Remote sensing estimation method and device for lake surface lake entering flow

Abstract

The invention discloses a remote sensing estimation method and device for lake surface lake-entering flow, and relates to the field of lake surface lake-entering flow estimation.The method comprises the steps that optical remote sensing images, synthetic aperture radar images and satellite height measurement data of a target lake area in different periods are obtained; determining lake water body areas in different periods according to the optical remote sensing image and the synthetic aperture radar image; determining lake water level variation of the target lake area in any two periods according to satellite height measurement data; according to the lake water level variable quantity of any two periods and the corresponding lake water body area, determining the lake water quantity variable quantity of any two periods; and according to the lake water volume variation, estimating the lake earth surface into-lake flow in any two periods. According to the method, the accuracy and timeliness of lake surface lake inflow estimation can be improved.

Description

Technical Field

[0001] The present application relates to the field of estimating the surface inflow of lakes, and particularly to a method and device for remotely sensing and estimating the surface inflow of lakes. Background Art

[0002] As an important part of the hydrological cycle, lakes sensitively record climate change information and are important carriers for revealing the response of surface water resources to climate change. Monitoring and researching lakes are crucial for understanding regional hydrological processes and water resource changes. Although remote sensing technology has made certain progress in lake monitoring, existing research mainly focuses on monitoring lake area, water level, and water volume. As a key parameter in the lake water balance, the surface inflow into lakes currently lacks research on inversion based on remote sensing technology, which limits the comprehensive understanding of lake hydrological processes. Summary of the Invention

[0003] The purpose of the present application is to provide a method and device for remotely sensing and estimating the surface inflow of lakes, which can improve the accuracy and timeliness of estimating the surface inflow of lakes.

[0004] To achieve the above purpose, the present application provides the following solutions: In the first aspect, the present application provides a method for remotely sensing and estimating the surface inflow of lakes, including: Obtaining optical remote sensing images, synthetic aperture radar images, and satellite altimetry data of a target lake area at different times; Determining the lake water area at different times according to the optical remote sensing images and synthetic aperture radar images; Determining the change in lake water level between any two times in the target lake area according to the satellite altimetry data; Determining the change in lake water volume between any two times according to the change in lake water level between any two times and the corresponding lake water area; Estimating the surface inflow of lakes between any two times according to the change in lake water volume.

[0005] In the second aspect, the present application provides a device for remotely sensing and estimating the surface inflow of lakes, including: A data acquisition module for obtaining optical remote sensing images, synthetic aperture radar images, and satellite altimetry data of a target lake area at different times; An area determination module for determining the lake water area at different times according to the optical remote sensing images and synthetic aperture radar images; A water level change calculation module for determining the change in lake water level between any two times in the target lake area according to the satellite altimetry data; A water volume change calculation module for determining the change in lake water volume between any two times according to the change in lake water level between any two times and the corresponding lake water area; A surface inflow estimation module for estimating the surface inflow of a lake between any two periods according to the change in lake water volume.

[0006] In a third aspect, the present application provides a computer device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the computer program to implement the above-mentioned remote sensing estimation method for the surface inflow of a lake.

[0007] In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the above-mentioned remote sensing estimation method for the surface inflow of a lake is implemented.

[0008] According to the specific embodiments provided by the present application, the following technical effects are disclosed: The present application provides a remote sensing estimation method and device for the surface inflow of a lake, which obtains optical remote sensing images, synthetic aperture radar images, and satellite altimetry data of a target lake area at different times; determines the lake water area at different times according to the optical remote sensing images and synthetic aperture radar images; determines the change in lake water level between any two periods in the target lake area according to the satellite altimetry data; determines the change in lake water volume between any two periods according to the change in lake water level between any two periods and the corresponding lake water area; estimates the surface inflow of the lake between any two periods according to the change in lake water volume. By integrating multi-source remote sensing data, the present application aims to obtain high-precision lake area and water level, improve the accuracy and timeliness of the estimation of the surface inflow of the lake. At the same time, a dynamic connection framework between the change in lake water volume and the surface inflow is established, filling the technical gap in remotely inferring the surface inflow based on remote sensing. The present application not only provides new ideas and tools for the study of lake hydrological processes, but also provides scientific support for water resource management. Through the accurate monitoring of the dynamic changes of lakes, the impact of climate change on regional water resources can be better understood, so as to provide data support for decision-making and promote sustainable water resource management. Description of the Drawings

[0009] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application, and those of ordinary skill in the art can obtain other drawings without creative efforts based on these drawings.

[0010] Figure 1 It is an application environment diagram of a remote sensing estimation method for the surface inflow of a lake in an embodiment of the present application; Figure 2Schematic flowchart of a method for remotely sensing and estimating the surface inflow of a lake provided by an embodiment of the present application; Figure 3 Schematic diagram of functional modules of a device for remotely sensing and estimating the surface inflow of a lake provided by an embodiment of the present application; Figure 4 Schematic diagram of the structure of a computer device provided by an embodiment of the present application. Detailed implementation manners

[0011] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0012] To make the above objects, features, and advantages of the present application more obvious and understandable, the present application will be further described in detail below in conjunction with the drawings and specific implementation manners.

[0013] The method for remotely sensing and estimating the surface inflow of a lake provided by the embodiments of the present application can be applied to an application environment as Figure 1 shown. Among them, the terminal communicates with the server through the network. The data storage system can store the data that the server needs to process. The data storage system can be set separately, integrated on the server, placed in the cloud or on other servers. The terminal can send optical remote sensing images, synthetic aperture radar images, and satellite altimetry data of different periods in the target lake area to the server. After receiving the optical remote sensing images, synthetic aperture radar images, and satellite altimetry data of different periods in the target lake area, the server determines the lake water area of different periods according to the optical remote sensing images and synthetic aperture radar images; determines the lake water level change amount between any two periods in the target lake area according to the satellite altimetry data; determines the lake water volume change amount between any two periods according to the lake water level change amount between any two periods and the corresponding lake water area; estimates the surface inflow of the lake between any two periods according to the lake water volume change amount. The server can feedback the surface inflow of the lake between any two periods obtained to the terminal. In addition, in some embodiments, the method for remotely sensing and estimating the surface inflow of a lake can also be implemented by the server or the terminal alone. For example, the terminal can directly perform the method for remotely sensing and estimating the surface inflow of a lake on the optical remote sensing images, synthetic aperture radar images, and satellite altimetry data of different periods in the target lake area, or the server can obtain the video to be processed from the data storage system and perform the method for remotely sensing and estimating the surface inflow of a lake on the optical remote sensing images, synthetic aperture radar images, and satellite altimetry data of different periods in the target lake area.

[0014] Among them, the terminal can be, but is not limited to, various desktop computers, laptop computers, smartphones, tablet computers, Internet of Things devices, and portable wearable devices. The Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, etc. The portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc. The server can be implemented by an independent server or a server cluster composed of multiple servers, and can also be a cloud server.

[0015] In an exemplary embodiment, as Figure 2 shown, a method for remotely estimating the surface inflow of a lake is provided. This method is executed by a computer device, specifically, it can be executed alone by a computer device such as a terminal or a server, or jointly executed by a terminal and a server. In the embodiments of the present application, taking this method applied to Figure 1 the server in

[0016] Step 101, obtain optical remote sensing images, synthetic aperture radar images, and satellite altimetry data of the target lake area at different times.

[0017] Step 102, determine the lake water area at different times according to the optical remote sensing images and synthetic aperture radar images.

[0018] Step 103, determine the lake water level change amount between any two times in the target lake area according to the satellite altimetry data.

[0019] Step 104, determine the lake water volume change amount between any two times according to the lake water level change amount and the corresponding lake water area between any two times.

[0020] Step 105, estimate the surface inflow of the lake between any two times according to the lake water volume change amount.

[0021] By implementing the above steps 101 to 105, the present application aims to obtain high-precision lake area and water level by integrating multi-source remote sensing data, and comprehensively utilize different types of remote sensing data, providing a more reliable basis for lake monitoring, and improving the accuracy and timeliness of estimating the surface inflow of the lake. At the same time, a dynamic connection framework between the lake water volume change amount and the surface inflow is established, filling the technical gap in remotely inferring the surface inflow based on remote sensing. The present application not only provides new ideas and tools for lake hydrological process research, but also provides scientific support for water resource management. Through the precise monitoring of lake dynamic changes, the impact of climate change on regional water resources can be better understood, thereby providing data support for decision-making and promoting sustainable water resource management.

[0022] In another exemplary embodiment of the present application, in step 102, determining the lake water area in different periods based on the optical remote sensing image and the synthetic aperture radar image specifically includes: (1) Preprocess the optical remote sensing images and synthetic aperture radar images in different periods respectively to obtain the preprocessed optical remote sensing images and preprocessed synthetic aperture radar images.

[0023] Perform radiometric correction and atmospheric correction on the original optical remote sensing image to eliminate the influence of environmental factors on the image quality, and perform image mosaicking to ensure that all images cover the entire lake area. Denoise the synthetic aperture radar image to improve the data quality. After the two types of images are preprocessed, they can be used for the extraction of the lake water area respectively.

[0024] (2) Calculate the normalized difference water index based on the preprocessed optical remote sensing image, and apply the fixed threshold method or the adaptive threshold method to extract the lake water area in the optical remote sensing image according to the normalized difference water index.

[0025] (3) Based on the backscattering characteristics of the radar image, use the fixed threshold method or the adaptive threshold method to extract the lake water area in the radar image.

[0026] (4) Determine the lake water area in different periods based on the lake water area in the optical remote sensing image and the lake water area in the radar image.

[0027] Collect multi-source remote sensing data, including optical remote sensing images and synthetic aperture radar images in different periods, to ensure comprehensive coverage of the lake area. The radar image is insensitive to cloud occlusion and can observe the lake water under adverse weather conditions. The optical image has a strong ability to distinguish the spectral characteristics of the water body boundary and can capture accurate information on the lake boundary under good weather conditions. Therefore, combining the two types of data can make up for the concreteness of a single data type and more comprehensively and accurately reflect the lake water area and its spatio-temporal variation characteristics.

[0028] In another exemplary embodiment of the present application, if the required lake water area and lake water level information can be obtained during the research period, the water level change amount can be directly obtained based on the lake water level information. That is, in step 103, determining the lake water level change amount between any two periods in the target lake area based on satellite altimetry data specifically includes: (1) Obtain satellite altimetry data in different periods of the target lake area.

[0029] (2) Determine the lake water level values in different periods based on the satellite altimetry data.

[0030] (3) Determine the lake water level change amount between any two periods in the target lake area based on the lake water level values in different periods.

[0031] For some periods when there is only lake water area data but no water level data, it is necessary to calculate the water level change value. As another alternative implementation, in step 103, determining the lake water level change amount between any two periods in the target lake area according to satellite altimetry data specifically includes: (1) Determine the lake water area change amount (ΔS) according to the lake water areas in different periods of the target lake area.

[0032] (2) Obtain the satellite altimetry data in different periods of the target lake area.

[0033] (3) Determine the lake water level values in different periods according to the satellite altimetry data.

[0034] Obtain the satellite altimetry data and extract the in-transit water level altimetry data passing through the lake area. According to the time information of the satellite altimetry data, group the data according to different in-transit periods of the satellite (i.e., a complete measurement process when the satellite passes through the lake area); the data group of each in-transit period consists of a set of measurement points, where each measurement point contains a water level observation value and satellite observation parameters.

[0035] For each data group of each in-transit period, perform error correction group by group to improve the data quality. The error correction mainly includes orbit error correction, terrain error correction, and systematic error correction. After the preprocessing is completed, each set of measurement point data has high-precision water level observation values.

[0036] Calculate the lake water level value group by group according to the in-transit period, that is, calculate the average value of the water level values of the measurement points in each group of data as the representative lake water level value of this in-transit period.

[0037] Organize the lake water level values calculated in all in-transit periods into time series data, and the time change trend of the lake water level can be obtained.

[0038] (4) Determine the lake water level change amount (ΔH) according to the lake water level values in different periods.

[0039] (5) Fit the relationship function between the lake water area change amount and the lake water level change amount.

[0040] (6) Determine the lake water level change amount between any two periods according to the relationship function between the lake area change amount and the water level change amount.

[0041] In this application, based on the lake water area and the lake water level value, a relationship function between the lake area change amount (ΔS) and the water level change amount (ΔH) is established. For the lake area and water level data at the same time, based on the initial time, the area change amount (ΔS) and the water level change amount (ΔH) of these periods are extracted. The lake area change amount (ΔS, as the dependent variable) and the water level change amount (ΔH, as the independent variable) are subjected to fitting analysis to establish a relationship model between the two. For some periods where there is only lake water area data but no lake water level data, the lake water level change value (ΔH) can be calculated through the established relationship model, and then the incomplete lake water level time series can be supplemented.

[0042] In another exemplary embodiment of this application, in step 104, it is assumed that the lake water volume change follows an irregular frustum model, and the calculation formula for the lake water volume change amount between any two periods is:

[0043] In the formula, represents the lake water volume change amount between any two periods; and respectively represent the lake water areas of any two periods, and S a is the upper surface area of the frustum (the lake water area corresponding to the higher lake water level value among any two periods), and S b is the lower surface area of the frustum (the lake water area corresponding to the lower lake water level value among any two periods); represents the lake water level change amount between any two periods.

[0044] In another exemplary embodiment of this application, in step 105, for a lake with an outflow, the water balance formula is: ΔV = P - E + R in -R out Among them, is the change in the lake water storage volume, that is, the lake water volume change amount between any two periods; P is the lake precipitation, which can be calculated through meteorological data and is a known quantity; R in is the surface water inflow into the lake, which is an unknown quantity; E is the lake evaporation, which can be calculated through meteorological data and is a known quantity; R out is the lake outflow, which comes from surface monitoring or relevant model estimation and is a known quantity.

[0045] For a closed endorheic lake, assuming that the groundwater recharge and leakage of the target lake roughly cancel each other out over a long period of time, the lake water balance formula is simplified to: ΔV = P - E + R in Estimate the surface inflow R of the lake according to the relationship between the known and unknown quantities described above in 。

[0046] For lakes with an outflow, the calculation formula for the surface inflow of the lake is: R in = ΔV - P + E + R out For closed endorheic lakes, the calculation formula for the surface inflow of the lake is: R in = ΔV - P + E By combining the lake water volume change with the water balance formula, dynamically estimate the surface inflow, filling the technical gap in the estimation of inflow by remote sensing technology.

[0047] In this application, a technical system covering the whole process of lake monitoring is established, covering the whole process from lake area extraction, water level monitoring, water volume change estimation to surface inflow estimation. In particular, an estimation method for surface inflow is proposed for the first time, dynamically monitoring the lake water volume change, combining the lake water volume change with the water balance formula, establishing a dynamic connection framework between the lake water volume change and the surface inflow, dynamically estimating the surface inflow, improving the accuracy and timeliness of the estimation of lake inflow, enhancing the scientificity and accuracy of lake inflow monitoring, and providing a scientific basis for water resource management. In addition, the estimation method of this application does not require a large amount of ground measured data, is applicable to dynamic monitoring of lake water volume and surface inflow in large ranges and multiple time periods, and has higher flexibility and operability in practical applications, especially in areas where data acquisition is difficult.

[0048] This application also provides an application scenario that applies the above-mentioned remote sensing estimation method for surface inflow of lakes. Specifically: The remote sensing estimation method for surface inflow of lakes provided in this embodiment can be applied in the scenario of monitoring surface inflow of lakes. This scenario includes a data collection link and a link for estimating the surface inflow of lakes; the data collection link is used to obtain optical remote sensing images, synthetic aperture radar images and satellite altimetry data of the target lake area at different times; the link for estimating the surface inflow of lakes is used to estimate the surface inflow of the target lake according to the optical remote sensing images, synthetic aperture radar images and satellite altimetry data. The remote sensing estimation method for surface inflow of lakes provided in this embodiment belongs to the link for estimating the surface inflow of lakes.

[0049] Based on the same inventive concept, an embodiment of the present application also provides an apparatus for remotely sensing and estimating the surface inflow of a lake for implementing the above-mentioned remotely sensing and estimating method for the surface inflow of a lake. The solution provided by this apparatus for solving problems is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the apparatus for remotely sensing and estimating the surface inflow of a lake provided below can refer to the limitations on the remotely sensing and estimating method for the surface inflow of a lake in the above text, and will not be elaborated here.

[0050] In an exemplary embodiment, as Figure 3 shown, an apparatus for remotely sensing and estimating the surface inflow of a lake is provided, including: A data acquisition module M1, configured to acquire optical remote sensing images, synthetic aperture radar images, and satellite altimetry data of a target lake area at different times.

[0051] An area determination module M2, configured to determine the lake water area at different times according to the optical remote sensing images and synthetic aperture radar images.

[0052] A water level change calculation module M3, configured to determine the lake water level change between any two times in the target lake area according to the satellite altimetry data.

[0053] A water volume change calculation module M4, configured to determine the lake water volume change between any two times according to the lake water level change between any two times and the corresponding lake water area.

[0054] A surface inflow estimation module M5, configured to estimate the surface inflow of the lake between any two times according to the lake water volume change.

[0055] In an exemplary embodiment, a computer device is provided. This computer device can be a server or a terminal, and its internal structure diagram can be as Figure 4As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, 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 the computer program in the non-volatile storage medium. The database of the computer device is used to store the estimated lake surface inflow data. The input / output interface of the computer device is used to exchange information between the processor and external devices. 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, it implements a method for remotely estimating the lake surface inflow.

[0056] Those skilled in the art can understand that Figure 4 the structure shown in is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements. In an exemplary embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, the steps in the above method embodiments are implemented.

[0057] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by the processor, the steps in the above method embodiments are implemented.

[0058] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with relevant regulations.

[0059] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing 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 methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memories. Non-volatile memories can include read-only memory (ROM), magnetic tapes, floppy disks, flash memories, optical memories, high-density embedded non-volatile memories, resistive random access memories (ReRAM), magnetoresistive random access memories (MRAM), ferroelectric random access memories (FRAM), phase change memories (PCM), graphene memories, etc. Volatile memories can include random access memory (RAM) or external cache memories, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0060] The databases involved in the embodiments provided in this application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in this application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logics, data processing logics based on quantum computing, etc., without limitation.

[0061] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, 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, it should be considered as the scope described in this specification.

[0062] Specific examples are used in this article to elaborate on the principles and implementation manners of this application. The descriptions of the above embodiments are only used to help understand the method and its core idea of this application; at the same time, for those of ordinary skill in the art, according to the idea of this application, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation to this application.

Claims

1. A remote sensing estimation method for the surface inflow of a lake, characterized in that, Including: Obtain optical remote sensing images, synthetic aperture radar images and satellite altimetry data of the target lake area in different periods; Determine the lake water area in different periods according to the optical remote sensing images and synthetic aperture radar images; Determine the lake water level change amount between any two periods in the target lake area according to the satellite altimetry data; Determine the lake water volume change amount between any two periods according to the lake water level change amount between any two periods and the corresponding lake water area; Estimate the surface inflow of the lake between any two periods according to the lake water volume change amount.

2. The remote sensing estimation method for the inflow of lake surface into the lake according to claim 1, wherein Determine the lake water area in different periods according to the optical remote sensing images and synthetic aperture radar images, specifically including: Preprocess the optical remote sensing images and synthetic aperture radar images in different periods respectively to obtain the preprocessed optical remote sensing images and preprocessed synthetic aperture radar images; Calculate the normalized difference water index according to the preprocessed optical remote sensing images; Extract the lake water area in the optical remote sensing images by using the fixed threshold method or the adaptive threshold method according to the normalized difference water index; Extract the lake water area in the radar images by using the fixed threshold method or the adaptive threshold method based on the backscattering characteristics of the radar images; Determine the lake water area in different periods according to the lake water area in the optical remote sensing images and the lake water area in the radar images.

3. The remote sensing estimation method for the inflow of lake surface from the lake surface according to claim 1, characterized in that Determine the lake water level change amount between any two periods in the target lake area according to the satellite altimetry data, specifically including: Obtain the satellite altimetry data of the target lake area in different periods; Determine the lake water level values in different periods according to the satellite altimetry data; Determine the lake water level change amount between any two periods in the target lake area according to the lake water level values in different periods.

4. The remote sensing estimation method for the inflow of lake surface water according to claim 1, characterized in that Determine the lake water level change amount between any two periods in the target lake area according to the satellite altimetry data, specifically including: Determine the lake water area change amount according to the lake water area in different periods in the target lake area; Obtain the satellite altimetry data of the target lake area in different periods; Determine the lake water level values in different periods according to the satellite altimetry data; Determine the lake water level change amount according to the lake water level values in different periods; Fit the relationship function between the lake water area change amount and the lake water level change amount; Determine the lake water level change amount between any two periods according to the relationship function between the lake area change amount and the water level change amount.

5. The remote sensing estimation method for the inflow of lake surface into the lake according to claim 3 or 4, characterized in that The calculation formula for the lake water volume change amount between any two periods is: In the formula, represents the change in lake water volume between any two periods; and respectively represent the water body areas of the lake in any two periods; represents the change in lake water level between any two periods.

6. The remote sensing estimation method for the inflow of lake surface from the lake surface according to claim 1, characterized in that For lakes with an outflow, the calculation formula for the surface inflow of the lake is: R in =ΔV - P + E + R out Wherein, R in represents the inflow of surface water into the lake; represents the change in lake water volume between any two periods; P represents the precipitation of the lake; E represents the evaporation of the lake; R out represents the outflow of the lake.

7. The remote sensing estimation method for the inflow of lake surface from the lake surface according to claim 1, characterized in that For closed endorheic lakes, the calculation formula for the surface inflow of the lake is: R in =ΔV - P + E wherein, R in represents the inflow of surface water into the lake; represents the change in lake water volume between any two periods; P represents the precipitation of the lake; E represents the evaporation of the lake.

8. A remote sensing estimation device for the inflow of lake surface into the lake, characterized in that, Including: A data acquisition module for obtaining optical remote sensing images, synthetic aperture radar images and satellite altimetry data of the target lake area in different periods; An area determination module for determining the lake water area in different periods according to the optical remote sensing images and synthetic aperture radar images; A water level change amount calculation module for determining the lake water level change amount between any two periods in the target lake area according to the satellite altimetry data; A water volume change amount calculation module for determining the lake water volume change amount between any two periods according to the lake water level change amount between any two periods and the corresponding lake water area; The surface water inflow estimation module is used to estimate the surface water inflow into the lake between any two periods according to the change in the lake water volume.

9. A computer device, comprising: A memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the computer program to implement the remote sensing estimation method for the surface water inflow into the lake according to any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the remote sensing estimation method for the surface water inflow into the lake according to any one of claims 1-7.

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