic function fitting water level curve based on each valid water level value, the horizontal coordinate of the quadratic function fitting water level curve is the serial number of the satellite footprint point in the target river area, and the vertical coordinate of the quadratic function fitting water level curve is the water level value corresponding to the satellite footprint point; correct each valid water level value of each observation period according to each quadratic function fitting water level curve; for each observation period, determine the target water level value of the target river area in the observation period according to the multiple corrected valid water level values; and determine the target water level time series according to the target water level value of the target river area in each observation period.

[0217] In an exemplary embodiment, the acquisition module 1201 is specifically used to obtain radar echo data corresponding to each satellite footprint point in the target river area; determine the peak sharpness of each radar echo data based on the maximum power value of each radar echo data; for each radar echo data, if the peak sharpness of the radar echo data is greater than the preset sharpness, determine the radar echo data as a water waveform in the target river area.

[0218] Each module in the aforementioned satellite remote sensing water level determination device for complex river environments can be implemented in whole or in part through software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in the computer device in the form of software, so that the processor can call and execute the corresponding operations of each module.

[0219] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Figure 13 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O) and a communication interface. The processor, memory and input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a satellite remote sensing water level determination method for a complex river environment is implemented.

[0220] Those skilled in the art will understand that Figure 13 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0221] In an exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps described in any of the above method embodiments when executing the computer program.

[0222] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps described in any of the above method embodiments are implemented.

[0223] In one embodiment, a computer program product is provided, comprising a computer program, which implements the steps of any of the above method embodiments when executed by a processor.

[0224] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), quantum computing-based data processing logic devices, artificial intelligence (AI) processors, and the like.

[0225] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0226] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for determining water level using satellite remote sensing in complex river environments, characterized in that: The method comprises: Acquire multiple water waveforms in a target river area, wherein the water waveforms are determined based on echo data of a target observation period; For each of the water waveforms, performing sub-waveform identification according to the water waveform to determine a valid sub-waveform in the water waveform; For each of the water waveforms, if the number of the valid sub-waveforms is greater than or equal to 2, determining a candidate sub-waveform group based on the valid sub-waveforms, and determining a target sub-waveform based on the peak power difference of the candidate sub-waveform group, wherein the candidate sub-waveform group consists of two consecutive valid sub-waveforms; Determining a corresponding re-tracking point according to each target sub-waveform, and determining a plurality of water level values ​​of the target river area within the target observation period according to each re-tracking point; The performing sub-waveform identification according to the water waveform to determine a valid sub-waveform in the water waveform includes: Determine the sub-waveform search starting point according to a preset power threshold; Searching forward and backward based on the sub-waveform search starting point to determine at least one minimum point of the water waveform, and stopping the search when the power of the water waveform is less than a minimum power threshold; Determine a plurality of initial sub-waveforms according to the minimum points, wherein the minimum points are the starting point of the leading edge of an initial sub-waveform and the ending point of the trailing edge of other initial selected sub-waveforms adjacent to the initial sub-waveform; For each of the initial sub-waveforms, if the peak power of the initial sub-waveform and the power at the leading edge starting point of the sub-waveform meet a preset condition, the sub-waveform is determined to be a valid sub-waveform; the preset condition includes that a power difference between the peak power and the power at the leading edge starting point is not less than a preset power difference, and / or the preset condition includes that a power slope between the peak power and the power at the leading edge starting point is not less than a preset power slope threshold; The determining of the target sub-waveform according to the peak power difference of the candidate sub-waveform group includes: If the difference between the peak powers of two candidate sub-waveforms in the candidate sub-waveform group is less than a preset threshold, the target sub-waveform is the first candidate sub-waveform; If the difference in peak power between the two candidate sub-waveforms is not less than a preset threshold, the target sub-waveform is the second candidate sub-waveform, wherein in the candidate sub-waveform group, the first candidate sub-waveform is located before the second candidate sub-waveform.

2. The method according to claim 1, characterized in that If the number of the valid sub-waveforms is greater than 2, determining a candidate sub-waveform group according to the valid sub-waveforms includes: The candidate sub-waveform group is determined according to the effective sub-waveform with the largest peak power and other effective sub-waveforms adjacent to the effective sub-waveform.

3. The method according to claim 1, characterized in that The method further comprises: Acquire an initial water level time series of a target river region, wherein the initial water level time series includes multiple water level values ​​of the target river region within multiple observation periods; Obtaining a preset water level range, where the preset water level range is determined based on the wet season water level, the dry season water level, and a priori water level of the target river area; The water level values ​​in the initial water level time series are screened for abnormal values ​​according to the preset water level range to determine a valid water level time series, wherein in the valid water level time series, one observation period includes at least one valid water level value.

4. The method according to claim 3, characterized in that The method further comprises: Determine the median absolute deviation of the water level values ​​corresponding to each time window in the effective water level time series by a sliding time window method, wherein a time window includes multiple observation periods; For the center of each time window, abnormal water level values ​​are identified and eliminated according to the median absolute deviation, and at least one valid water level value of the observation period corresponding to the center of the time window is determined.

5. The method according to claim 3 or 4, characterized in that The method further comprises: For each of the observation periods, if the number of valid water level values ​​is greater than a preset number, a quadratic function fitting water level curve is determined according to each of the valid water level values, the abscissa of the quadratic function fitting water level curve being the serial number of the satellite footprint point in the target river area, and the ordinate of the quadratic function fitting water level curve being the water level value corresponding to the satellite footprint point; Correcting the effective water level values ​​of the observation periods according to the quadratic function fitting water level curves; For each of the observation periods, determining a target water level value of the target river area within the observation period according to the corrected multiple effective water level values; The target water level time series is determined according to the target water level value of the target river area in each of the observation periods.

6. The method according to claim 1, characterized in that The step of obtaining a plurality of water waveforms in the target river area includes: Acquire radar echo data corresponding to each satellite footprint point in the target river area; determining the peak sharpness of each radar echo data according to the maximum power value of each radar echo data; For each radar echo data, if the peak sharpness of the radar echo data is greater than a preset sharpness, the radar echo data is determined to be a water waveform in the target river area.

7. A satellite remote sensing water level determination device for complex river environments, characterized in that: The device comprises: An acquisition module, configured to acquire a plurality of water waveforms in a target river area, wherein the water waveforms are determined based on echo data of a target observation period; an identification module, configured to perform sub-waveform identification on each of the water waveforms according to the water waveform, and determine a valid sub-waveform in the water waveform; a first determining module configured to, for each of the water body waveforms, determine a candidate sub-waveform group based on the valid sub-waveforms if the number of the valid sub-waveforms is greater than or equal to 2, and determine a target sub-waveform based on a peak power difference of the candidate sub-waveform group, wherein the candidate sub-waveform group consists of two consecutive valid sub-waveforms; A second determining module is configured to determine a corresponding re-tracking point according to each target sub-waveform, and determine a plurality of water level values ​​of the target river area within the target observation period according to each re-tracking point; The identification module is specifically configured to determine a sub-waveform search starting point based on a preset power threshold; search forward and backward based on the sub-waveform search starting point to determine at least one minimum point of the water waveform, and stop searching when the power of the water waveform is less than a minimum power threshold; determine multiple initial sub-waveforms based on each of the minimum points, wherein the minimum points are a leading edge starting point of an initial sub-waveform and a trailing edge ending point of other initial selected sub-waveforms adjacent to the initial sub-waveform; for each of the initial sub-waveforms, if the peak power of the initial sub-waveform and the power of the leading edge starting point of the sub-waveform meet a preset condition, determine the sub-waveform as a valid sub-waveform; the preset condition includes that a power difference between the peak power and the power of the leading edge starting point is not less than a preset power difference, and / or the preset condition includes that a power slope between the peak power and the power of the leading edge starting point is not less than a preset power slope threshold; The first determination module is specifically configured to determine, if a difference in peak power between two candidate sub-waveforms in the candidate sub-waveform group is less than a preset threshold, that the target sub-waveform is the first candidate sub-waveform; and if a difference in peak power between the two candidate sub-waveforms is not less than the preset threshold, that the target sub-waveform is the second candidate sub-waveform, wherein, in the candidate sub-waveform group, the first candidate sub-waveform is located before the second candidate sub-waveform.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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