Earth surface water storage inversion method and system based on satellite remote sensing

Abstract

The invention discloses an earth surface water storage inversion method and system based on satellite remote sensing. The method comprises the steps that a remote sensing image of an earth surface is obtained through satellite remote sensing; analyzing the remote sensing image to obtain topographic data and earth surface unshielded water storage information; on the basis of the topographic data and the earth surface unshielded water storage information, earth surface shielded water storage information is obtained through prediction; and calculating the earth surface water storage amount based on the earth surface unshielded water storage information and the earth surface shielded water storage information. The problem that the accuracy of the inverted surface water storage amount is low due to the fact that the surface water storage amount is obtained through optical remote sensing in a complex terrain shielding surface water storage method is solved.

Description

Background Art

[0002] The surface water storage situation is of great significance for water resources management. It is the basis for evaluating the total amount of water resources, can reflect the abundance or scarcity of water resources, and is also the key basis for allocating water resources and planning water conservancy projects, realizing the rational utilization and sustainable development of water resources. In the prior art, multi-spectral and hyperspectral data are obtained by optical remote sensing, and by calculating vegetation indices and water indices, the relationship with surface water storage is established to invert the surface water storage situation, which can accurately evaluate the water resource reserves and distribution. However, due to the complex terrain of the surface, the surface water storage blocked by abnormal landforms cannot be obtained by optical remote sensing, resulting in a low accuracy of the inverted surface water storage volume. Summary of the Invention

[0003] In order to overcome the problem that the surface water storage method blocked by complex terrain cannot be obtained by optical remote sensing, resulting in a low accuracy of the inverted surface water storage volume, this application provides a surface water storage inversion method and system based on satellite remote sensing.

[0004] In the first aspect, to solve the above technical problems, this application provides a surface water storage inversion method based on satellite remote sensing, including:

[0005] Obtaining a remote sensing image of the surface using satellite remote sensing;

[0006] Analyzing the remote sensing image to obtain terrain data and surface unobstructed water storage information;

[0007] Predicting the surface obstructed water storage information based on the terrain data and the surface unobstructed water storage information;

[0008] Calculating the surface water storage volume based on the surface unobstructed water storage information and the surface obstructed water storage information.

[0009] In the second aspect, this application also provides a surface water storage inversion system based on satellite remote sensing, including:

[0010] A remote sensing module for obtaining a remote sensing image of the surface using satellite remote sensing;

[0011] An analysis module for analyzing the remote sensing image to obtain terrain data and surface unobstructed water storage information;

[0012] A prediction module for predicting the surface obstructed water storage information based on the terrain data and the surface unobstructed water storage information;

[0013] A calculation module for calculating the surface water storage volume based on the surface unobstructed water storage information and the surface obstructed water storage information.

[0014] In a third aspect, the present application also provides a computing device, including a memory, a processor, and a program stored in the memory and running on the processor. When the processor executes the program, it implements the steps of a method for retrieving surface water storage based on satellite remote sensing as described above.

[0015] In a fourth aspect, the present application also provides a computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions run on a terminal device, the terminal device is caused to execute the steps of a method for retrieving surface water storage based on satellite remote sensing.

[0016] The beneficial effects of the present application are as follows: First, by analyzing the remote sensing images of the surface obtained by satellite remote sensing, terrain data and surface unobstructed water storage information are obtained, and based on the terrain data and surface unobstructed water storage information, surface obstructed water storage information is predicted. Second, based on the surface unobstructed water storage information and surface obstructed water storage information, the surface water storage volume is calculated. In this way, when retrieving the surface water storage volume, the surface obstructed water storage information is also considered, so that the retrieved surface water storage volume can include the water storage volume situation blocked by abnormal landforms in complex terrain areas on the surface, thereby improving the accuracy of the retrieved surface water storage volume. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a schematic flowchart of a method for retrieving surface water storage based on satellite remote sensing shown in an exemplary embodiment of the present application;

[0018] Figure 2 It is a schematic structural diagram of a system for retrieving surface water storage based on satellite remote sensing shown in an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0019] The following embodiments are further explanations and supplements to the present application and do not constitute any limitation to the present application.

[0020] The following describes a method and a system for retrieving surface water storage based on satellite remote sensing in embodiments of the present application with reference to the accompanying drawings.

[0021] A method for retrieving surface water storage based on satellite remote sensing in an embodiment of the present application. This method is applied to a terminal device. In the present application solution, the terminal device or the server is used as the execution subject to explain the present application solution. The terminal device or the server is used to execute the steps of a method for retrieving surface water storage based on satellite remote sensing.

[0022] Please refer to Figure 1 , Figure 1 It is a method for retrieving surface water storage based on satellite remote sensing shown in an exemplary embodiment of the present application. As Figure 1 shown, the present application provides a method for retrieving surface water storage based on satellite remote sensing, including:

[0023] Step S11: Obtain the remote sensing image of the ground surface using satellite remote sensing;

[0024] Step S12: Analyze the remote sensing image to obtain terrain data and unobstructed surface water storage information;

[0025] Step S13: Based on the terrain data and the unobstructed surface water storage information, predict the obstructed surface water storage information;

[0026] Step S14: Calculate the surface water storage volume based on the unobstructed surface water storage information and the obstructed surface water storage information.

[0027] In an embodiment of the present application, a method for retrieving surface water storage based on satellite remote sensing is provided. First, by analyzing the remote sensing image of the ground surface obtained by satellite remote sensing, terrain data and unobstructed surface water storage information are obtained, and based on the terrain data and the unobstructed surface water storage information, the obstructed surface water storage information is predicted. Second, based on the unobstructed surface water storage information and the obstructed surface water storage information, the surface water storage volume is calculated. In this way, the obstructed surface water storage information is also considered when retrieving the surface water storage volume, so that the retrieved surface water storage volume can include the water storage volume situation blocked by abnormal landforms at complex terrains on the ground surface, thereby improving the accuracy of the retrieved surface water storage volume.

[0028] Optionally, obtaining the remote sensing image of the ground surface using satellite remote sensing includes:

[0029] Use a satellite to perform microwave remote sensing on the ground surface from different angles to obtain multi-angle remote sensing data;

[0030] Preprocess the multi-angle remote sensing data to obtain the remote sensing image of the ground surface. The preprocessing includes calibration processing, image fusion, and information extraction.

[0031] In this embodiment provided by the present application, a satellite is used to perform microwave remote sensing on the ground surface from different angles to obtain relatively comprehensive multi-angle remote sensing data, and the multi-angle remote sensing data is preprocessed to process the multi-angle remote sensing data into a remote sensing image that can be recognized by the human eye and can include relatively comprehensive real ground surface information, so as to improve the matching degree between the obtained remote sensing image and the real ground surface, and further improve the accuracy of calculating the surface water storage volume based on the remote sensing image. Among them, the calibration processing includes radiometric calibration, geometric calibration, and atmospheric calibration.

[0032] Optionally, analyzing the remote sensing image to obtain terrain data and unobstructed surface water storage information includes:

[0033] Use a terrain feature extraction algorithm to process the remote sensing image to generate terrain data;

[0034] The remote sensing image is processed using the water body index method to generate unobstructed surface water storage information.

[0035] In this embodiment provided by the present application, the remote sensing image is processed using the terrain feature extraction algorithm and the water body index method respectively to generate terrain data and unobstructed surface water storage information. Compared with the manual processing method, the method of the present application can improve the generation efficiency of target data, thereby improving the inversion efficiency of surface water storage.

[0036] Optionally, processing the remote sensing image using the terrain feature extraction algorithm to generate terrain data includes:

[0037] Performing edge detection on the remote sensing image to obtain edge data, where the edge data includes object boundaries, terrain changes, and linear features;

[0038] Performing texture analysis on the remote sensing image to obtain texture data for each pixel in the remote sensing image, where the texture data includes object types, soil moisture, and terrain roughness;

[0039] Performing contour tracing on the remote sensing image to obtain contour data for each pixel in the remote sensing image;

[0040] Forming terrain data based on the edge data, texture data, and contour data.

[0041] In this embodiment provided by the present application, edge detection, texture analysis, and contour tracing are respectively performed on the remote sensing image to obtain the edge data of the remote sensing image, the texture data for each pixel in the remote sensing image, and the contour data, and terrain data is formed based on the edge data, texture data, and contour data, which facilitates subsequent accurate inversion of surface water storage based on the terrain data, thereby improving the accuracy of the inverted surface water storage.

[0042] In this embodiment, edge detection is an important technique in remote sensing image processing. It aims to detect the edge information between objects in the image, which is crucial for target segmentation and recognition. Through edge detection, terrain features such as object boundaries, terrain changes, and linear features can be identified to form edge data.

[0043] Object boundary: Edge detection can clearly identify the boundaries between different objects, such as the boundaries between forests and farmlands, rivers and lakes, cities and villages, etc. Object boundaries can be used for object classification and regional division.

[0044] Terrain change: In remote sensing images, the undulation of the terrain often leads to changes in the gray values of the image, thus forming edges. Therefore, edge detection can also be used to identify terrain changes, such as the trend of mountains and the undulation of hills.

[0045] Linear features: Linear features such as roads, rivers, and railways usually exhibit distinct edge features in remote sensing images. Through edge detection, the positions and orientations of these linear features can be accurately extracted.

[0046] In this embodiment, texture analysis is another important remote sensing image processing technique, which aims to extract texture information in the image for target recognition and classification. Through texture analysis, topographic features such as land cover types, soil moisture, vegetation cover, and terrain roughness can be identified to form texture data.

[0047] Land cover types: Different land cover types often exhibit different texture features in remote sensing images. For example, forests usually exhibit dense and regular textures, while farmlands may exhibit sparser and irregular textures. Therefore, texture analysis can be used to identify land cover types such as forests, farmlands, grasslands, and deserts.

[0048] Soil moisture and vegetation cover: The soil moisture and vegetation cover also affect the texture features of remote sensing images. For example, wet soil may exhibit relatively dull and smooth textures, while dry soil may exhibit relatively bright and rough textures. Similarly, dense vegetation usually exhibits thick textures, while sparse vegetation may exhibit sparser textures.

[0049] Terrain roughness: Terrain roughness refers to the irregularity of the surface morphology (topography). In remote sensing images, terrain roughness is usually manifested as the complexity of the image texture.

[0050] Optionally, the remote sensing image is processed using the water body index method to generate surface unobstructed water storage information, including:

[0051] Obtain the reflectance of each pixel in the remote sensing image;

[0052] Using a preset water body index model and light reflectance, calculate the corresponding water body index value to obtain a water body index image;

[0053] Based on the water body index value, perform threshold segmentation on the water body index image to obtain an unobstructed water body boundary;

[0054] Using a preset water body depth model and water body index value, calculate the corresponding unobstructed water body depth;

[0055] Based on the unobstructed water body boundary and unobstructed water body depth, form surface unobstructed water storage information.

[0056] In this embodiment provided by the present application, using a preset water index model and the reflectivity of each pixel in the remote sensing image, the water index value of each pixel is calculated to form a water index image. Based on the water index value, threshold segmentation is performed on the water index image to obtain the unoccluded water body boundary, and using a preset water depth model and the water index value, the unoccluded water depth of each pixel is calculated to form the surface unoccluded water storage information composed of the unoccluded water body boundary and the unoccluded water depth, which is convenient for subsequent accurate inversion of the surface water storage volume based on this surface unoccluded water storage information, thereby improving the accuracy of the inverted surface water storage volume.

[0057] In an exemplary embodiment provided by the present application, using a preset water index model and the light reflectivity, the corresponding water index value is calculated. The specific steps are as follows: Input the light reflectivity into the preset water index model for calculation to obtain the water index value of the pixel corresponding to the light reflectivity.

[0058] The mathematical expression of the water index model can be:

[0059] MNDWI = (Green - SWIR1) / (Green + SWIR1);

[0060] Where, MNDWI represents the normalized difference water index value, Green represents the reflectivity of the green band of the pixel, NIR represents the reflectivity of the near-infrared band of the pixel, and SWIR1 represents the reflectivity of the short-wave infrared 1 band of the pixel;

[0061] The mathematical expression of the water index model can also be:

[0062] RWI = Green / NIR;

[0063] Where, RWI represents the water index value, Green represents the reflectivity of the green band of the pixel, and NIR represents the reflectivity of the near-infrared band of the pixel;

[0064] The mathematical expression of the water index model can also be:

[0065] AWEI = 4 × (Green - SWIR1) - 0.25 × NIR + 2.75 × SWIR2;

[0066] Where, AWEI represents the automated water extraction index value, that is, the water index value extracted automatically, Green represents the reflectivity of the green band of the pixel, SWIR1 represents the reflectivity of the short-wave infrared 1 band of the pixel, NIR represents the reflectivity of the near-infrared band of the pixel, and SWIR2 represents the reflectivity of the short-wave infrared 2 band of the pixel.

[0067] In an exemplary embodiment provided by the present application, the preset water body index model is a model that meets the accuracy requirements and is pre-trained using a water body index value training set and a corresponding water depth training set.

[0068] Optionally, the terrain data includes edge data, texture data, and contour data, and the unoccluded water storage information on the ground surface includes unoccluded water body boundaries and unoccluded water depths;

[0069] Based on the terrain data and the unoccluded water storage information on the ground surface, the occluded water storage information on the ground surface is predicted, including:

[0070] The boundary in the unoccluded water body boundary where the unoccluded water depth is greater than a set value is used as an abnormal boundary;

[0071] The edge data, texture data, and contour data that are adjacent to the abnormal boundary and do not belong to the water body information are used as occluded edge data, occluded texture data, and occluded contour data;

[0072] Based on the occluded edge data, occluded texture data, occluded contour data, and abnormal boundary, the occluded water storage information on the ground surface is determined.

[0073] In the embodiment provided by the present application, when there is a boundary in the unoccluded water body boundary where the unoccluded water depth is greater than the set value, it indicates that there may be surface water storage occluded by abnormal landforms at this boundary. Then, this boundary is used as an abnormal boundary. Then, the edge data, texture data, and contour data that are adjacent to the abnormal boundary and do not belong to the water body information are used as occluded edge data, occluded texture data, and occluded contour data, and based on the occluded edge data, occluded texture data, occluded contour data, and abnormal boundary, the occluded water storage information on the ground surface is determined, which is convenient for subsequent participation of the occluded water storage information on the ground surface in the inversion of the surface water storage volume, so that the inverted surface water storage volume can include the water storage volume situation occluded by abnormal landforms at complex terrain on the ground surface, thereby improving the accuracy of the inverted surface water storage volume.

[0074] Optionally, determining the occluded water storage information on the ground surface based on the occluded edge data, occluded texture data, occluded contour data, and abnormal boundary includes:

[0075] Establish a hydrological model based on the occluded edge data, occluded texture data, and occluded contour data;

[0076] In the hydrological model, simulate the erosion of the abnormal boundary by the water flow in the unoccluded water body area where the abnormal boundary is located to obtain an occluded water body area;

[0077] Based on the occluded water body area and the unoccluded water depth of the abnormal boundary, obtain the occluded water depth of each pixel in the occluded water body area;

[0078] Form surface occlusion water storage information based on the occluded water body area and the occluded water body depth.

[0079] In this embodiment provided by the present application, first, a hydrological model established by using occlusion edge data, occlusion texture data, and occlusion contour data is used to simulate the erosion of the abnormal boundary by the water flow in the unoccluded water body area where the abnormal boundary is located, so as to obtain the occluded water body area. Secondly, based on the occluded water body area and the unoccluded water body depth of the abnormal boundary, the occluded water body depth of each pixel in the occluded water body area is obtained, and surface occlusion water storage information is formed based on the occluded water body area and the occluded water body depth, which is convenient for subsequent participation of the surface occlusion water storage information in the inversion of the surface water storage volume, so that the inverted surface water storage volume can include the water storage volume situation occluded by the abnormal landform at the complex terrain on the surface, thereby improving the accuracy of the inverted surface water storage volume. Among them, the unoccluded water body area is a closed area surrounded by the water body boundary occluded by the abnormal landform.

[0080] Optionally, obtaining the occluded water body depth of each pixel in the occluded water body area based on the occluded water body area and the unoccluded water body depth of the abnormal boundary includes:

[0081] Taking the boundary in the occluded water body area except the corresponding abnormal boundary as the occlusion boundary;

[0082] Obtaining the distance information between the occlusion boundary and the abnormal boundary;

[0083] Based on the preset water flow erosion rule, distance information, and the unoccluded water body depth of the abnormal boundary, calculate the occluded water body depth of each pixel in the occluded water body area. The water flow erosion rule indicates that the depth change rule of the occluded water body area eroded by the water flow is an arithmetic progression.

[0084] In this embodiment provided by the present application, taking the boundary in the occluded water body area except the corresponding abnormal boundary as the occlusion boundary, and calculating the occluded water body depth of each pixel in the occluded water body area according to the preset water flow erosion rule based on the distance information between the occlusion boundary and the abnormal boundary and the unoccluded water body depth of the abnormal boundary, which is convenient for subsequent participation of the surface occlusion water storage information formed based on the occluded water body depth in the inversion of the surface water storage volume, so that the inverted surface water storage volume can include the water storage volume situation occluded by the abnormal landform at the complex terrain on the surface, thereby improving the accuracy of the inverted surface water storage volume.

[0085] In this embodiment, the water flow erosion rule can also indicate that the points in the abnormal boundary correspond to the points in the occlusion boundary one by one, the depth change rule between each group of corresponding points is an arithmetic progression, and the occluded water body depth corresponding to the points in the abnormal boundary is greater than the occluded water body depth corresponding to the points in the occlusion boundary.

[0086] Optionally, the unobstructed surface water storage information includes the unobstructed water body area and the unobstructed water body depth, and the obstructed surface water storage information includes the obstructed water body area and the obstructed water body depth;

[0087] Based on the unobstructed surface water storage information and the obstructed surface water storage information, the surface water storage is calculated, including:

[0088] Based on the resolution of the remote sensing image and the unobstructed water body depth of each pixel in the unobstructed water body area, the unobstructed surface water storage is calculated;

[0089] Based on the resolution and the obstructed water body depth of each pixel in the obstructed water body area, the obstructed surface water storage is calculated;

[0090] Based on the unobstructed surface water storage and the obstructed surface water storage, the surface water storage is calculated.

[0091] In this embodiment provided by the present application, based on the resolution of the remote sensing image, the true surface area corresponding to each pixel in the remote sensing image can be understood. Then, the unobstructed water body depth of each pixel in the unobstructed water body area is multiplied by the true surface area to obtain the unobstructed surface water storage, and the obstructed water body depth of each pixel in the obstructed water body area is multiplied by the true surface area to obtain the obstructed surface water storage. Then, the unobstructed surface water storage and the obstructed surface water storage are added together to obtain the surface water storage. In this way, the obstructed surface water storage is also considered when inverting the surface water storage, so that the inverted surface water storage can include the water storage situation blocked by abnormal landforms in complex terrain areas on the surface, thereby improving the accuracy of the inverted surface water storage.

[0092] Please refer to Figure 2 , Figure 2 which shows a surface water storage inversion system based on satellite remote sensing according to an exemplary embodiment of the present application. As Figure 2 shown, the present application provides a surface water storage inversion system 200 based on satellite remote sensing, including:

[0093] A remote sensing module 201 for obtaining a remote sensing image of the surface using satellite remote sensing;

[0094] An analysis module 202 for analyzing the remote sensing image to obtain terrain data and unobstructed surface water storage information;

[0095] A prediction module 203 for predicting the obstructed surface water storage information based on the terrain data and the unobstructed surface water storage information;

[0096] A calculation module 204 for calculating the surface water storage based on the unobstructed surface water storage information and the obstructed surface water storage information.

[0097] The surface water storage inversion system 200 based on satellite remote sensing provided in this embodiment first uses the analysis module 202 to analyze the remote sensing image of the surface obtained by satellite remote sensing using the remote sensing module 201, obtain terrain data and surface unoccluded water storage information, and use the prediction module 203 to predict the surface occluded water storage information based on the terrain data and the surface unoccluded water storage information. Secondly, the calculation module 204 calculates the surface water storage volume based on the surface unoccluded water storage information and the surface occluded water storage information. In this way, the surface occluded water storage information is also considered when inverting the surface water storage volume, so that the inverted surface water storage volume can include the water storage volume situation occluded by special-shaped landforms in complex terrain areas on the surface, thereby improving the accuracy of the inverted surface water storage volume.

[0098] Optionally, the remote sensing module 201 is specifically configured to:

[0099] Use a satellite to perform microwave remote sensing on the surface from different angles to obtain multi-angle remote sensing data;

[0100] Perform preprocessing on the multi-angle remote sensing data to obtain a remote sensing image of the surface. The preprocessing includes calibration processing, image fusion, and information extraction.

[0101] Optionally, the analysis module 202 is specifically configured to:

[0102] Use a terrain feature extraction algorithm to process the remote sensing image to generate terrain data;

[0103] Use the water body index method to process the remote sensing image to generate surface unoccluded water storage information.

[0104] Optionally, the analysis module 202 is specifically configured to:

[0105] Perform edge detection on the remote sensing image to obtain edge data, where the edge data includes object boundaries, terrain changes, and linear features;

[0106] Perform texture analysis on the remote sensing image to obtain texture data for each pixel in the remote sensing image. The texture data includes object types, soil moisture, and terrain roughness;

[0107] Perform contour tracing on the remote sensing image to obtain contour data for each pixel in the remote sensing image;

[0108] Form terrain data based on the edge data, texture data, and contour data.

[0109] Optionally, the analysis module 202 is specifically configured to:

[0110] Obtain the reflectivity of each pixel in the remote sensing image;

[0111] Calculate the corresponding water body index value using a preset water body index model and light reflectivity to obtain a water body index image;

[0112] Perform threshold segmentation on the water body index image based on the water body index value to obtain an unobstructed water body boundary;

[0113] Calculate the corresponding unobstructed water body depth using a preset water body depth model and the water body index value;

[0114] Form surface unobstructed water storage information based on the unobstructed water body boundary and the unobstructed water body depth.

[0115] Optionally, the terrain data includes edge data, texture data, and contour data, and the surface unobstructed water storage information includes an unobstructed water body boundary and an unobstructed water body depth;

[0116] The prediction module 203 is specifically configured to:

[0117] Use the boundary in the unobstructed water body boundary where the unobstructed water body depth is greater than a set value as an abnormal boundary;

[0118] Use the edge data, texture data, and contour data that are adjacent to the abnormal boundary and do not belong to water body information as occluded edge data, occluded texture data, and occluded contour data;

[0119] Determine surface occluded water storage information based on the occluded edge data, occluded texture data, occluded contour data, and the abnormal boundary.

[0120] Optionally, the prediction module 203 is specifically configured to:

[0121] Establish a hydrological model based on the occluded edge data, occluded texture data, and occluded contour data;

[0122] In the hydrological model, simulate the erosion of the abnormal boundary by the water flow in the unobstructed water body area where the abnormal boundary is located to obtain an occluded water body area;

[0123] Obtain the occluded water body depth of each pixel in the occluded water body area based on the occluded water body area and the unobstructed water body depth of the abnormal boundary;

[0124] Form surface occluded water storage information based on the occluded water body area and the occluded water body depth.

[0125] Optionally, the prediction module 203 is specifically configured to:

[0126] Use the boundary in the occluded water body area except for the corresponding abnormal boundary as an occluded boundary;

[0127] Obtain the distance information between the occluded boundary and the abnormal boundary;

[0128] Based on the preset water flow erosion rule, distance information, and the unoccluded water depth of the abnormal boundary, the occluded water depth of each pixel in the occluded water body area is calculated. The water flow erosion rule characterizes that the depth change rule of the occluded water body area eroded by the water flow is an arithmetic progression.

[0129] Optionally, the surface unoccluded water storage information includes the unoccluded water body area and the unoccluded water depth, and the surface occluded water storage information includes the occluded water body area and the occluded water depth;

[0130] The calculation module 204 is specifically configured to:

[0131] Based on the resolution of the remote sensing image and the unoccluded water depth of each pixel in the unoccluded water body area, the surface unoccluded water storage volume is calculated;

[0132] Based on the resolution and the occluded water depth of each pixel in the occluded water body area, the surface occluded water storage volume is calculated;

[0133] Based on the surface unoccluded water storage volume and the surface occluded water storage volume, the surface water storage volume is calculated.

[0134] It should be noted that the above-mentioned surface water storage inversion system based on satellite remote sensing provided in the above embodiment and the above-mentioned surface water storage inversion method based on satellite remote sensing belong to the same concept. The specific ways in which each module and unit perform operations have been described in detail in the method embodiment, and will not be repeated here. The above-mentioned surface water storage inversion system based on satellite remote sensing provided in the above embodiment can, in practical applications, allocate the above functions to different functional modules as needed, that is, divide the internal structure of the system into different functional modules to complete all or part of the functions described above. This is not limited here either.

[0135] A computing device according to an embodiment of the present application includes a memory, a processor, and a program stored on the memory and running on the processor. When the processor executes the program, it implements some or all of the steps of the above-mentioned surface water storage inversion method based on satellite remote sensing.

[0136] Among them, the computing device can be a computer. Correspondingly, its program is computer software, and the above parameters and steps in a computing device of the present application can refer to the parameters and steps in the embodiment of the above-mentioned surface water storage inversion method based on satellite remote sensing, and will not be elaborated here.

[0137] A computer-readable storage medium according to an embodiment of the present application stores instructions that, when running, execute the steps of the above-mentioned surface water storage inversion method based on satellite remote sensing.

[0138] Among them, the computer-readable storage medium can be a transient computer-readable storage medium or a non-transient computer-readable storage medium.

[0139] The technical solution of the embodiments of the present disclosure can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes one or more instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method of the embodiments of the present disclosure. The aforementioned computer-readable storage medium can be a non-transient computer-readable storage medium, including: various media such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs that can store program codes, or can also be a transient computer-readable storage medium.

[0140] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present application. Among them, each block in the flowchart or block diagram may represent a module, a program segment, or a part of the code, and the above-mentioned module, program segment, or part of the code includes one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram or flowchart, and the combination of blocks in the block diagram or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0141] Those skilled in the art of technology know that the present application can be implemented as a system, a method, or a computer program product. Therefore, the present disclosure can be specifically implemented in the following forms: it can be completely hardware, or completely software (including firmware, resident software, microcode, etc.), or a combination of hardware and software, which is generally referred to as a "module" or "system" in this article. In addition, in some embodiments, the present application can also be implemented in the form of a computer program product in one or more computer-readable media, and the computer-readable media contains computer-readable program codes. The computer-readable storage medium can be, for example, but not limited to - an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or component, or any combination of the above.

[0142] In the description of this specification, the descriptions referring to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of this application. In this specification, the schematic descriptions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0143] Although the embodiments of this application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting this application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A method for retrieving surface water storage based on satellite remote sensing, characterized in that, Including: Obtaining a remote sensing image of the earth's surface using satellite remote sensing; Analyzing the remote sensing image to obtain terrain data and surface unobstructed water storage information; Predicting surface obstructed water storage information based on the terrain data and the surface unobstructed water storage information; Calculating the surface water storage volume based on the surface unobstructed water storage information and the surface obstructed water storage information.

2. The method according to claim 1, characterized in that The obtaining a remote sensing image of the earth's surface using satellite remote sensing includes: Performing microwave remote sensing on the earth's surface from different angles using a satellite to obtain multi-angle remote sensing data; Performing preprocessing on the multi-angle remote sensing data to obtain a remote sensing image of the earth's surface, and the preprocessing includes calibration processing, image fusion, and information extraction.

3. The method according to claim 1, wherein The analyzing the remote sensing image to obtain terrain data and surface unobstructed water storage information includes: Processing the remote sensing image using a terrain feature extraction algorithm to generate terrain data; Processing the remote sensing image using a water body index method to generate surface unobstructed water storage information.

4. The method according to claim 3, characterized in that, The processing the remote sensing image using a terrain feature extraction algorithm to generate terrain data includes: Performing edge detection on the remote sensing image to obtain edge data, and the edge data includes object boundaries, terrain changes, and linear features; Performing texture analysis on the remote sensing image to obtain texture data of each pixel in the remote sensing image, and the texture data includes object types, soil moisture, and terrain roughness; Performing contour tracing on the remote sensing image to obtain contour data of each pixel in the remote sensing image; Forming terrain data based on the edge data, the texture data, and the contour data.

5. The method according to claim 3, characterized in that, The processing the remote sensing image using a water body index method to generate surface unobstructed water storage information includes: Obtaining the reflectance of each pixel in the remote sensing image; Calculating corresponding water body index values using a preset water body index model and the light reflectance to obtain a water body index image; Performing threshold segmentation on the water body index image based on the water body index values to obtain unobstructed water body boundaries; Calculating corresponding unobstructed water body depths using a preset water body depth model and the water body index values; Forming surface unobstructed water storage information based on the unobstructed water body boundaries and the unobstructed water body depths.

6. The method according to any one of claims 1 to 5, characterized in that The terrain data includes edge data, texture data, and contour data, and the surface unobstructed water storage information includes unobstructed water body boundaries and unobstructed water body depths; The predicting surface obstructed water storage information based on the terrain data and the surface unobstructed water storage information includes: Taking the boundaries in the unobstructed water body boundaries where the unobstructed water body depth is greater than a set value as abnormal boundaries; Taking the edge data, the texture data, and the contour data that are adjacent to the abnormal boundaries and do not belong to water body information as obstructed edge data, obstructed texture data, and obstructed contour data; Determining surface obstructed water storage information based on the obstructed edge data, obstructed texture data, obstructed contour data, and the abnormal boundaries.

7. The method according to claim 6, wherein The determining surface obstructed water storage information based on the obstructed edge data, obstructed texture data, obstructed contour data, and the abnormal boundaries includes: Establish a hydrological model based on the occlusion edge data, the occlusion texture data, and the occlusion contour data; In the hydrological model, simulate the erosion of the abnormal boundary by the water flow in the unoccluded water area where the abnormal boundary is located to obtain the occluded water area; Based on the occluded water area and the unoccluded water depth of the abnormal boundary, obtain the occluded water depth of each pixel in the occluded water area; Form surface occluded water storage information based on the occluded water area and the occluded water depth; 8. The method according to claim 7, wherein The obtaining the occluded water depth of each pixel in the occluded water area based on the occluded water area and the unoccluded water depth of the abnormal boundary includes: Take the boundary of the occluded water area except the corresponding abnormal boundary as the occlusion boundary; Obtain the distance information between the occlusion boundary and the abnormal boundary; Based on a preset water flow erosion rule, the distance information, and the unoccluded water depth of the abnormal boundary, calculate the occluded water depth of each pixel in the occluded water area, where the water flow erosion rule represents that the depth change rule of the occluded water area obtained by water flow erosion is an arithmetic progression; 9. The method according to claim 1, characterized in that The surface unoccluded water storage information includes the unoccluded water area and the unoccluded water depth, and the surface occluded water storage information includes the occluded water area and the occluded water depth; The calculating the surface water storage volume based on the surface unoccluded water storage information and the surface occluded water storage information includes: Calculate the surface unoccluded water storage volume based on the resolution of the remote sensing image and the unoccluded water depth of each pixel in the unoccluded water area; Calculate the surface occluded water storage volume based on the resolution and the occluded water depth of each pixel in the occluded water area; Calculate the surface water storage volume based on the surface unoccluded water storage volume and the surface occluded water storage volume; 10. A surface water storage inversion system based on satellite remote sensing, characterized in that, Includes: A remote sensing module for obtaining a remote sensing image of the surface using satellite remote sensing; An analysis module for analyzing the remote sensing image to obtain terrain data and surface unoccluded water storage information; A prediction module for predicting the surface occluded water storage information based on the terrain data and the surface unoccluded water storage information; A calculation module for calculating the surface water storage volume based on the surface unoccluded water storage information and the surface occluded water storage information;

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