CN114152302B - Lake water storage variation estimation method, system, electronic device and medium - Google Patents
Lake water storage variation estimation method, system, electronic device and medium Download PDFInfo
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Abstract
The disclosure relates to the technical field of monitoring of lake water storage variation, in particular to a method, a system, electronic equipment and a medium for estimating lake water storage variation. The method comprises the following steps: collecting and analyzing a multi-source remote sensing image to obtain the area of the lake, and collecting and analyzing multi-source satellite height measurement data to obtain the water level of the lake, wherein the multi-source remote sensing image and the multi-source satellite height measurement data are time-synchronous data; constructing a lake area-water level relation curve corresponding to the lake based on the lake area and the lake water level; according to the lake area-water level relation curve and the annual lake area, the water storage variation of the lake is estimated, wherein the annual lake area is obtained according to the global surface water data set, and the accuracy of estimating the water storage variation of the lake can be improved by adopting the method.
Description
Technical Field
The disclosure relates to the technical field of monitoring of lake water storage variation, in particular to a method, a system, electronic equipment and a medium for estimating lake water storage variation.
Background
At present, in a regional ecosystem, a lake is used as an important carrier for regional land water circulation and has an important effect on regional water balance, and because the water balance is the basis of research on hydrology of the lake, the dynamic change of a lake water area is concerned, the regional water balance is mastered in time, and a basis can be provided for sustainable utilization of regional water resources.
The dynamic monitoring of the lake water area mainly monitors whether the lake water area changes or not, in the prior art, aiming at the lake water storage variable quantity, a measuring ship is generally adopted to obtain underwater topographic data based on field observation, and then the lake water storage variable quantity is estimated, or based on remote sensing observation, the lake area and the lake water level are obtained by utilizing remote sensing satellite data and height measurement data, so that the lake water storage variable quantity is estimated according to the lake area and the lake water level.
However, with the prior art, the method based on field observation has the problem of consuming a large amount of manpower and material resources, and can hardly be realized in severe environments such as plateau, desert and the like, and is difficult to be popularized and applied in a large range; aiming at the method based on remote sensing observation, the satellite data is single, and the estimation accuracy of the lake water storage variation is reduced.
Disclosure of Invention
Based on this, it is necessary to provide a method, a system, an electronic device and a medium for estimating the amount of change in the stored water in the lake.
In a first aspect, an embodiment of the present disclosure provides a method for estimating a variation of stored water in a lake, where the method includes:
collecting and analyzing a multi-source remote sensing image to obtain the area of the lake, and collecting and analyzing multi-source satellite height measurement data to obtain the water level of the lake, wherein the multi-source remote sensing image and the multi-source satellite height measurement data are time-synchronous data;
constructing a lake area-water level relation curve corresponding to the lake based on the lake area and the lake water level;
and estimating the water storage variation of the lake according to the lake area-water level relation curve and the annual lake area, wherein the annual lake area is obtained according to a global surface water data set.
In one embodiment, the collecting and analyzing the multi-source remote sensing image to obtain the lake area comprises:
calculating normalized water body index images respectively corresponding to the multi-source remote sensing images according to the green wave band spectral features and the near-infrared wave band spectral features;
based on the normalized water body index image, performing water body segmentation by adopting a maximum inter-class variance method to obtain a lake water body vector diagram corresponding to the lake;
and calculating the area of the lake based on the lake water body vector diagram.
In one embodiment, the collecting and analyzing multi-source satellite height measurement data to obtain lake levels includes:
obtaining a plurality of first satellite elevation points based on a plurality of satellite elevation points in the multi-source satellite elevation data and the longitude and latitude information of the lake;
screening the plurality of first satellite elevation points based on a lake water body vector diagram to obtain a plurality of second satellite elevation points corresponding to the lake;
removing abnormal satellite elevation points from the second satellite elevation points to obtain a plurality of target satellite elevation points corresponding to the lake;
and calculating the lake water level based on a plurality of target satellite elevation points.
In one embodiment, the removing abnormal satellite elevation points from the plurality of second satellite elevation points to obtain a plurality of target satellite elevation points corresponding to the lake includes:
sequentially judging whether the elevation points of other second satellites meet preset conditions corresponding to the elevation points of the second satellites which are taken as the reference at present by taking each elevation point of the second satellites as the reference;
when determining that the other second satellite elevation points do not meet the preset condition, eliminating the other second satellite elevation points to obtain a plurality of third satellite elevation points;
determining a target second satellite elevation point based on a plurality of the second satellite elevation points;
obtaining a plurality of target satellite elevation points corresponding to the lake based on the target second satellite elevation points, wherein the plurality of target satellite elevation points are a plurality of third satellite elevation points corresponding to the target second satellite elevation points;
the calculating the lake water level based on the plurality of target satellite elevation points comprises:
and carrying out mean value calculation on the plurality of target satellite elevation points to obtain the lake water level.
In one embodiment, the estimating the variation of the stored water of the lake according to the lake area-water level relation curve and the annual lake area comprises:
calculating to obtain the annual lake water level according to the lake area-water level relation curve and the annual lake area;
and estimating the water storage variable quantity of the lake according to the annual area of the lake, the annual water level of the lake and a water storage variable quantity model.
In one embodiment, the water impoundment delta model is defined by the expression:
wherein the content of the first and second substances,
represents the lake secondtAnnual lake area;
represents the lake secondt(iv) lake annual area of +1 year;
represents the lake secondtAnnual lake annual water level;
represents the lake numbertThe lake year water level of +1 year.
In one embodiment, the multi-source remote sensing image at least comprises: landsat remote sensing images and Sentinel 2 remote sensing images;
the multi-source satellite altimetry data at least comprises: CryoSat 2 satellite elevation data, ICESat 2 satellite elevation data, and Sentinel 3 satellite elevation data.
In a second aspect, an embodiment of the present disclosure provides a system for estimating a lake water storage variation, including a data processing module and a display module;
the data processing module is configured to execute the estimation method of the lake water storage variation according to the first aspect;
and the display module is used for displaying the estimation process and result of the lake water storage variation.
In a third aspect, the disclosed embodiment provides an electronic device, which includes a memory and a processor, where the memory stores a computer program, and the processor implements the steps of the method for estimating the variation in stored water in a lake according to the first aspect when executing the computer program.
In a fourth aspect, the disclosed embodiments provide a computer-readable storage medium, on which a computer program is stored, and the computer program, when executed by a processor, implements the steps of the method for estimating the variation in impounded water in lakes.
According to the estimation method for the lake water storage variation, the accurate lake area and lake water level are obtained according to the multi-source remote sensing image and the multi-source satellite height measurement data by obtaining the multi-source remote sensing image and the multi-source satellite height measurement data, the lake area-water level relation curve is constructed based on the lake area and the lake water level, the lake water storage variation is further estimated, and compared with the method for estimating the lake water storage variation by using single data in the prior art, the estimation method for the lake water storage variation can improve the accuracy of estimation for the lake water storage variation.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure.
In order to more clearly illustrate the embodiments or technical solutions in the prior art of the present disclosure, the drawings used in the description of the embodiments or prior art will be briefly described below, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive exercise.
Fig. 1 is a schematic flow chart of a method for estimating variation of stored water in a lake according to an embodiment of the present disclosure;
FIG. 2 is a schematic flow chart of another method for estimating variation of stored water in a lake according to an embodiment of the present disclosure;
fig. 3 is a schematic flow chart of another method for estimating variation of stored water in a lake according to an embodiment of the present disclosure;
fig. 4 is a schematic flow chart of another method for estimating variation of stored water in a lake according to an embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of a system for estimating variation in stored water in lakes according to an embodiment of the present disclosure.
Detailed Description
In order that the above objects, features and advantages of the present disclosure may be more clearly understood, aspects of the present disclosure will be further described below. It should be noted that, in the case of no conflict, the embodiments and features in the embodiments of the present disclosure may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present disclosure, but the present disclosure may be practiced in other ways than those described herein; it is to be understood that the embodiments disclosed in the specification are only a few embodiments of the present disclosure, and not all embodiments.
At present, in a regional ecosystem, a lake is used as an important carrier for regional land water circulation and has an important effect on regional water balance, and because the water balance is the basis of research on hydrology of the lake, the dynamic change of a lake water area is concerned, the regional water balance is mastered in time, and a basis can be provided for sustainable utilization of regional water resources. The dynamic monitoring of the lake water area mainly monitors whether the lake water area changes or not, in the prior art, aiming at the lake water storage variable quantity, a measuring ship is generally adopted to obtain underwater topographic data based on field observation, and then the lake water storage variable quantity is estimated, or based on remote sensing observation, the lake area and the lake water level are obtained by utilizing remote sensing satellite data and height measurement data, so that the lake water storage variable quantity is estimated according to the lake area and the lake water level.
However, with the prior art, the method based on field observation has the problem of consuming a large amount of manpower and material resources, and can hardly be realized in severe environments such as plateau, desert and the like, and is difficult to be popularized and applied in a large range; aiming at the method based on remote sensing observation, the satellite data is single, and the estimation accuracy of the lake water storage variation is reduced.
Therefore, the method for estimating the water storage variation of the lake can improve the accuracy of estimating the water storage variation of the lake by acquiring the multi-source remote sensing image and the multi-source satellite height measurement data, obtaining more accurate lake area and lake water level according to the multi-source remote sensing image and the multi-source satellite height measurement data, constructing a lake area-water level relation curve based on the lake area and the lake water level, and further estimating the water storage variation of the lake.
In an embodiment, as shown in fig. 1, fig. 1 is a schematic flow chart of a method for estimating variation in stored water in a lake according to an embodiment of the present disclosure, which specifically includes the following steps:
s10: collecting and analyzing the multisource remote sensing image to obtain the lake area, and collecting and analyzing the multisource satellite height measurement data to obtain the lake water level.
The multi-source remote sensing image and the multi-source satellite height measurement data are time-synchronous data; the remote sensing image is based on a satellite remote sensing technology, monitoring of the earth surface layer is achieved, a large amount of earth surface change information can be rapidly obtained, the multi-source remote sensing image at least comprises a Landsat remote sensing image and a Sentinel 2 remote sensing image, the Landsat remote sensing image is long-time sequence multi-band remote sensing image data, the multi-band information source is high in resolution ratio, and the multi-band information source belongs to open source data. The Sentinel 2 remote sensing image is also high-resolution multiband remote sensing image data, is used for land monitoring, and can provide images of vegetation, soil and water coverage, inland waterways, coastal areas and the like.
The satellite height measurement data is data obtained by measuring the vertical distance from a satellite to an instant sea level (or a flat ground) by using a height measuring instrument carried by an artificial earth satellite, and the multisource satellite height measurement data at least comprises the following steps: the height measurement data of the CryoSat 2 satellite, the ICESat 2 satellite and the Sentinel 3 satellite are respectively the height measurement data of the lake obtained by measuring with the CryoSat 2 satellite, the ICESat 2 satellite and the Sentinel 3 satellite.
The time synchronization refers to that the time of the acquired multi-source remote sensing image is close to the time of acquiring multi-source satellite height measurement data, and does not need to belong to the same time, and as long as the data acquired in a proper time difference range belong to data with time synchronization, for example, for the multi-source remote sensing image, when data of 1 month and 15 days in 2000 are acquired, data belonging to 1 month and 08 days to 2000 month and 22 days in 2000 are acquired correspondingly, namely the data that the multi-source remote sensing image and the multi-source satellite height measurement data are time-synchronized are satisfied.
Specifically, when a multi-source remote sensing image is collected, the multi-source remote sensing image is analyzed and processed to obtain the lake area, and when multi-source satellite height measurement data is collected, the multi-source satellite height measurement data is analyzed and processed to obtain the lake water level.
It should be noted that the lake area and the lake level are corresponding areas and levels of the same lake, and a set of data pairs is formed based on the lake area and the lake level, but the disclosure is not limited thereto, and those skilled in the art may specifically set the data pairs according to actual situations.
On the basis of the above embodiments, in some embodiments of the present disclosure, further, as shown in fig. 2, collecting and analyzing a multi-source remote sensing image to obtain a lake area, one possible implementation manner is:
s101: and calculating normalized water body index images respectively corresponding to the multi-source remote sensing images according to the green wave band spectral characteristics and the near-infrared wave band spectral characteristics.
The green band spectral feature and the near-infrared band spectral feature are used for determining the difference values of the spectrums of the multi-band remote sensing image data in the green band and the near-infrared band so as to determine the position of the lake water body.
The normalized water body index is normalized difference processing based on a specific wave band of the remote sensing image, namely normalized difference processing based on the green wave band and the near infrared wave band, so that water body information in the image is highlighted, and thus a normalized water body index image in the multi-source remote sensing image is extracted, namely the lake water body is obtained.
Specifically, the multi-source remote sensing images are processed based on the green band spectral features and the near-infrared band spectral features, and normalized water body index images respectively corresponding to the multi-source remote sensing images are obtained through calculation by using a normalized water body index method, so that water body information corresponding to lakes is extracted.
S102: and based on the normalized water body index image, performing water body segmentation by adopting a maximum inter-class variance method to obtain a lake water body vector diagram corresponding to the lake.
The maximum inter-class variance method is a method for automatically solving a threshold value suitable for a double-peak condition, and is also called as an Otsu method, an image is divided into a foreground and a background according to the gray characteristic of the image, when the inter-class variance between the foreground and the background is larger, the difference between the foreground and the background is larger, and when part of the foreground is mistaken for the background or part of the background is mistaken for the foreground, the difference between the foreground and the background is reduced. Thus, a segmentation that maximizes the inter-class variance means that the probability of false positives is minimized. Here, the foreground refers to lake water, and the background refers to surrounding mountains, etc.
The lake water body vector diagram is obtained by adopting a maximum inter-class variance method to carry out water body segmentation, determining the position of the lake water body, converting the lake water body vector diagram into a vector diagram and storing the vector diagram, namely the lake water body vector diagram, and acquiring the geographical coordinate position of the lake water body according to the lake water body vector diagram.
S103: and calculating the area of the lake based on the lake water body vector diagram.
Specifically, after the lake water body vector diagram is obtained through calculation, the lake area is obtained through calculation according to the lake water body vector diagram.
Illustratively, according to the lake water body vector diagram, the lake water body vector diagram is reprojected by using a general mercar projection to determine the geographic coordinate position of the lake water body, and a GetArea function in a function library is called to calculate the area of the lake, but the disclosure is not limited thereto, and a person skilled in the art can calculate the area according to actual situations.
On the basis of the above embodiments, in some embodiments of the present disclosure, further, as shown in fig. 2, collecting and analyzing multi-source satellite height measurement data to obtain a lake level, one possible implementation manner is:
s104: and obtaining a plurality of first satellite elevation points based on a plurality of satellite elevation points in the multi-source satellite elevation measurement data and the longitude and latitude information of the lake.
The longitude and latitude information is determined according to the multi-source remote sensing image, and the first satellite elevation points are a plurality of first satellite elevation points which are respectively corresponding to all lakes in the global range and are obtained based on the longitude and latitude information of the lakes in the global range.
S105: and screening the plurality of first satellite elevation points based on the lake water body vector diagram to obtain a plurality of second satellite elevation points corresponding to the lake.
The second satellite elevation points refer to a plurality of corresponding second satellite elevation points for a specific lake.
Illustratively, the lake water body vector diagram is a vector diagram corresponding to the tuo pin lake, and according to the lake water body vector diagram of the tuo pin lake, a plurality of first satellite elevation points in all lakes in the global range are screened to obtain a plurality of second satellite elevation points falling on the surface of the tuo pin lake, but the disclosure is not limited thereto.
S106: and eliminating abnormal satellite elevation points from the second satellite elevation points to obtain a plurality of target satellite elevation points corresponding to the lake.
The abnormal satellite elevation point refers to an outlier in a plurality of second satellite elevation points, which is a deviation of elevation points falling on a lake surface due to factors such as atmosphere and terrain or due to instrument reasons when the satellite elevation points are acquired.
The target satellite elevation point refers to the satellite elevation point which accurately falls on the lake surface.
Therefore, accurate target satellite elevation points are obtained by obtaining a plurality of second satellite elevation points corresponding to the lakes and removing abnormal satellite elevation points from the plurality of second satellite elevation points.
On the basis of the foregoing embodiments, in some embodiments of the present disclosure, further, as shown in fig. 3, one possible implementation manner of S106 is:
s1061: and sequentially judging whether the elevation points of other second satellites meet the preset conditions corresponding to the current reference second satellite elevation point or not by taking each second satellite elevation point as a reference.
Wherein the predetermined condition is used to determine the determination condition of one or more abnormal satellite elevation points in each second satellite elevation point, for example, for a plurality of second satellite elevation points falling on the surface of the lake of Toxico lake, such as EPLS{P1、P2、P3...PiAre aimed atEach second satellite elevation point, when being P1When the point is taken as a reference, the corresponding preset condition is determined to be P1-0.3< Pi <P1+0.3, sequentially judging the elevation points such as P of other second satellites according to the preset condition2、P3...PiWhether the second satellite elevation point P is satisfied1The corresponding preset conditions are not limited thereto, and the disclosure is not particularly limited, and those skilled in the art can set the conditions according to actual situations.
S1062: and when determining that the elevation points of other second satellites do not meet the preset condition, eliminating the elevation points of other second satellites to obtain a plurality of third satellite elevation points.
Specifically, when it is determined that there is a second satellite elevation point that does not satisfy the preset condition among other second satellite elevation points except for the second satellite elevation point currently serving as the reference, the second satellite elevation point is considered to belong to an abnormal satellite elevation point, and the abnormal satellite elevation point is removed to obtain a plurality of third satellite elevation points.
It should be noted that, when each second satellite elevation point is taken as a reference, a plurality of corresponding third satellite elevation points are obtained for each second satellite elevation point.
S1063: a target second satellite elevation point is determined based on the plurality of second satellite elevation points.
S1064: and obtaining a plurality of target satellite elevation points corresponding to the lake based on the target second satellite elevation points.
And the plurality of target satellite elevation points are a plurality of third satellite elevation points corresponding to the target second satellite elevation points.
Specifically, a target second satellite elevation point is determined among the plurality of second satellite elevation points according to the plurality of second satellite elevation points corresponding to the lakes, and a plurality of target satellite elevation points are obtained according to a plurality of third satellite elevation points corresponding to the target second satellite elevation point.
For example, for a plurality of second satellite elevation points falling on the surface of the tuo-su lake, the number of a plurality of third satellite elevation points corresponding to each second satellite elevation point falling on the surface of the tuo-su lake is determined, the second satellite elevation point with the largest number is selected as the target second satellite elevation point, and the plurality of third satellite elevation points corresponding to the target second satellite elevation point are a plurality of target satellite elevation points.
S107: and calculating the lake water level based on the elevation points of the plurality of target satellites.
On the basis of the foregoing embodiments, in some embodiments of the present disclosure, further, as shown in fig. 3, one possible implementation manner of S107 is:
s1071: and carrying out mean value calculation on the elevation points of the plurality of target satellites to obtain the lake water level.
Specifically, the average value of a plurality of target satellite elevation points is calculated after a plurality of target satellite elevation points corresponding to the lake and the number of the target satellite elevation points are determined, so that the lake level is obtained.
Therefore, the lake level is obtained by acquiring the more accurate target satellite elevation points on the lake surface and performing the average value calculation based on the target satellite elevation points, so that the accuracy of acquiring the lake level is improved.
S12: and constructing a corresponding lake area-water level relation curve of the lake based on the lake area and the lake water level.
Specifically, fitting is carried out by using a common least square regression method according to the lake areas of the long-time sequence and the lake levels with time synchronization corresponding to the lake areas of the long-time sequence, so as to construct a lake area-water level relation curve.
It should be noted that the lake areas and the lake levels refer to long-time-series lake areas, and the long-time-series lake levels respectively corresponding to the long-time-series lake areas and having time-synchronized long-time-series lake levels, that is, a plurality of data pairs are formed according to the long-time-series lake areas and the corresponding long-time-series lake levels respectively having time-synchronized long-time-series lake levels, and the lake area-level relation curve is constructed by fitting the data pairs.
For example, when fitting is performed by using a common least square regression method to construct a lake area-water level relation curve, fitting is performed on currently commonly used 8 curve types, such as a linear curve, a quadratic polynomial curve, a cubic polynomial curve, a quartic polynomial curve, a quintic polynomial curve, an exponential curve, a logarithmic curve and a power curve, respectively, and a curve with the largest correlation coefficient and the smallest root mean square error in the 8 curve types and a monotonically increasing function curve is selected as a final lake area-water level relation curve.
S14: and estimating the variation of the stored water of the lake according to the lake area-water level relation curve and the annual area of the lake.
The lake annual area is obtained according to a global surface water data set, the global surface water data set comprises a position and time distribution diagram of surface water in the past continuous years, data of the range and change of the water area are provided, the data are also determined based on remote sensing images, and the data are mainly sorted in a mode of classifying each pixel into water or non-water, so that the water area of the whole time period is recorded.
For example, the whole time period may be one year, and the average value of the lake areas obtained at different times of the year is calculated, so that the result is the annual area of the lake.
Based on the foregoing embodiments, in some embodiments of the present disclosure, further, as shown in fig. 4, one possible implementation manner of S14 is as follows:
s141: and calculating the annual lake water level according to the lake area-water level relation curve and the annual lake area.
Specifically, after a lake area-water level relation curve is constructed according to the lake area and the corresponding lake water level with time synchronization, the lake annual area is determined in a global surface water data set, and the lake annual area is substituted into the lake area-water level relation curve, so that the lake annual water level corresponding to the lake annual area is obtained.
S142: and estimating the water storage variable quantity of the lake according to the annual area of the lake, the annual water level of the lake and the water storage variable quantity model.
The water storage variable quantity model belongs to a prismatic table model, the landform of the lake is simulated through the prismatic table model, and the lake area and the lake water level which correspond to each other for two continuous years are substituted into the water storage variable quantity model, so that the lake water storage variable quantity is obtained through calculation.
The water impoundment variation model is defined by the following expression:
Like this, this embodiment is through acquireing multisource remote sensing image and multisource satellite height finding data, obtains more accurate lake area and lake water level according to multisource remote sensing image and multisource satellite height finding data to construct lake area-water level relation curve based on lake area and lake water level, further estimate the retaining variation of lake, compare in prior art and use the retaining variation of single data estimation lake, can improve its accuracy of estimating the retaining variation of lake.
It should be understood that although the various steps in the flowcharts of fig. 1-4 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 1-4 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternating with other steps or at least some of the sub-steps or stages of other steps.
In one embodiment, as shown in fig. 4, there is provided a system for estimating the variation of stored water in a lake, comprising: a data processing module 10 and a display module 12.
Wherein, the data processing module 10 is configured to execute the estimation method of the lake water storage variation in the above embodiment;
the display module 12 is used for displaying the estimation process and result of the lake water storage variation.
In an embodiment of the present invention, the data processing module 10 includes a lake area calculating unit, configured to calculate normalized water index images corresponding to the multi-source remote sensing images respectively according to the green band spectral features and the near-infrared band spectral features; based on the normalized water body index image, performing water body segmentation by adopting a maximum inter-class variance method to obtain a lake water body vector diagram corresponding to the lake; and calculating the area of the lake based on the lake water body vector diagram.
In an implementation manner of an embodiment of the present invention, the data processing module 10 includes a lake level calculation unit, configured to obtain a plurality of first satellite elevation points based on a plurality of satellite elevation points in multi-source satellite elevation measurement data and longitude and latitude information of a lake; screening a plurality of first satellite elevation points based on the lake water body vector diagram to obtain a plurality of second satellite elevation points corresponding to the lake; removing abnormal satellite elevation points from the second satellite elevation points to obtain a plurality of target satellite elevation points corresponding to the lake; and calculating the lake water level based on the elevation points of the plurality of target satellites.
In an implementation manner of the embodiment of the present invention, the lake level calculation unit is specifically configured to sequentially determine, with each second satellite elevation point as a reference, whether other second satellite elevation points meet a preset condition corresponding to a second satellite elevation point currently serving as a reference; when determining that the elevation points of other second satellites do not meet the preset condition, eliminating the elevation points of other second satellites to obtain a plurality of third satellite elevation points; determining a target second satellite elevation point based on the plurality of second satellite elevation points; obtaining a plurality of target satellite elevation points corresponding to the lake based on the target second satellite elevation points, wherein the plurality of target satellite elevation points are a plurality of third satellite elevation points corresponding to the target second satellite elevation points; and carrying out mean value calculation on the elevation points of the plurality of target satellites to obtain the lake water level.
In an embodiment of the present invention, the data processing module 10 further includes a stored water variation estimation unit, configured to calculate an annual lake water level according to a lake area-water level relation curve and an annual lake area; and estimating the water storage variable quantity of the lake according to the annual area of the lake, the annual water level of the lake and the water storage variable quantity model.
In an embodiment of the present invention, the water storage variation amount model is defined by the following expression:
wherein, the first and the second end of the pipe are connected with each other,
represents the lake secondtAnnual lake area;
represents the lake secondt(iv) lake annual area of +1 year;
represents the lake secondtAnnual lake annual water level;
represents the lake secondtThe lake year water level of +1 year.
In an embodiment of the present invention, the multi-source remote sensing image at least includes: landsat remote sensing images and Sentinel 2 remote sensing images; the multi-source satellite height measurement data at least comprises: CryoSat 2 satellite elevation data, ICESat 2 satellite elevation data, and Sentinel 3 satellite elevation data.
In an embodiment of the present invention, the display module is specifically configured to display processing procedures and processing results of the lake area calculation unit, the lake water level calculation unit, and the water storage variation estimation unit.
In the embodiment, by constructing the lake water storage variation estimation system, the multi-source remote sensing image and the multi-source satellite height measurement data are automatically acquired, the more accurate lake area and lake level are obtained according to the multi-source remote sensing image and the multi-source satellite height measurement data, and the lake area-level relation curve is constructed based on the lake area and the lake level, so that the lake water storage variation is further estimated.
An embodiment of the present disclosure provides an electronic device, including: the storage, the processor, and the computer program stored in the storage and capable of running on the processor, where the processor executes the computer program to implement the method for estimating the lake water storage variation provided in the embodiment of the present disclosure, for example, the processor executes the computer program to implement the technical solution of any one of the method embodiments shown in fig. 1 to fig. 4, and the implementation principle and the technical effect are similar, and are not described herein again.
The present disclosure also provides a computer-readable storage medium, on which a computer program is stored, where the computer program can be executed by a processor to implement the method for estimating the variation in the stored water in a lake according to the embodiment of the present disclosure, for example, when the computer program is executed by the processor, the technical solution of the method embodiment shown in any one of fig. 1 to fig. 4 is implemented, and the implementation principle and the technical effect are similar, and are not described herein again.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, databases, or other media used in the embodiments provided by the present disclosure may include at least one of non-volatile and volatile memory. Non-volatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical storage, or the like. Volatile Memory can include Random Access Memory (RAM) or external cache Memory. By way of illustration and not limitation, RAM is available in many forms, such as Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), and the like.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present disclosure, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for those skilled in the art, various changes and modifications can be made without departing from the concept of the present disclosure, and these changes and modifications are all within the scope of the present disclosure. Therefore, the protection scope of the present disclosure should be subject to the appended claims.
Claims (9)
1. A lake impounded water variation estimation method is characterized by comprising the following steps:
collecting and analyzing a multi-source remote sensing image to obtain a lake area, and collecting and analyzing multi-source satellite height measurement data to obtain a lake water level, wherein the multi-source remote sensing image and the multi-source satellite height measurement data are time-synchronous data, and the multi-source satellite height measurement data at least comprise: the system comprises a CryoSat 2 satellite height measurement data, an ICESat 2 satellite height measurement data and a Sentinel 3 satellite height measurement data, wherein the CryoSat 2 satellite height measurement data, the ICESat 2 satellite height measurement data and the Sentinel 3 satellite height measurement data are respectively height measurement data of lakes obtained by measuring with a CryoSat 2 satellite, an ICESat 2 satellite and a Sentinel 3 satellite;
constructing a lake area-water level relation curve corresponding to the lake based on the lake area and the lake water level;
estimating the water storage variation of the lake according to the lake area-water level relation curve and the annual lake area, wherein the annual lake area is obtained according to a global surface water data set;
collecting and analyzing multi-source satellite height measurement data to obtain lake water level, including:
obtaining a plurality of first satellite elevation points based on a plurality of satellite elevation points in the multi-source satellite elevation data and the longitude and latitude information of the lake;
screening the plurality of first satellite elevation points based on a lake water body vector diagram to obtain a plurality of second satellite elevation points corresponding to the lake;
sequentially judging whether other second satellite elevation points meet preset conditions corresponding to the second satellite elevation points which are currently taken as the reference or not by taking each second satellite elevation point as the reference, wherein the preset conditions are used for determining judgment conditions of one or more abnormal satellite elevation points in each second satellite elevation point;
when determining that the other second satellite elevation points do not meet the preset condition, eliminating the other second satellite elevation points to obtain a plurality of third satellite elevation points;
determining a target second satellite elevation point based on a plurality of the second satellite elevation points;
obtaining a plurality of target satellite elevation points corresponding to the lake based on the target second satellite elevation points, wherein the plurality of target satellite elevation points are a plurality of third satellite elevation points corresponding to the target second satellite elevation points;
and calculating the lake water level based on a plurality of target satellite elevation points.
2. The method of claim 1, wherein collecting and analyzing the multi-source remote sensing image to obtain a lake area comprises:
calculating normalized water body index images respectively corresponding to the multi-source remote sensing images according to the green wave band spectral characteristics and the near-infrared wave band spectral characteristics;
based on the normalized water body index image, performing water body segmentation by adopting a maximum inter-class variance method to obtain a lake water body vector diagram corresponding to the lake;
and calculating the area of the lake based on the lake water body vector diagram.
3. The method of claim 1, wherein said calculating said lake level based on a plurality of said target satellite elevation points comprises:
and carrying out mean value calculation on the plurality of target satellite elevation points to obtain the lake water level.
4. The method according to claim 1, wherein the estimating of the variation of the stored water of the lake according to the lake area-water level relation curve and the annual lake area comprises:
calculating to obtain the annual lake water level according to the lake area-water level relation curve and the annual lake area;
and estimating the water storage variable quantity of the lake according to the annual area of the lake, the annual water level of the lake and a water storage variable quantity model.
5. The method of claim 4, wherein the impounded water delta model is defined by the expression:
wherein, the first and the second end of the pipe are connected with each other,
representing the annual area of the lake in the tth year;
representing the annual area of the lake in the t +1 th year;
representing the lake year water level of the t year of the lake;
representing the lake year water level of the t +1 year of the lake.
6. The method of claim 1, wherein the multi-source remote sensing image comprises at least: landsat remote sensing images and Sentinil 2 remote sensing images.
7. A lake water storage variation estimation system is characterized by comprising a data processing module and a display module;
the data processing module is used for executing the estimation method of the variation of the stored water in the lake of claim 1;
and the display module is used for displaying the estimation process and result of the lake water storage variation.
8. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method for estimating the variation of stored water in a lake according to any one of claims 1 to 6 when executing the computer program.
9. A computer-readable storage medium, on which a computer program is stored, wherein the computer program, when being executed by a processor, implements the steps of the method for estimating the variation in impounded water in lakes according to any one of claims 1 to 6.
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