Lake reservoir capacity measuring and calculating method and device based on remote sensing satellite data, terminal and medium

Abstract

The invention belongs to the field of reservoir capacity measurement and calculation, and particularly discloses a lake reservoir capacity measurement and calculation method and device based on remote sensing satellite data, a terminal and a medium. DEM data of a lake reservoir at different historical times and lake reservoir water levels at corresponding times are obtained, and reservoir areas at different historical times are extracted through the DEM data; the reservoir capacities at different water levels are obtained through the reservoir capacity curve, and then a reservoir area-reservoir capacity model is constructed; obtaining lake reservoir remote sensing image data at a target moment, and extracting a lake reservoir area at the target moment from the lake reservoir remote sensing image data according to the normalized difference water body index; and based on a reservoir area-reservoir capacity model, according to the lake reservoir area at the target moment, obtaining the lake reservoir capacity at the target moment. According to the method, the remote sensing satellite data, the DEM data and the reasonable mathematical model are combined, the lake reservoir capacity is measured and calculated, the lake reservoir capacity measuring and calculating efficiency is improved, and the cost is reduced.

Description

Technical Field

[0001] The present invention belongs to the field of reservoir capacity measurement, and particularly relates to a method, device, terminal and medium for measuring the capacity of lakes and reservoirs based on remote sensing satellite data. Background Art

[0002] As important storage carriers of surface water resources, lakes and reservoirs play a crucial role in many fields such as water resource management, flood control and drought relief. Traditional methods for measuring the capacity of lakes and reservoirs often rely on field measurements, which require a large amount of human, material and time costs. Moreover, in some large lakes, reservoirs in remote areas or areas with complex terrain, field measurements face many difficulties and are even difficult to implement.

[0003] Currently, satellite remote sensing data makes it possible to monitor surface information over a large area and dynamically. However, the current method of directly and accurately measuring the capacity of lakes and reservoirs using only remote sensing data is only in the stage of simply estimating the water surface area, and it is not effectively combined with digital elevation model (DEM) data that can reflect terrain undulations, reducing the utilization rate of remote sensing data.

[0004] In addition, although DEM data can visually present topographic and geomorphic features and be used to extract the water area at different water levels, when used alone, it lacks real-time performance, is difficult to reflect the dynamic changes of the water area over time, and the cost and processing difficulty of obtaining high-precision DEM data are relatively high. At the same time, the water body recognition technology based on remote sensing images is not effectively connected with the reservoir capacity calculation and cannot directly serve the accurate assessment of the capacity of lakes and reservoirs. Therefore, it is necessary to integrate remote sensing satellite data, DEM data and a reasonable mathematical model to develop a new method for measuring the capacity of lakes and reservoirs to improve the efficiency of measuring the capacity of lakes and reservoirs and reduce costs. Summary of the Invention

[0005] To solve the above problems, the present invention provides a method, device, terminal and medium for measuring the capacity of lakes and reservoirs based on remote sensing satellite data. By combining remote sensing satellite data, DEM data and a reasonable mathematical model, the capacity of lakes and reservoirs is measured, the efficiency of measuring the capacity of lakes and reservoirs is improved, and the cost is reduced.

[0006] In the first aspect, the technical solution of the present invention provides a method for measuring the capacity of lakes and reservoirs based on remote sensing satellite data, including the following steps: Obtain the DEM data of the lakes and reservoirs at different historical times and the water levels of the lakes and reservoirs at the corresponding times, extract the reservoir areas at different historical times through the DEM data, and obtain the reservoir capacities at different water levels through the reservoir capacity curve, and then construct a reservoir area-reservoir capacity model; Obtain the remote sensing image data of the lake or reservoir at the target time, and extract the area of the lake or reservoir at the target time from the remote sensing image data of the lake or reservoir according to the normalized difference water index; Based on the reservoir area-capacity model, obtain the reservoir capacity of the lake or reservoir at the target time according to the area of the lake or reservoir at the target time.

[0007] In an alternative embodiment, the reservoir areas at different historical times are extracted through DEM data, specifically including: Obtain the water level of the lake or reservoir at the current time, use GIS software to extract the DEM area higher than this water level as the reservoir water surface range at this water level, and calculate the area of this range by GIS software to obtain the reservoir area at the current time.

[0008] In an alternative embodiment, obtain the remote sensing image data of the lake or reservoir at the target time, and extract the area of the lake or reservoir at the target time from the remote sensing image data of the lake or reservoir according to the normalized difference water index, specifically including: Obtain the remote sensing image data of the lake or reservoir at the target time containing the normalized difference water index and import it into the remote sensing image data processing system; Calculate each pixel of the remote sensing image of the lake or reservoir according to the normalized difference water index calculation formula to obtain the normalized difference water index image; Set the segmentation threshold; Assign the value of 1 to the pixels in the normalized difference water index image whose index is greater than or equal to the segmentation threshold, and assign the value of 0 to the pixels whose index is less than the segmentation threshold to obtain a binary image; The remote sensing image data processing system converts the raster data of the binary image into vector surface data through the raster to vector tool, and obtains the area of the lake or reservoir at the target time according to the vector surface data.

[0009] In an alternative embodiment, the normalized difference water index calculation formula is: MNDWI = (Green - SWIR) / (Green + SWIR); Where MNDWI is the normalized difference water index, Green is the green light band of the image, and SWIR is the short-wave infrared band of the image.

[0010] In an alternative embodiment, the segmentation threshold is 0.

[0011] In an alternative embodiment, obtaining the area of the lake or reservoir at the target time according to the vector surface data specifically includes: Export the vector surface data as a shp file and store it; Process the shp file based on the speckle processing tool of the remote sensing image data processing system to extract the speckle area; The area of the fragmented patch region is calculated through spatial analysis based on the remote sensing image data processing system, and the shape of the fragmented patch region is obtained through the shape index calculation method; Obtain the position of the fragmented patch region in the binary image and the distance from the surrounding water bodies; Classify the fragmented patch region based on the area, shape, position in the binary image, and distance from the surrounding water bodies of the fragmented patch region according to the preset rules; Perform operations of merging or removing fragmented patches according to the classification results; Obtain the area of the lake or reservoir at the target moment based on the vector surface data after fragmented patch processing.

[0012] In a second aspect, the technical solution of the present invention provides a device for measuring the capacity of a lake or reservoir based on remote sensing satellite data, including: A measurement model construction module, configured to obtain DEM data of lakes and reservoirs at different historical times and the water levels of lakes and reservoirs at corresponding times, extract the reservoir areas at different historical times through the DEM data, and obtain the reservoir capacities at different water levels through the reservoir capacity curve, and then construct a reservoir area - reservoir capacity model; A reservoir area acquisition module, configured to obtain remote sensing image data of a lake or reservoir at the target moment, and extract the reservoir area of the lake or reservoir at the target moment from the remote sensing image data of the lake or reservoir according to the normalized difference water index; A reservoir capacity measurement module, configured to obtain the reservoir capacity of the lake or reservoir at the target moment based on the reservoir area - reservoir capacity model according to the reservoir area of the lake or reservoir at the target moment.

[0013] In an optional implementation manner, the reservoir area acquisition module is specifically configured to: Obtain remote sensing image data of a lake or reservoir at the target moment containing the normalized difference water index and import it into the remote sensing image data processing system; Calculate each pixel of the remote sensing image of the lake or reservoir according to the normalized difference water index calculation formula to obtain a normalized difference water index image; Set a segmentation threshold; Assign a value of 1 to the pixels in the normalized difference water index image with an index greater than the segmentation threshold, and assign a value of 0 to the pixels with an index less than the segmentation threshold to obtain a binary image; The remote sensing image data processing system converts the raster data of the binary image into vector surface data through a raster - to - vector tool, and obtains the reservoir area of the lake or reservoir at the target moment according to the vector surface data.

[0014] In a third aspect, the technical solution of the present invention provides a terminal, including: A memory, configured to store a program for measuring the capacity of a lake or reservoir based on remote sensing satellite data; A processor for implementing the steps of the method for calculating the capacity of lakes and reservoirs based on remote sensing satellite data as described in any one of the above when executing the program for calculating the capacity of lakes and reservoirs based on remote sensing satellite data.

[0015] In a fourth aspect, the technical solution of the present invention provides a computer-readable storage medium, on which a program for calculating the capacity of lakes and reservoirs based on remote sensing satellite data is stored. When the program for calculating the capacity of lakes and reservoirs based on remote sensing satellite data is executed by a processor, the steps of the method for calculating the capacity of lakes and reservoirs based on remote sensing satellite data as described in any one of the above are implemented.

[0016] The method, device, terminal and medium for calculating the capacity of lakes and reservoirs based on remote sensing satellite data provided by the present invention have the following beneficial effects compared with the prior art: First, the DEM data of lakes and reservoirs at different historical times are combined with the water levels of lakes and reservoirs at the corresponding times. Based on the characteristics of the DEM data reflecting the topography and landforms, and combined with the dynamic change information of the water levels, a reservoir area-capacity model is constructed to accurately describe the internal mathematical relationship between the area and capacity of lakes and reservoirs, so that the capacity calculation is no longer limited to a single moment or static conditions, but can adapt to the dynamic capacity assessment under different water level fluctuations, providing a data basis for the dynamic management of water resources; Second, the normalized difference water index is used to extract the reservoir area of the lakes and reservoirs at the target time from the remote sensing image data of lakes and reservoirs, giving play to the accuracy and convenience of MNDWI in the field of water body identification, and being able to more accurately divide the water body boundary, effectively excluding other interfering ground objects, and obtaining a higher accuracy of the reservoir area, thereby ensuring the accuracy of the capacity at the target time calculated based on the reservoir area-capacity model; In addition, taking advantage of the large-area and periodic observation advantages of remote sensing satellite data, it is possible to break through geographical space limitations, timely obtain the latest image information of the target lakes and reservoirs, without the need for a large amount of manpower to conduct in-depth field measurements, greatly saving manpower, material resources and time costs. The present invention calculates the capacity of lakes and reservoirs by combining remote sensing satellite data, DEM data and a reasonable mathematical model, improving the efficiency of calculating the capacity of lakes and reservoirs and reducing costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solution of the present invention, the drawings required for description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0018] Figure 1 It is a schematic flow chart of a method for calculating the capacity of lakes and reservoirs based on remote sensing satellite data provided by an embodiment of the present invention.

[0019] Figure 2Schematic block diagram of a device for calculating the capacity of lakes and reservoirs based on remote sensing satellite data provided by an embodiment of the present invention.

[0020] Figure 3 Schematic diagram of the structure of a terminal provided by an embodiment of the present invention. Detailed implementation manners

[0021] To make the objectives, features, and advantages of the present invention more obvious and understandable, the technical solutions in the present invention will be clearly and completely described below with reference to the accompanying drawings in the specific embodiments of the present invention. Obviously, the embodiments described below are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments in this patent, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of this patent.

[0022] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention belongs. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments, and are not intended to limit the present invention.

[0023] Figure 1 Schematic flowchart of a method for calculating the capacity of lakes and reservoirs based on remote sensing satellite data provided by an embodiment of the present invention. Among them, Figure 1 The execution subject can be a system for calculating the capacity of lakes and reservoirs based on remote sensing satellite data. The method for calculating the capacity of lakes and reservoirs based on remote sensing satellite data provided by the embodiments of the present invention is executed by a computer device. Correspondingly, the system for calculating the capacity of lakes and reservoirs based on remote sensing satellite data runs in the computer device. According to different requirements, the order of the steps in this flowchart can be changed, and some can be omitted.

[0024] As Figure 1 shown, the method includes the following steps.

[0025] S1. Obtain the DEM data of the lake or reservoir at different historical times and the water levels of the lake or reservoir at the corresponding times, extract the reservoir areas at different historical times through the DEM data, and obtain the reservoir capacities at different water levels through the reservoir capacity curve, and then construct a reservoir area-capacity model.

[0026] S2. Obtain the remote sensing image data of the lake or reservoir at the target time, and extract the reservoir area of the lake or reservoir at the target time from the remote sensing image data of the lake or reservoir according to the normalized difference water index.

[0027] S3. Based on the reservoir area-capacity model, obtain the reservoir capacity of the lake or reservoir at the target time according to the reservoir area of the lake or reservoir at the target time.

[0028] In this embodiment, by combining remote sensing satellite data, DEM data, and a reasonable mathematical model, the capacity of lakes and reservoirs is measured, improving the measurement efficiency of the capacity of lakes and reservoirs and reducing costs. To further understand the present invention, the following provides a detailed description of each of the above steps.

[0029] The first part is to construct a reservoir area-capacity model.

[0030] First, obtain the DEM data of lakes and reservoirs at different historical times and the water levels of lakes and reservoirs at the corresponding times. Extract the reservoir areas at different historical times through the DEM data, and obtain the capacities at different water levels through the capacity curve, thereby constructing a reservoir area-capacity model.

[0031] In the data collection stage, collect the DEM data of the studied lakes and reservoirs at different times to ensure the accuracy and integrity of the data, which can be sourced from satellite remote sensing, aerial photogrammetry, or ground survey, etc. Obtain the water level data of the reservoir at different corresponding times, which can be obtained from the water level monitoring stations of the reservoir or through historical records and relevant water conservancy departments. It should be noted that preprocess the collected DEM data, including processing such as unifying the coordinate system and projection conversion of the DEM data, to ensure that the DEM data and water level data at different times are in the same coordinate system for subsequent analysis and calculation. At the same time, remove or repair the noise, outliers, etc. in the DEM data to improve the data quality.

[0032] The data processing stage includes extracting the reservoir areas at different historical times through the DEM data and obtaining the capacities at different water levels through the capacity curve. Further, extracting the reservoir areas at different historical times through the DEM data includes obtaining the water level of the lake and reservoir at the current time, using GIS software to extract the DEM area higher than this water level as the reservoir water surface range at this water level, and calculating the area of this range by GIS software to obtain the reservoir area at the current time.

[0033] Exemplarily, the library area is obtained using ArcGIS. First step, load the DEM data and water level data: In ArcGIS, load the DEM data of the study area into the map window through the "Add Data" function. At the same time, ensure that the corresponding water level data has been obtained and imported into ArcGIS in tabular form, or record the water level values for future use. Second step, create the water level surface: According to the given water level value, use the "Create TIN" or "Create Raster Surface" tool in the "3D Analyst" toolbar to create a plane with the same range as the DEM data and a height of the given water level value. This plane represents the reservoir water surface at the selected water level. Third step, extract the DEM area above the water level: Use the "Surface Analysis" → "Extract Above / Below Surface" tool in the "3D Analyst" toolbar. Select the DEM data as the input surface, and the just-created water level surface as the reference surface. Set to extract the area "above" the reference surface. After clicking "OK", raster data of the DEM area above this water level will be obtained. Fourth step, raster to vector: To facilitate area calculation, the raster area above the water level obtained from the extraction needs to be converted into vector polygons. Use the "Conversion Tools" → "From Raster" → "Raster to Polygon" tool to convert the raster data obtained in the previous step into vector polygon data. Fifth step, calculate the area: In ArcGIS, right-click on the converted vector polygon data, select "Open Attribute Table", add a new field in the attribute table to store the area value. Then, use the "Calculate Geometry" tool, select the "Area" option, and fill the calculated area value into the newly added field. This area value is the library area at the selected water level.

[0034] Furthermore, the reservoir capacity at different water levels is obtained through the reservoir capacity curve. Specifically, obtain the reservoir capacity curve of this lake reservoir from the reservoir management department. The reservoir capacity curve is usually drawn based on historical water level measurements and reservoir capacity calculation results, representing the corresponding relationship between the water level and the reservoir capacity. According to the water level data at each time point, look up the corresponding reservoir capacity value on the reservoir capacity curve, or use the fitting equation of the reservoir capacity curve to calculate the corresponding reservoir capacity through the water level value.

[0035] In this embodiment, the extracted library areas and corresponding reservoir capacity data at different water levels are sorted out. Using the library area as the independent variable and the reservoir capacity as the dependent variable, a suitable mathematical model is used for fitting, such as a linear regression model, a polynomial regression model, an exponential model, etc., to establish a "library area - reservoir capacity" model. An independent validation dataset can be used to validate the established model and evaluate the accuracy and reliability of the model. For example, indicators such as mean squared error, mean absolute error, and coefficient of determination are used to measure the fitting effect of the model, and the model is adjusted and optimized according to the validation results until the accuracy requirements are met.

[0036] The second part is to extract the lake / reservoir area at the target time based on the remote sensing image data of lakes and reservoirs.

[0037] In this embodiment, based on the remote sensing image data of lakes and reservoirs, the lake / reservoir area at the target time is extracted from the remote sensing image data of lakes and reservoirs through the Normalized Difference Water Index (MNDWI), which specifically includes the following steps.

[0038] Step 1: Obtain the remote sensing image data of the lake / reservoir at the target time containing the Normalized Difference Water Index and import it into the remote sensing image data processing system.

[0039] First, import the remote sensing image data containing the information of the Normalized Difference Water Index (MNDWI) into the selected remote sensing image data processing system. Common remote sensing image data processing systems include ENVI, ArcGIS, etc. Ensure that the image data format is correctly recognized by the system, and the information of each band is complete and the data quality is good.

[0040] Step 2: Calculate each pixel of the remote sensing image of the lake / reservoir according to the formula of the Normalized Difference Water Index to obtain the Normalized Difference Water Index image.

[0041] The construction of MNDWI is based on the special reflection characteristics of water bodies in the Short-Wave Infrared (SWIR) band. Compared with the red light band, water bodies have stronger absorption ability in the SWIR band. By combining the reflection information of the red light band and the SWIR band, water bodies and surrounding ground objects can be effectively highlighted. The formula for the Normalized Difference Water Index is: MNDWI=(Green - SWIR) / (Green + SWIR) Where MNDWI is the Normalized Difference Water Index, Green is the green light band of the image, and SWIR is the short-wave infrared band of the image.

[0042] It should be noted that the corresponding green band and mid-infrared band numbers of different remote sensing data sources are different. For example, for Landsat 8 OLI data, the green band is usually the 3rd band, and the mid-infrared band is the 6th band. Through the corresponding remote sensing image processing software (such as ENVI, ArcGIS, etc.), calculate each pixel of the image according to the formula to obtain a single-band MNDWI image.

[0043] Step 3: Set the segmentation threshold.

[0044] By observing the gray value distribution of the MNDWI image and combining with the actual water body characteristics of the research area, etc., methods such as visual interpretation, empirical values, or repeated experimental comparisons can be used to determine the appropriate threshold. Generally speaking, the MNDWI values corresponding to water body pixels are relatively high, usually around 0 and above. Due to differences in sediment content, pollution degree, etc. of water bodies in different regions, the thresholds will be different. In this embodiment, the segmentation threshold is set to 0.

[0045] Step 4, assign the value of 1 to the pixels in the normalized difference water index image whose index is greater than or equal to the segmentation threshold, and assign the value of 0 to the pixels whose index is less than the segmentation threshold, to obtain a binary image.

[0046] Perform binary operation on the calculated MNDWI image according to the determined threshold, that is, assign the value of 1 (representing water body) to the pixels in the image that are greater than or equal to the threshold, and assign the value of 0 (representing non-water body) to the pixels less than the threshold. In this way, a binary image is obtained, clearly distinguishing the water body and non-water body areas. Specifically, find the corresponding threshold segmentation tool in the remote sensing image data processing system. For the MNDWI image, set the threshold to 0 and execute the segmentation operation. The remote sensing image data processing system will screen out the pixels in the image with MNDWI values greater than 0 according to the set threshold. These pixels correspond to the areas preliminarily determined to be water bodies such as lakes and reservoirs, while the pixels with MNDWI values less than or equal to 0 are regarded as non-water body areas and excluded. After this step, a binary image showing only the water body areas of lakes and reservoirs (presented in black and white, with white representing water bodies and black representing non-water bodies) is obtained, providing a basis for generating water area range data in the subsequent steps.

[0047] Step 5, the remote sensing image data processing system converts the raster data of the binary image into vector surface data through the raster-to-vector tool, and obtains the area of lakes and reservoirs at the target time according to the vector surface data.

[0048] In this embodiment, image processing software (such as the boundary extraction tool in ArcGIS, the edge detection operator in ENVI, etc.) is used to perform boundary extraction operations on the binary water body image, and then calculate the area of lakes and reservoirs. For example, in ArcGIS, the raster data can be first converted into vector surface data through the raster-to-vector tool, and then the surface vector data of the water body can be converted into linear boundary data through the surface-to-line tool, obtaining the vector expression form of the water area boundary, and then calculating the area of lakes and reservoirs.

[0049] Step 5.1, convert the raster data of the binary image into vector surface data through the raster-to-vector tool.

[0050] Exemplarily, in ArcGIS, the "Raster to Polygon" tool can be used to convert binary water body raster data into polygon vector data. At this time, each continuous water body area (such as lakes, reservoirs, etc.) will be converted into a separate polygon feature.

[0051] Step 5.2, export the vector polygon data as a shp file and store it.

[0052] After converting the water body raster into vector polygon features, through the export or save as function of the system, select the shp file format for saving, specify the storage path and file name. At the same time, according to actual needs, relevant attribute information can also be set for the vector features in the generated shp file, such as adding fields and corresponding values for the water body name, affiliated area, etc., to facilitate subsequent query and analysis.

[0053] Step 5.3, process the shp file based on the patch processing tool of the remote sensing image data processing system to extract the patch area.

[0054] Use the patch processing tool in the remote sensing image data processing system to perform patch extraction operations on the generated vector data (shp file) of the lake and reservoir water area. These patches are relatively small and isolated parts in the water area vector polygon features, which may be caused by factors such as image resolution, water body edge complexity, or other factors, resulting in a fragmented state of the water body range. The tool will identify these patch areas and mark or separately extract them as corresponding feature sets or layers for further analysis.

[0055] Step 5.4, calculate the area of the patch area based on the spatial analysis of the remote sensing image data processing system, and obtain the shape of the patch area through the shape index calculation method.

[0056] For the extracted patch areas, use the spatial analysis function provided by the system to obtain information such as their area and shape. For example, in ArcGIS, the "Calculate Geometry" tool can be used to calculate attribute values such as the area and perimeter of the patches, and at the same time, analyze the shape characteristics of the patches through some shape index calculation methods (such as shape compactness, etc.).

[0057] Step 5.5, obtain the position of the patch area in the binary image and the distance from the surrounding water bodies.

[0058] Specifically, for each marked fragmented patch area, calculate its centroid coordinates using the spatial analysis function of the software. Taking ArcGIS as an example, there is a "Centroid" tool in the "Features" sub-menu under the "Data Management" tool. Using the fragmented patch feature class as the input, a new layer containing the centroid coordinates of each fragmented patch can be output. The coordinate values depend on the coordinate system initially adopted for the image, so that the position information of the fragmented patches in the binary image can be accurately obtained, usually represented by (X, Y) coordinate pairs.

[0059] For the distance to the surrounding water bodies, use the built-in Euclidean distance tool in the software, such as the "Euclidean Distance" tool in ArcGIS, to calculate the distance from the centroid of the fragmented patch to the nearest water body pixel in a straight-line distance manner. The output result is a distance raster image, and the value of each pixel in the image represents the distance from that position to the nearest water body. Map the centroid coordinates of the fragmented patches to this distance raster image to read the distance value between the fragmented patches and the surrounding water bodies.

[0060] Step 5.6, classify the fragmented patch areas based on the area and shape of the fragmented patch areas, their positions in the binary image, and the distances to the surrounding water bodies according to pre-set rules.

[0061] In this embodiment, classification rules are pre-set for classifying the fragmented patch areas to determine whether to perform a merging operation or a removal operation on the fragmented patch areas. The classification rules are set based on the area and shape of the fragmented patch areas, their positions in the binary image, and the distances to the surrounding water bodies.

[0062] Step 5.7, perform fragmented patch merging or removal operations according to the classification results.

[0063] For fragmented patches that are judged to belong to the same water body but are separated due to imaging reasons, etc., they can be merged into a continuous water body area using the merging function in the system (such as the merge feature operation under the editing tool in ArcGIS), so that the expression of the water area range is more in line with the actual situation.

[0064] For fragmented patches that are judged to be abnormal noise points or have too small an area and do not conform to the actual water body characteristics, they are removed from the vector data of the water area range through functions such as deleting features in the system to avoid interfering with subsequent analysis work based on water area data.

[0065] Step 5.8, obtain the area of the lake or reservoir at the target moment based on the vector surface data after fragmented patch processing.

[0066] Use the vector data area calculation function provided by the software (for example, in ArcGIS, the area of surface features can be calculated through the "Calculate Geometry" tool in the attribute table) to calculate the areas of the converted vector surface features of lakes and reservoirs respectively, and finally obtain the accurate area values of each lake and reservoir at the target time.

[0067] In an alternative embodiment, quality inspection is performed on the processed image data to check data integrity, clarity, positioning accuracy, effect of removing fragmented patches, and data consistency. After passing the quality inspection, the water boundary of the lake is obtained, the water body is converted into a vector polygon, and the area of the vector polygon is calculated, thereby obtaining the water area.

[0068] In the third part, the storage capacity of lakes and reservoirs is obtained according to the reservoir area-storage capacity model.

[0069] In this embodiment, based on the reservoir area-storage capacity model, the storage capacity of lakes and reservoirs at the target time is obtained according to the reservoir area of lakes and reservoirs at the target time. After the reservoir area of lakes and reservoirs at the target time has been extracted in the above second part, according to the reservoir area-storage capacity model constructed in the first part, the storage capacity of lakes and reservoirs at the target time is obtained.

[0070] Furthermore, the water resource situation of lakes and reservoirs is obtained through the analysis and evaluation of water level, water area, and lake / reservoir volume, and a water volume change curve of lakes and reservoirs is drawn. Analyze the changes in lake area and water storage volume over different times and spatial scales, including analysis of the change trend of reservoir area, analysis of the change trend of water storage volume, analysis of the spatial distribution of shrinking lakes, etc. And perform statistical analysis on the lake area and water storage volume to provide data support for the analysis of influencing factors of lake area and water storage volume.

[0071] In the above text, an embodiment of a method for measuring the capacity of lakes and reservoirs based on remote sensing satellite data has been described in detail. Based on the method for measuring the capacity of lakes and reservoirs based on remote sensing satellite data described in the above embodiment, the embodiment of the present invention also provides a device for measuring the capacity of lakes and reservoirs based on remote sensing satellite data corresponding to this method.

[0072] Figure 2 The following is a schematic block diagram of the structure of a device for measuring the capacity of lakes and reservoirs based on remote sensing satellite data provided by the embodiment of the present invention. In this embodiment, the device 200 for measuring the capacity of lakes and reservoirs based on remote sensing satellite data can be divided into multiple functional modules according to the functions it performs, such as Figure 2 shown. The functional modules may include: a measurement model construction module 210, a reservoir area acquisition module 220, and a storage capacity measurement module 230. The module referred to in the present invention means a series of computer program segments that can be executed by at least one processor and can complete fixed functions, and are stored in the memory.

[0073] The measurement model construction module 210 is configured to obtain DEM data of lakes and reservoirs at different historical times and the water levels of lakes and reservoirs at corresponding times, extract the reservoir areas at different historical times through the DEM data, and obtain the reservoir capacities at different water levels through the storage capacity curve, so as to construct a reservoir area - reservoir capacity model.

[0074] The reservoir area acquisition module 220 is configured to obtain remote sensing image data of a lake or reservoir at a target time, and extract the reservoir area of the lake or reservoir at the target time from the remote sensing image data of the lake or reservoir according to the normalized difference water index.

[0075] The reservoir capacity measurement module 230 is configured to obtain the reservoir capacity of the lake or reservoir at the target time based on the reservoir area - reservoir capacity model according to the reservoir area of the lake or reservoir at the target time.

[0076] In an optional embodiment, the reservoir area acquisition module 220 is specifically configured to: obtain the remote sensing image data of the lake or reservoir at the target time containing the normalized difference water index, and import it into the remote sensing image data processing system; calculate each pixel of the remote sensing image of the lake or reservoir according to the normalized difference water index calculation formula to obtain the normalized difference water index image; set the segmentation threshold; assign the value of 1 to the pixels in the normalized difference water index image whose index is greater than the segmentation threshold, and assign the value of 0 to the pixels whose index is less than the segmentation threshold to obtain a binary image; convert the raster data of the binary image into vector surface data by the raster - to - vector tool of the remote sensing image data processing system, and obtain the reservoir area of the lake or reservoir at the target time according to the vector surface data.

[0077] The lake and reservoir capacity measurement device based on remote sensing satellite data in this embodiment is used to implement the foregoing lake and reservoir capacity measurement method based on remote sensing satellite data. Therefore, the specific implementation manners in this device can be seen in the embodiment part of the lake and reservoir capacity measurement method based on remote sensing satellite data in the foregoing text. Therefore, its specific implementation manners can refer to the descriptions of the corresponding parts of each embodiment, and will not be elaborated here.

[0078] In addition, since the lake and reservoir capacity measurement device based on remote sensing satellite data in this embodiment is used to implement the foregoing lake and reservoir capacity measurement method based on remote sensing satellite data, its functions correspond to those of the above - mentioned method, and will not be repeated here.

[0079] Figure 3 The following is a schematic structural diagram of a terminal 300 provided by an embodiment of the present invention, including: a processor 310, a memory 320, and a communication unit 330. When the processor 310 implements the lake and reservoir capacity measurement program stored in the memory 320, the following steps are implemented: Obtain the DEM data of lakes and reservoirs at different historical times and the water levels of lakes and reservoirs at the corresponding times, extract the reservoir areas at different historical times through the DEM data, and obtain the reservoir capacities at different water levels through the storage capacity curve, and then construct a reservoir area-capacity model; Obtain the remote sensing image data of the lake and reservoir at the target time, and extract the reservoir area of the lake and reservoir at the target time from the remote sensing image data of the lake and reservoir according to the normalized difference water index; Based on the reservoir area-capacity model, obtain the reservoir capacity of the lake and reservoir at the target time according to the reservoir area of the lake and reservoir at the target time.

[0080] The present invention also provides a computer storage medium, and the storage medium herein may be a magnetic disk, an optical disk, a read-only memory (abbreviation: ROM) or a random access memory (abbreviation: RAM), etc.

[0081] The computer storage medium stores a program for calculating the capacity of lakes and reservoirs based on remote sensing satellite data. When the program for calculating the capacity of lakes and reservoirs based on remote sensing satellite data is executed by a processor, the following steps are implemented: Obtain the DEM data of lakes and reservoirs at different historical times and the water levels of lakes and reservoirs at the corresponding times, extract the reservoir areas at different historical times through the DEM data, and obtain the reservoir capacities at different water levels through the storage capacity curve, and then construct a reservoir area-capacity model; Obtain the remote sensing image data of the lake and reservoir at the target time, and extract the reservoir area of the lake and reservoir at the target time from the remote sensing image data of the lake and reservoir according to the normalized difference water index; Based on the reservoir area-capacity model, obtain the reservoir capacity of the lake and reservoir at the target time according to the reservoir area of the lake and reservoir at the target time.

[0082] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to those skilled in the art. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the broadest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for calculating the capacity of lakes and reservoirs based on remote sensing satellite data, characterized in that, Including the following steps: Obtain the DEM data of lakes and reservoirs at different historical times and the water levels of lakes and reservoirs at the corresponding times. Extract the reservoir areas at different historical times through the DEM data, and obtain the reservoir capacities at different water levels through the storage capacity curve, and then construct a reservoir area-capacity model; Obtain the remote sensing image data of the lake and reservoir at the target time, and extract the reservoir area of the lake and reservoir at the target time from the remote sensing image data of the lake and reservoir according to the normalized difference water index; Based on the reservoir area-capacity model, obtain the reservoir capacity of the lake and reservoir at the target time according to the reservoir area of the lake and reservoir at the target time.

2. The method for calculating the capacity of lakes and reservoirs based on remote sensing satellite data according to claim 1, wherein Extract the reservoir areas at different historical times through the DEM data, specifically including: Obtain the water level of the lake and reservoir at the current time, use GIS software to extract the DEM area higher than this water level as the reservoir water surface range at this water level, and calculate the area of this range by GIS software to obtain the reservoir area at the current time.

3. The method for calculating the capacity of lakes and reservoirs based on remote sensing satellite data according to claim 2, characterized in that, Obtain the remote sensing image data of the lake and reservoir at the target time, and extract the reservoir area of the lake and reservoir at the target time from the remote sensing image data of the lake and reservoir according to the normalized difference water index, specifically including: Obtain the remote sensing image data of the lake and reservoir at the target time containing the normalized difference water index and import it into the remote sensing image data processing system; Calculate each pixel of the remote sensing image of the lake and reservoir according to the normalized difference water index calculation formula to obtain the normalized difference water index image; Set the segmentation threshold; Assign the value of 1 to the pixels in the normalized difference water index image whose index is greater than or equal to the segmentation threshold, and assign the value of 0 to the pixels whose index is less than the segmentation threshold to obtain a binary image; The remote sensing image data processing system converts the raster data of the binary image into vector surface data through the raster-to-vector tool, and obtains the reservoir area of the lake and reservoir at the target time according to the vector surface data.

4. The method for calculating the capacity of lakes and reservoirs based on remote sensing satellite data according to claim 3, wherein, The normalized difference water index calculation formula is: MNDWI=(Green - SWIR) / (Green + SWIR); Where, MNDWI is the normalized difference water index, Green is the green light band of the image, and SWIR is the short-wave infrared band of the image.

5. The method for calculating the capacity of lakes and reservoirs based on remote sensing satellite data according to claim 3, wherein The segmentation threshold is 0.

6. The method for calculating the capacity of lakes and reservoirs based on remote sensing satellite data according to claim 3, characterized in that, Obtain the reservoir area of the lake and reservoir at the target time according to the vector surface data, specifically including: Export the vector surface data as a shp file and store it; Process the shp file based on the speckle processing tool of the remote sensing image data processing system to extract the speckle area; Calculate the area of the speckle area based on the spatial analysis of the remote sensing image data processing system and obtain the shape of the speckle area through the shape index calculation method; Obtain the position of the speckle area in the binary image and the distance from the surrounding water body; Classify the speckle area based on the preset rules according to the area and shape of the speckle area, its position in the binary image, and the distance from the surrounding water body; Perform speckle merging or removal operations according to the classification results; Obtain the reservoir area of the lake and reservoir at the target time according to the vector surface data after speckle processing.

7. A device for measuring the capacity of lakes and reservoirs based on remote sensing satellite data, characterized in that, Including: The measurement model construction module is used to obtain the DEM data of lakes and reservoirs at different historical times and the water levels of lakes and reservoirs at the corresponding times, extract the reservoir areas at different historical times through the DEM data, and obtain the reservoir capacities at different water levels through the storage capacity curve, so as to construct a reservoir area-capacity model; The reservoir area acquisition module is used to obtain the remote sensing image data of the lake and reservoir at the target time, and extract the reservoir area of the lake and reservoir at the target time from the remote sensing image data of the lake and reservoir according to the normalized difference water index; The reservoir capacity measurement module is used to obtain the reservoir capacity of the lake and reservoir at the target time based on the reservoir area-capacity model and the reservoir area of the lake and reservoir at the target time.

8. The device for calculating the capacity of lakes and reservoirs based on remote sensing satellite data according to claim 7, wherein, The reservoir area acquisition module is specifically used for: Obtain the remote sensing image data of the lake and reservoir at the target time containing the normalized difference water index and import it into the remote sensing image data processing system; Calculate each pixel of the remote sensing image of the lake and reservoir according to the normalized difference water index calculation formula to obtain a normalized difference water index image; Set the segmentation threshold; Assign the value of 1 to the pixels in the normalized difference water index image with an index greater than the segmentation threshold, and assign the value of 0 to the pixels with an index less than the segmentation threshold to obtain a binary image; The remote sensing image data processing system converts the raster data of the binary image into vector surface data through the raster-to-vector tool, and obtains the reservoir area of the lake and reservoir at the target time according to the vector surface data.

9. A terminal, characterized in that, It includes: A memory for storing a program for measuring the capacity of lakes and reservoirs based on remote sensing satellite data; A processor for implementing the steps of the method for measuring the capacity of lakes and reservoirs based on remote sensing satellite data as described in any one of claims 1-6 when executing the program for measuring the capacity of lakes and reservoirs based on remote sensing satellite data.

10. A computer-readable storage medium, characterized in that, The readable storage medium stores a program for measuring the capacity of lakes and reservoirs based on remote sensing satellite data, and when the program for measuring the capacity of lakes and reservoirs based on remote sensing satellite data is executed by a processor, it implements the steps of the method for measuring the capacity of lakes and reservoirs based on remote sensing satellite data as described in any one of claims 1-6.

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