Method and device for extracting reservoir damming and branching information based on digital elevation model

Abstract

The present invention discloses a method and device for extracting reservoir damming and interception information based on a digital elevation model, comprising: obtaining a reservoir digital elevation model and key parameters, extracting corresponding water level contour line datasets, range boundaries, and slope data; classifying the contour line datasets and performing faceting and spatial relationship operations to form different category patch datasets; querying and processing the patch datasets through spatial inclusion relationships to form a damming water area patch object set; traversing the object set, calculating the nearest point and minimum distance to the main flood control restricted water level patch or object set to form a damming and interception object, and calculating the dam top plane area, average elevation, and the lost storage capacity and affected storage capacity due to the damming and interception. The present invention overcomes the current technical problems of limited manual recognition accuracy and incomplete information extraction for damming and interception information, and provides a basis for reservoir flood control storage capacity analysis and damming and interception rectification decision-making.

Description

Technical Field

[0001] The present application relates to the fields of surveying and mapping and geographic information science, and in particular to a method and device for extracting reservoir damming and branching information based on a digital elevation model. Background Art

[0002] Reservoirs are important engineering facilities for developing and utilizing water resources and preventing and controlling flood disasters. They are crucial for flood control, water supply, ecology, power generation, and shipping. Reservoir capacity is a key parameter for reservoir scheduling, the original storage capacity of water conservancy hubs, and operational management. Its accuracy directly affects the reservoir's flood control safety and water storage benefits. However, over time, reservoir capacity may be affected by natural factors such as upstream sediment inflow and soil erosion along the reservoir banks, as well as human factors such as operational scheduling, silt removal, and capacity expansion, resulting in changes in actual storage capacity. Flood control capacity refers to the reservoir volume between the flood control high water level and the flood control limit water level. It is used to control floods and meet the flood control requirements of flood protection targets downstream of the reservoir. It is directly related to the reservoir's storage capacity and flood control effectiveness during floods.

[0003] Damming and blocking tributaries is an illegal act that encroaches on water, squeezes reservoir capacity, obstructs flood flow, and endangers the safety of reservoir projects. Fertilizer and fish farming can also lead to serious pollution of reservoir waters. Damming and blocking tributaries reduces reservoir capacity, impacts flood control, destroys vegetation, and impedes water purification. Therefore, reservoir management authorities have strengthened dynamic monitoring of damming and blocking tributaries.

[0004] Currently, dam and barrier information is mainly extracted manually based on optical remote sensing images. The extracted information includes the average length, average width, area, and water area affected by the dam and barrier. This method has the following shortcomings: (1) The accuracy of manually identified dam and barrier information is limited. The accuracy depends on the operator, and the knowledge of different operators varies, so the accuracy cannot be effectively guaranteed. (2) The extraction of dam and barrier information is incomplete. The optical remote sensing images lack elevation information, including the average elevation of the dam crest, the lost reservoir capacity, and the affected reservoir capacity. Subsequent analysis and judgment require further extraction of relevant information. Summary of the Invention

[0005] The purpose of the embodiment of the present invention is to provide a method and device for extracting reservoir dam and branch information based on a digital elevation model, which solves the problems existing in the related technology that the previous dam and branch information relies on limited accuracy of manual identification and lacks the average elevation of the dam top, lost storage capacity and key information affecting the storage capacity. It can realize the automatic extraction of dam and branch information to ensure accuracy and improve work efficiency, and also realize the complete extraction of the average elevation of the dam top, lost storage capacity of dam and branch and key information affecting the storage capacity. The present invention overcomes the current technical problems such as the limited accuracy of manual identification of dam and branch information and incomplete information extraction, and provides a data basis for reservoir flood control storage capacity analysis and dam and branch rectification decision-making.

[0006] According to a first aspect of an embodiment of the present application, a method for extracting reservoir damming and branching information based on a digital elevation model is provided, comprising:

[0007] S1: Obtain the reservoir digital elevation model, flood control limit water level, flood control high water level, target resolution, maximum dam width, minimum water area, minimum acute angle and reservoir surface seed points;

[0008] S2: preprocessing the digital elevation model according to the flood control restricted water area, flood control high water level and target resolution, and extracting corresponding water level contour line dataset, range boundary and slope data based on the preprocessed digital elevation model;

[0009] S3: Classifying the contour line dataset, using the reservoir water surface seed points and the minimum water area and performing faceting and spatial relationship operations to generate different types of patch datasets, namely, a main flood control limit water level patch dataset, a secondary flood control limit water level patch dataset, and a secondary flood control high water level patch dataset;

[0010] S4: traversing the secondary flood control high water level patch dataset and the secondary flood control limit water level patch dataset, and forming a damming water area patch object set through spatial inclusion relationship query and judgment processing;

[0011] S5: Traversing the dammed water area patch object set, calculating the closest point and minimum distance between each patch and the main flood control restricted water level patch, forming a dammed branch object and adding it to the dammed branch object set after using the maximum dam width judgment and the minimum acute angle constraint, and marking the water area patch object at the same time;

[0012] S6: traversing the dammed water area patch object set, determining the water area patch object mark, respectively calculating the closest point and minimum distance between the water area patch object set and the dammed water area patch object set, and forming a dammed branch object after using the maximum dam width determination and the minimum acute angle constraint, and adding it to the dammed branch object set;

[0013] S7: traverse the damming and branching object set, and calculate the dam crest plane area, the dam crest average elevation, the lost storage capacity due to damming and branching, and the storage capacity affected by damming and branching respectively in combination with the slope data.

[0014] According to a second aspect of an embodiment of the present application, a device for extracting reservoir damming and branching information based on a digital elevation model is provided, comprising:

[0015] The acquisition module is used to obtain the digital elevation model of the reservoir, flood control limit water level, flood control high water level, target resolution, maximum dam width, minimum water area, minimum acute angle and reservoir surface seed points;

[0016] A preprocessing and extraction module is used to preprocess the digital elevation model according to the flood control restricted water area, flood control high water level and target resolution, and extract the corresponding water level contour line dataset, range boundary and slope data based on the preprocessed digital elevation model;

[0017] A patch dataset generation module is used to classify the contour line dataset, and generate different types of patch datasets by using the reservoir water surface seed points and the minimum water area and performing faceting and spatial relationship operations, namely, a main flood control limit water level patch dataset, a secondary flood control limit water level patch dataset, and a secondary flood control high water level patch dataset;

[0018] A water area patch object set generation module is used to traverse the secondary flood control high water level patch dataset and the secondary flood control limit water level patch dataset, and form a damming water area patch object set through spatial inclusion relationship query and judgment processing;

[0019] A first barrier object set generation module is configured to traverse the dammed water area patch object set, calculate the closest point and minimum distance between the dammed water area patch and the main flood control limit water level patch, and generate a dammed barrier object after using the maximum dam width judgment and the minimum acute angle constraint, and add the dammed barrier object to the dammed barrier object set, while marking the water area patch object.

[0020] A second barrier object set generation module is configured to traverse the dammed water area patch object set, determine the water area patch object mark, calculate the closest point and minimum distance between the water area patch object and the dammed water area patch object set, and generate a dammed barrier object using the maximum dam width determination and minimum acute angle constraint, and add the dammed barrier object to the dammed barrier object set;

[0021] The calculation module is used to traverse the damming and intercepting object set, and calculate the dam top plane area, the dam top average elevation, the lost storage capacity due to damming and intercepting, and the storage capacity affected by damming and intercepting in combination with the slope data.

[0022] According to a third aspect of the embodiments of the present application, there is provided an electronic device, including:

[0023] one or more processors;

[0024] a memory for storing one or more programs;

[0025] When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in the first aspect.

[0026] According to a fourth aspect of an embodiment of the present application, a computer-readable storage medium is provided, on which computer instructions are stored. When the instructions are executed by a processor, the steps of the method described in the first aspect are implemented.

[0027] The technical solutions provided by the embodiments of the present application may have the following beneficial effects:

[0028] It can be seen from the above embodiments that the present application adopts a reservoir dam and branch information extraction method based on a digital elevation model, uses a digital elevation model to generate contour lines and slope data, forms a dammed water area map object set through contour line classification and a series of spatial relationship operations, traverses and calculates the nearest point and minimum distance of the object set, generates a dam and branch object set after using the maximum width judgment of the dam and the minimum acute angle constraint, and finally calculates the dam and branch information in combination with the slope data. This overcomes the current technical problems of limited manual recognition accuracy and incomplete information extraction based on optical remote sensing images for dam and branch information, and achieves the purpose of extracting complete information of dam and branch including the average elevation of the dam top, lost storage capacity and affected storage capacity, and automatically identifying and extracting dam and branch information, which is conducive to improving accuracy and efficiency, and provides reliable data for reservoir flood control storage capacity analysis and dam and branch rectification decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0030] Figure 1 The present invention is a flowchart of a method for extracting reservoir damming and branch interception information based on a digital elevation model according to an exemplary embodiment.

[0031] Figure 2 The figure is a schematic diagram of a digital elevation model of a reservoir according to an exemplary embodiment.

[0032] Figure 3 The diagram is a schematic diagram of a flood control high water level, a flood control limit water level and a range boundary of a local area generated by a digital elevation model of a reservoir according to an exemplary embodiment.

[0033] Figure 4 The figure is a schematic diagram of slope data of a local area generated by a digital elevation model of a reservoir according to an exemplary embodiment.

[0034] Figure 5 The diagram is a schematic diagram showing a classification of a major flood control restricted water level patch, a minor flood control restricted water level patch dataset, a major flood control high water level patch, and a minor flood control high water level patch dataset for a local area of ​​a reservoir according to an exemplary embodiment.

[0035] Figure 6 The figure is a schematic diagram of a typical dammed water area patch object in a local area of ​​a reservoir according to an exemplary embodiment.

[0036] Figure 7The figure is a schematic diagram showing the polygons of damming and intercepting branches and the plane slope of the dam top in a local area of ​​a reservoir according to an exemplary embodiment.

[0037] Figure 8 The figure is a schematic diagram showing the average width of a polygonal dam body for damming and blocking branches in a local area of ​​a reservoir according to an exemplary embodiment.

[0038] Figure 9 The present invention is a block diagram of a device for extracting reservoir damming and branch interception information based on a digital elevation model according to an exemplary embodiment.

[0039] Figure 10 The figure is a schematic structural diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0040] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0041] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. As used in this application and the appended claims, the singular forms "a," "an," "the," and "the" are intended to include the plural forms, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.

[0042] It should be understood that although the terms first, second, third, etc. may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0043] the term:

[0044] A Digital Elevation Model (DEM) is a digital simulation of ground topography using limited terrain elevation data. DEM data is organized and expressed in two ways: regular rectangular grids and irregular triangulated networks. Regular rectangular grid DEMs are often stored in raster data formats, such as TIFF.

[0045] The flood control limit water level refers to the upper limit of water allowed to be stored in a reservoir during the flood season. It is also the starting water level for flood control operations during the flood season and is also known as the flood control limit water level. During the flood season, reservoirs use a portion of their storage capacity to store floodwater and reduce flood peaks to ensure safe discharge and reduce the need for flood discharge equipment. During floods, the reservoir water level is only allowed to exceed the flood control limit water level; when the flood subsides, the reservoir water level should return to the flood control limit water level.

[0046] The flood control high water level refers to the highest water level reached in front of the dam when the reservoir encounters the design standard flood of the downstream protection object.

[0047] Nearest neighbor analysis calculates the distance between each point in one feature class and the nearest point or line feature in another feature class.

[0048] Figure 1 This is a flow chart showing a method for extracting reservoir damming and branching information based on a digital elevation model according to an exemplary embodiment. Figure 1 The method for extracting reservoir damming and branching information based on a digital elevation model may include the following steps:

[0049] S1: Obtain the reservoir digital elevation model, flood control limit water level, flood control high water level, target resolution, maximum dam width, minimum water area, minimum acute angle and reservoir surface seed points;

[0050] Specifically, a digital elevation model (DEM) is obtained. This model is a digital simulation of the ground topography using limited terrain elevation data. DEM data is organized and expressed in two ways: regular rectangular grids and irregular triangulated networks. Regular rectangular grid DEMs are often stored in raster data formats, such as TIFF.

[0051] For example, the flood control limit water level of a reservoir is 168.74m, the flood control high water level is 173.00m, the target resolution is 0.5m, the maximum dam width is 50m, the minimum water area is 10㎡, and the minimum acute angle is 5°. The seed point of the reservoir water surface can be selected from any point on the reservoir water surface. The X and Y coordinates are currently 455557.236 and 2730674.698.

[0052] S2: preprocessing the digital elevation model according to the flood control restricted water area, flood control high water level and target resolution, and extracting corresponding water level contour line dataset, range boundary and slope data based on the preprocessed digital elevation model;

[0053] Specifically, digital elevation model preprocessing refers to checking the current digital elevation model format and grid size. When the digital elevation model format is an irregular triangulated network (TIN), it needs to be converted into a digital elevation model raster format according to the target resolution; when the digital elevation model is in raster format and the resolution is greater than the target resolution, cubic convolution resampling is required to the target resolution.

[0054] In this embodiment, Figure 2 The digital elevation model of a reservoir is a raster format data (TIFF) with a resolution of 2m. It is necessary to use cubic convolution resampling to generate a digital elevation model with a resolution of 0.5m. Based on the preprocessed digital elevation model, two water level contour line datasets of 168.74m and 173.00m, range boundary and slope data are extracted. Figure 3 The local flood control high water level, flood control limit water level and range boundary extracted for a reservoir are used for subsequent extraction of different types of patch datasets. Figure 4 The slope data of a local area extracted from a certain water area is preprocessed here to generate slope data, which is mainly used to extract the dam crest area and average elevation information of the dam crest for the final dam construction.

[0055] S3: Classify the contour line dataset, and use the reservoir water surface seed points and the minimum water area to generate different types of patch datasets through faceting and spatial relationship operations, namely, the main flood control limit water level patch dataset, the secondary flood control limit water level patch dataset, and the secondary flood control high water level patch dataset. This step includes the following sub-steps:

[0056] S31: dividing the contour line dataset into a flood control limit water level contour line dataset and a flood control high water level contour line dataset according to the elevation value, and shrinking the range boundary to form an inner range boundary;

[0057] Specifically, the contour dataset is classified into a flood control limit water level contour dataset and a flood control high water level contour dataset based on elevation values. In this embodiment, the range boundary is indented by 2 times the target resolution, that is, a -1.0m buffer is applied, resulting in a polygon forming the inner range boundary. Because the boundary may contain some data missing during raster-to-vector conversion, indenting by 2 times the target resolution ensures that the contour lines of the reservoir dam area intersect with the range boundary, ensuring successful surface construction.

[0058] S32: The inner range boundary and the flood control limit water level contour line dataset are uniformly constructed to form multiple polygons of the global flood control limit water level, and the largest area polygon is taken to perform intersection judgment with the reservoir water surface seed point. If they intersect, the inner ring of the largest area polygon is deleted and recorded as the main flood control limit water level patch; if the largest area polygon does not intersect with the reservoir water surface seed point, the inner ring of the second largest area polygon is deleted and recorded as the main flood control limit water level patch; the flood control limit water level contour line dataset is directly constructed to form the reservoir flood control limit water level polygon, and the main flood control limit water level patch is used for erasing analysis. The resulting polygons are first merged and then scattered, and then traversed. If the area is smaller than the minimum water area, the next traversal is performed; otherwise, it is added to the secondary flood control limit water level patch dataset;

[0059] Specifically, the inner range boundary and the 168.74m flood control limit water level contour dataset are uniformly constructed to form the global flood control limit water level polygon. There are a total of 1887 polygons. After being arranged in descending order of area, the areas of the first two polygons are 77462534.73 and 51302469.89. The reservoir water surface seed points are used to intersect these two polygons. The polygon with an area of ​​77462534.73 does not intersect with the reservoir water surface seed points and is the land area outside the reservoir water surface to the range boundary; the polygon with an area of ​​51302469.89 intersects with the reservoir water surface seed points and is the reservoir water surface area. In this case, the inner ring of this polygon is deleted and it is used as the main flood control limit water level patch. The 168.74m contour dataset was directly constructed to form 1883 polygons for the reservoir's flood control limit water level. Erasing analysis was performed using the primary flood control limit water level patch, resulting in 1032 polygons. These polygons were merged and then broken up, leaving a total of 901 polygons. A traversal was then performed. If the area was less than the minimum water area of ​​10 m2, the polygons were moved to the next traversal; otherwise, they were added to the secondary flood control limit water level patch dataset. Ultimately, 634 polygons with an area less than 10 m2 were filtered out, leaving 267 polygons to be added to the secondary flood control limit water level patch dataset. Using the minimum water area filter here reduces invalid patches and reduces subsequent processing workload.

[0060] S33: The inner range boundary and the flood control high water level contour line dataset are uniformly constructed to form multiple polygons of the global flood control high water level. The polygon with the largest area is taken to perform intersection judgment with the reservoir water surface seed point. If they intersect, the inner ring of the polygon with the largest area is deleted and recorded as the main flood control high water level patch. If the polygon with the largest area does not intersect with the reservoir water surface seed point, the inner ring of the polygon with the second largest area is deleted and recorded as the main flood control high water level patch. The flood control high water level contour line dataset is directly constructed to form a reservoir flood control high water level polygon. The main flood control high water level patch is used for erasing analysis. The resulting polygons are first merged and then broken up, and then traversed. If the area is smaller than the minimum water area, the next traversal is performed. Otherwise, it is added to the secondary flood control high water level patch dataset.

[0061] Specifically, the inner range boundary and the 173m flood control high water level contour line dataset are uniformly constructed to form the global flood control high water level polygon. There are a total of 4017 polygons. After being arranged in descending order of area, the areas of the first two polygons are 59915396.65 and 41082248.50. The reservoir water surface seed points are used to intersect these two polygons. The polygon with an area of ​​59915396.65 intersects with the reservoir water surface seed points and is the reservoir water surface area. In this case, the inner ring of this polygon is deleted and it is used as the main flood control high water level patch. Directly constructing the flood control high water level contour dataset, we generated 4013 polygons for the reservoir area flood control high water level. Using the primary flood control high water level patch for erasure analysis, we found 2440 polygons. These polygons were merged and then broken up, resulting in a total of 2076 polygons. Traversal was then performed. If the area was less than the minimum water area of ​​10 m2, the polygons were moved to the next traversal. Otherwise, they were added to the secondary flood control high water level patch dataset. Ultimately, 1581 polygons with an area less than 10 m2 were filtered out, leaving 495 polygons to be added to the secondary flood control high water level patch dataset. Using the minimum water area filter here reduces invalid patches and reduces subsequent processing workload.

[0062] Figure 5 The following diagram shows the different types of patch datasets formed after the above processing in a local area of ​​a reservoir, including the main flood control limit water level patch dataset, the secondary flood control limit water level patch dataset, the main flood control high water level patch dataset, and the secondary flood control high water level patch dataset. These will be used for the subsequent extraction of the dammed water area patch object set.

[0063] S4: Traversing the secondary flood control high water level patch dataset and the secondary flood control limit water level patch dataset, and forming a damming water area patch object set through spatial inclusion relationship query and judgment processing; this step includes the following sub-steps:

[0064] S41: traverse the secondary flood control high water level patch dataset, obtain the secondary flood control high water level patch, use its polygon as the search range and the spatial inclusion relationship as the search condition, query the secondary flood control limit water level patch dataset, and record the query result as the associated secondary flood control limit water level patch; if the associated secondary flood control limit water level patch is not empty, add a first label to it and save it, and take its polygon as the dammed water area polygon; if the query result is empty, then the secondary flood control high water level patch is recorded as the dammed water area polygon; construct a first dammed water area patch object that includes the dammed water area polygon, the secondary flood control high water level patch, and the associated secondary flood control limit water level patch, and add it to the dammed water area patch object set;

[0065] Specifically, the dataset of 495 secondary flood high water level patches was traversed to obtain secondary flood high water level patches. Using their polygons as the search range and spatial inclusion relationships as the search criteria, the dataset of secondary flood restricted water level patches was queried. The query results were recorded as associated secondary flood restricted water level patches. Of these, 37 secondary flood high water level patches were found to have secondary flood restricted water level patches. These 45 secondary flood restricted water level patches were marked as processed and saved. The remaining 458 secondary flood high water level patches had no associated secondary flood restricted water level patches. A total of 495 dammed water area patch objects were constructed, consisting of the dammed water area polygon, secondary flood high water level patches, and associated secondary flood restricted water level patches. These objects were added to the dammed water area patch object set. Figure 6 The situation 1 referred to herein is a certain secondary flood control high water level map area, which includes the secondary flood control restricted water level map area; the situation 2 referred to herein is a certain secondary flood control high water level map area, which does not include the secondary flood control restricted water level map area.

[0066] S42: traverse the secondary flood control limit water level patch dataset, obtain the secondary flood control limit water level patch, determine its label, and if it is the first label, proceed to the next traversal; if not, record the polygon of the secondary flood control limit water level patch as a dammed water area polygon, which is recorded as an associated secondary flood control limit water level patch; construct a second dammed water area patch object that includes the dammed water area polygon and the associated secondary flood control limit water level patch, and add it to the dammed water area patch object set;

[0067] Specifically, 267 secondary flood control limit water level patch datasets were traversed, of which 45 markers were processed, and dammed water patch objects containing dammed water polygons and associated secondary flood control limit water level patches were constructed, with a total of 222 objects, which were added to the dammed water patch object set. Figure 6 The situation 3 mentioned above refers to a secondary flood control restricted water level patch, which is located within the primary flood control high water level patch and cannot be queried through the secondary flood control high water level patch dataset.

[0068] S5: Traverse the dammed water area patch object set, calculate the closest point and minimum distance between the patch and the main flood control limit water level patch, and form a dammed branch object after using the maximum dam width judgment and the minimum acute angle constraint, and add it to the dammed branch object set, and mark the water area patch object at the same time; this step includes the following sub-steps:

[0069] S51: Traverse the dammed water area patch object set, obtain the dammed water area patch object, take the dammed water area polygon as the target polygon, calculate the closest point and minimum distance between the target polygon and the main flood control limit water level patch; if the minimum distance is greater than or equal to n times the maximum width of the dam, directly enter the next traversal;

[0070] Specifically, 717 dammed water area patch object sets are traversed to obtain the dammed water area patch objects, and their dammed water area polygons are recorded as target polygons. The nearest point and minimum distance between the target polygon and the main flood control limit water level patch are calculated. Figure 7 The coordinates X1 and Y1 of the nearest point of the middle dammed water area polygon (target polygon) to the main flood control limit water level map are calculated through nearest neighbor analysis, which are 460015.99 and 2734056.15, and the minimum distance is 16.35.

[0071] S52: If the minimum distance is less than n times the maximum width of the dam, calculate the neighboring points of the nearest point on the target polygon; construct a straight line with the nearest point and the neighboring points, take points on the straight line according to the target resolution, and obtain the elevation value of the point on the digital elevation model. If the maximum elevation value appears at the nearest point or the neighboring point, enter the next traversal; record the average of the elevation value of the nearest point and the elevation value of the neighboring point as the elevation of the bottom of the dam; with the neighboring point as the center, take points at equal intervals on the boundary of the target polygon, calculate the distance to the main flood control limit water level patch, and intercept the boundary of the target polygon with two points whose distance is equal to the maximum width of the dam, which is counted as the first inner boundary; with the nearest point as the center, take points at equal intervals on the boundary of the main flood control limit water level patch, calculate the distance to the target polygon, and intercept the boundary of the main flood control limit water level patch with two points whose distance is equal to the maximum width of the dam, which is counted as the first outer boundary;

[0072] Specifically, n here can be any real number between 1 and 5. n times the maximum dam width is mainly used to determine the relationship between the dam water area map and the main flood control limit water level map, and to determine whether the two are adjacent or separated by other dam water areas. In this embodiment, n is 2.

[0073] Among them, taking the neighboring point as the center, take points on the target polygon boundary at equal intervals, calculate the distance to the main flood control limit water level map, and intercept the target polygon boundary with two points whose distance is equal to the maximum width of the dam, which is counted as the first inner boundary. Specifically, it includes:

[0074] Calculate the starting point distance of the neighboring point on the boundary of the target polygon, and use this as the center, circularly select nodes at intervals of 0.1m forward, calculate the distance to the main flood control limit water level patch, stop the cycle when the distance is equal to the maximum width of the dam, and record the current forward node; circularly select nodes at intervals of 0.1m backward, calculate the distance to the main flood control limit water level patch, stop the cycle when the distance is equal to the maximum width of the dam, and record the current backward node; intercept the boundary of the target polygon based on the current forward node and the current backward node, and count it as the first inner boundary.

[0075] Among them, taking the nearest point as the center, take points on the boundary of the main flood control limit water level map at equal intervals, calculate the distance to the target polygon, and intercept the boundary of the main flood control limit water level map at two points with a distance equal to the maximum width of the dam, which is counted as the first outer boundary, specifically including:

[0076] Calculate the distance between the nearest point and the starting point of the main flood control limit water level map, and use this as the center to circularly select nodes at intervals of 0.1m forward, calculate the distance to the target polygon, and stop the cycle when the distance is equal to the maximum width of the dam, and record the current forward node; circularly select nodes at equal intervals of 0.1m backward, calculate the distance to the target polygon, and stop the cycle when the distance is equal to the maximum width of the dam, and record the current backward node; based on the current forward node and the current backward node, intercept the boundary of the main flood control limit water level map and record it as the first outer boundary.

[0077] In this embodiment, the minimum distance is 16.35, which is less than 2 times the maximum width of the dam, that is, 100m. The nearest point on the target polygon is calculated through nearest neighbor analysis, and its coordinates X2 and Y2 are 460032.20 and 2734060.87. A straight line is constructed with the nearest point and the nearest neighbor point, and a point is taken on the straight line according to the target resolution to obtain the elevation value of the point on the digital elevation model, as shown in Table 1. After calculation, the maximum elevation appears at coordinates X3 and Y3 of 460023.19 and 2734058.25, and the elevation value is 173.30. The elevation of the nearest point and the elevation of the nearest neighbor point are both 168.74m, and the average value is recorded as the elevation of the bottom of the dam, which is 168.74m. The first inner boundary and the first outer boundary are shown in Table 1. Figure 7 As shown, the process will not be repeated.

[0078] Table 1 shows the elevation values ​​on the straight line constructed by the nearest point and the neighboring points;

[0079]

[0080] S53: Construct a polygon based on the first inner boundary and the first outer boundary, and use the minimum acute angle constraint to process the spikes of the polygon. The processed polygon is recorded as the dam branch polygon, and the average distance between the first inner boundary and the first outer boundary is calculated and recorded as the average width of the dam body. The area of ​​the dam branch polygon is divided by the average width of the dam body and recorded as the average length of the dam body. Create a dam branch object with the dam branch polygon, the dam bottom elevation, the average width of the dam body, the average length of the dam body, and the dam water area map object, and add it to the dam branch object set; at the same time, add a second label to the dam water area map object and save it.

[0081] Specifically, the minimum acute angle constraint is used to process the spikes of polygons, as follows:

[0082] Taking the endpoint of the first inner boundary as the corner point, traverse the polygon nodes and select three consecutive points for acute angle spike detection. If the acute angle is less than the minimum acute angle, delete the spike node until it meets the requirements; similar processing is performed on the other endpoint of the first inner boundary and the two endpoints of the first outer boundary, which will not be repeated here. The angle between the three points can be calculated by first using the trigonometric cosine theorem. For example, if the coordinates of point A are (px1, py1), the coordinates of point B are (px2, py2), and the coordinates of point C are (px3, py3), then the cosine value of angle ABC is calculated as:

[0083] ;

[0084] ;

[0085] ;

[0086] ;

[0087] Where a is the distance between points B and C, c is the distance between points A and B, and b is the distance between points A and C. Angle ABC can then be calculated using the inverse cosine function.

[0088] In this embodiment, for example Figure 7 The damming arm polygon shown has been processed with acute angle constraints, and the upper left corner angle is 20 degrees. The area of ​​the damming arm polygon can be obtained through the open source library GDAL function, and the value is 1308.28㎡. The elevation of the dam bottom is 168.74m. The minimum width of the damming arm polygon is the minimum distance calculated above, 16.35m. The upper width is 39.89m, and the lower width is 30.75m. Based on the straight line connecting the nearest point and the nearest neighbor point, parallel lines are drawn at intervals of 1.0m to the left and right to intersect with the damming arm polygon. Figure 8As shown (the parallel lines on the left are not intersected, and the parallel lines on the right are intersecting segments), the average of the intersecting segments, the minimum distance, the upper width, and the lower width is calculated, and the value is 21.87m, which is the average width of the dam body. The average length of the dam body is 59.82m, obtained by dividing the area of ​​the dam-building polygon by the average width of the dam body.

[0089] S6: Traverse the dammed water area patch object set, determine the water area patch object mark, calculate the closest point and minimum distance between the object and the dammed water area patch object set, and form a dammed branch object after using the maximum dam width determination and minimum acute angle constraint and add it to the dammed branch object set; this step includes the following sub-steps:

[0090] S61: traverse the dammed water area patch object set, obtain the dammed water area patch object, determine the water area patch object label, if it is the second label, then enter the next traversal; if not, take the dammed water area polygon as the target polygon;

[0091] Specifically, 717 dammed water area patch object sets are traversed to obtain dammed water area patch objects, and the water area patch object label is determined. If it is the second label, the next traversal is entered; if not, the dammed water area polygon is recorded as the target polygon.

[0092] S62: The target polygon uses n times the maximum width of the dam as the search radius to query the dammed water area map object set. If the query result is empty, enter the next traversal; if the query result is not empty, the dammed water area polygon to which the queried dammed water area map object belongs is recorded as the reference polygon, and the nearest point and the minimum distance between the target polygon and the reference polygon are calculated; the nearest point of the nearest point on the target polygon is calculated, and a straight line is constructed with the nearest point and the nearest point. A point is taken on the straight line according to the target resolution to obtain the elevation value of the point on the digital elevation model. If the maximum elevation value is If it appears at the nearest point or the nearest neighbor point, the next traversal will begin; the average of the elevation values ​​of the nearest point and the nearest neighbor point is recorded as the dam bottom elevation; with the nearest neighbor point as the center, points are taken at equal intervals on the boundary of the target polygon, and the distance to the reference polygon is calculated. The boundary of the target polygon is intercepted by two points whose distance is equal to the maximum width of the dam, and this is counted as the second inner boundary; with the nearest point as the center, points are taken at equal intervals on the boundary of the reference polygon, and the distance to the target polygon is calculated. The boundary of the reference polygon is intercepted by two points whose distance is equal to the maximum width of the dam, and this is counted as the second outer boundary;

[0093] Specifically, n here can be any real number between 1 and 5. n times the maximum dam width is mainly used to determine the relationship between the dam water area map and the main flood control limit water level map, and to determine whether the two are adjacent or separated by other dam water areas. In this embodiment, n is 2.

[0094] Among them, taking the neighboring point as the center, take points on the boundary of the target polygon at equal intervals, calculate the distance to the reference polygon, and intercept the boundary of the target polygon with two points whose distance is equal to the maximum width of the dam, which is counted as the second inner boundary, specifically including:

[0095] Calculate the starting distance of the neighboring point on the boundary of the target polygon, and use this as the center to loop forward to take nodes, calculate the distance to the reference polygon, stop the loop when the distance is greater than the maximum width of the dam, and record the current forward node; loop backward to take nodes at equal intervals, calculate the distance to the reference polygon, stop the loop when the distance is greater than the maximum width of the dam, and record the current backward node; intercept the boundary of the target polygon based on the current forward node and the current backward node, and count it as the second inner boundary.

[0096] Among them, taking the nearest point as the center, take points on the reference polygon boundary at equal intervals, calculate the distance to the target polygon, and intercept the reference polygon boundary with two points whose distance is equal to the maximum width of the dam, which is counted as the second outer boundary, specifically including:

[0097] Calculate the distance between the nearest point and the starting point of the reference polygon, and use this as the center to loop forward to take nodes, calculate the distance to the target polygon, and stop the loop when the distance is greater than the maximum width of the dam, and record the current forward node; loop backward to take nodes at equal intervals, calculate the distance to the target polygon, and stop the loop when the distance is greater than the maximum width of the dam, and record the current backward node; based on the current forward node and the current backward node, intercept the boundary of the reference polygon and record it as the second outer boundary.

[0098] S63: Construct a polygon based on the second inner boundary and the second outer boundary, and use the minimum acute angle constraint to process the spikes of the polygon. The processed polygon is recorded as the dam-building branch polygon. The average distance between the second inner boundary and the second outer boundary is calculated and recorded as the average width of the dam body. The area of ​​the dam-building branch polygon is divided by the average width of the dam body to obtain the average length of the dam body. Create a dam-building branch object with the dam-building branch polygon, the dam bottom elevation, the average width of the dam body, the average length of the dam body, and the dam water area map object, and add it to the dam-building branch object set.

[0099] Specifically, the processing of polygon spikes using the minimum acute angle constraint is the same as S53 and will not be described in detail here.

[0100] Since the S6 process is basically the same as the S5 process, the specific embodiments are not described in detail.

[0101] S7: Traversing the damming and branching object set, and respectively calculating the dam crest plane area, the dam crest average elevation, the lost storage capacity due to damming and branching, and the storage capacity affected by damming and branching in combination with the slope data; this step includes the following sub-steps:

[0102] S71: Traverse the dam and branch object set to obtain the dam and branch objects, clip the slope data according to the dam and branch polygons of the dam and branch objects, and record the result as the dam and branch slope data. Reclassify the data according to whether the slope is greater than the flat land standard, and construct a polygon collection for the data with a slope less than the flat land standard. Traverse the polygon collection to calculate the average elevation within the polygon. If the average elevation is less than the average of the flood control high water level and the flood control limit water level, delete the polygon. Merge the traversed polygon collection, and record the resulting polygon as the dam crest plane polygon, whose area is the dam crest plane area. Calculate the average of the average elevations of the polygon collection, and record the result as the dam crest average elevation.

[0103] Specifically, the flat ground standard is a slope data with a slope of less than or equal to 5 degrees. Figure 7 The damming and branching objects shown are clipped with slope data based on the damming and branching polygons. The result is recorded as the damming and branching slope data. It is reclassified according to whether the slope is greater than 5 degrees. The data with a slope less than 5 degrees is used to construct a polygon collection, with a total of 10 polygons, as shown in Table 2. Traversal is performed. When the average elevation of one of the polygons is 169.26m, which is less than the average of the flood control high water level (173.00m) and the flood control limit water level (168.74m), 170.87m, the polygon is deleted and the next polygon is traversed. After the traversal, there are 8 polygons in the polygon collection. The merging operation is recorded as the dam top plane polygon, whose area is the dam top plane area, with a value of 89㎡. The average of the average elevation of the polygon collection after the traversal is calculated, and the result is recorded as the average elevation of the dam top, with a value of 173.38m.

[0104] Table 2 constructs a polygon collection for data with slopes less than 5 degrees;

[0105]

[0106] S72: The dam crest polygon is used as the top surface of the pyramid, the dam-barrier polygon is used as the bottom surface of the pyramid, and the dam crest average elevation minus the dam bottom elevation is used as the pyramid height. The storage capacity loss due to dam-barrier is calculated according to the pyramid volume formula.

[0107] Specifically, the dam top plane polygon is taken as the prism top surface S1, the dam-barrier polygon of the dam-barrier object is taken as the prism bottom surface S2, and the prism height h is taken as the average elevation of the dam top minus the elevation of the dam bottom. The storage capacity V1 lost by the dam-barrier can be roughly calculated according to the prism volume formula.

[0108]

[0109] The dam top plane polygon is used as the top surface of the pyramid S 1 (89) The damming and blocking polygon of the damming and blocking object is the bottom surface of the prism.S 2 (1038.28), the height of the prism is the average elevation of the dam top minus the elevation of the dam bottom. h（173.38-168.74 = 4.64） According to the prism volume formula, the loss of reservoir capacity V1 due to damming and blocking the branch is roughly calculated, which is 2213.69m³.

[0110]

[0111] S73: Based on the dammed water area patch object to which the dammed branch object belongs, if the secondary flood control high water level patch is not empty, its polygon is recorded as the dammed water area polygon; if it is empty, the polygon of the associated secondary flood control limit water level patch is recorded as the dammed water area polygon; using the dammed water area polygon as the boundary, the digital elevation model data is clipped, and its average elevation value is calculated; the flood control high water level minus the average elevation value is recorded as the average height of the dammed water area patch; the reservoir capacity affected by the dammed branch is calculated by multiplying the area of ​​the dammed water area polygon by the average height of the dammed water area patch;

[0112] Specifically, the reservoir capacity V2 affected by damming can be calculated based on the polygonal area of ​​the water area affected by damming. S Multiply by the average height of the dammed water area H calculate.

[0113] V2= S × H

[0114] For example Figure 7 If the secondary flood control high water level map is not empty for the damming and blocking object shown, then its polygon is recorded as the damming affected water area polygon, and the area is S =45624.89㎡; with the polygon of the water area affected by the dam as the boundary, the digital elevation model data is clipped and its average elevation value is 164.67m; the flood control high water level minus the average elevation value is recorded as the average height of the dam water area, that is, 173.00 minus 164.67 is 8.33m; the reservoir capacity V2 affected by the dam can be calculated according to the polygon area of ​​the water area affected by the dam. S Multiply by the average height of the dammed water area H The result of calculation is 380055.33m³.

[0115] V2=45624.89×8.33 = 380055.33.

[0116] It can be seen from the above embodiments that the present application adopts a reservoir dam and branch information extraction method based on a digital elevation model, uses a digital elevation model to generate contour lines and slope data, forms a dammed water area map object set through contour line classification and a series of spatial relationship operations, traverses and calculates the nearest point and minimum distance of the object set, generates a dam and branch object set after using the maximum width judgment of the dam and the minimum acute angle constraint, and finally calculates the dam and branch information in combination with the slope data. This overcomes the current technical problems of limited manual recognition accuracy and incomplete information extraction based on optical remote sensing images for dam and branch information, and achieves the purpose of extracting complete information of dam and branch including the average elevation of the dam top, lost storage capacity and affected storage capacity, and automatically identifying and extracting dam and branch information, which is conducive to improving accuracy and efficiency, and provides reliable data for reservoir flood control storage capacity analysis and dam and branch rectification decision-making.

[0117] Corresponding to the aforementioned embodiment of the method for extracting reservoir damming and branching information based on a digital elevation model, the present application also provides an embodiment of a device for extracting reservoir damming and branching information based on a digital elevation model.

[0118] Figure 9 This is a block diagram of a device for extracting reservoir damming and branching information based on a digital elevation model according to an exemplary embodiment. Figure 9 , the device comprises:

[0119] Acquisition module 1 is used to obtain the digital elevation model of the reservoir, flood control limit water level, flood control high water level, target resolution, maximum dam width, minimum water area, minimum acute angle and reservoir surface seed points;

[0120] Preprocessing and extraction module 2, for preprocessing the digital elevation model according to the flood control restricted water area, flood control high water level and target resolution, and extracting the corresponding water level contour line dataset, range boundary and slope data based on the preprocessed digital elevation model;

[0121] The patch dataset generation module 3 is used to classify the contour line dataset, and generate different types of patch datasets by using the reservoir water surface seed points and the minimum water area through faceting and spatial relationship operations, namely, the main flood control limit water level patch dataset, the secondary flood control limit water level patch dataset, and the secondary flood control high water level patch dataset;

[0122] The water area patch object set generation module 4 is used to traverse the secondary flood control high water level patch dataset and the secondary flood control limit water level patch dataset, and form a damming water area patch object set through spatial inclusion relationship query and judgment processing;

[0123] The first barrier object set generation module 5 is used to traverse the dammed water area patch object set, calculate the closest point and minimum distance between each of the dammed water area patch and the main flood control limit water level patch, and generate a dammed barrier object after using the maximum dam width judgment and the minimum acute angle constraint, and add it to the dammed barrier object set, and mark the water area patch object at the same time;

[0124] A second barrier object set generation module 6 is configured to traverse the dammed water area patch object set, determine the water area patch object mark, calculate the closest point and minimum distance between the water area patch object and the dammed water area patch object set, and generate a dammed barrier object using the maximum dam width determination and minimum acute angle constraint, and add the dammed barrier object to the dammed barrier object set;

[0125] The calculation module 7 is used to traverse the damming and intercepting object set, and calculate the dam top plane area, the dam top average elevation, the storage capacity lost by damming and intercepting, and the storage capacity affected by damming and intercepting in combination with the slope data.

[0126] Regarding the apparatus in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0127] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to the partial description of the method embodiments. The device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present application scheme. A person of ordinary skill in the art can understand and implement it without paying any creative work.

[0128] Accordingly, the present application also provides an electronic device, comprising: one or more processors; a memory for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors implement the above-mentioned method for extracting reservoir damming and branching information based on the digital elevation model. Figure 10 As shown in FIG, a hardware structure diagram of a device for extracting information of a reservoir damming and branching based on a digital elevation model provided by an embodiment of the present invention is provided, in addition to Figure 10 In addition to the processor, memory, DMA controller, disk, and non-volatile memory shown, any device with data processing capabilities in which the apparatus in the embodiment is located may also include other hardware, generally based on the actual functions of the device with data processing capabilities, which will not be described in detail.

[0129] Accordingly, the present application also provides a computer-readable storage medium having computer instructions stored thereon, which, when executed by a processor, implement the above-mentioned method for extracting reservoir damming and branching information based on a digital elevation model. The computer-readable storage medium may be an internal storage unit of any device with data processing capabilities described in any of the aforementioned embodiments, such as a hard disk or memory. The computer-readable storage medium may also be an external storage device, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), an SD card, a flash card, etc. equipped on the device. Furthermore, the computer-readable storage medium may also include both an internal storage unit and an external storage device of any device with data processing capabilities. The computer-readable storage medium is used to store the computer program and other programs and data required by any device with data processing capabilities, and may also be used to temporarily store data that has been output or is to be output.

[0130] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the contents disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present application that follow the general principles of the present application and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered merely as exemplary, and the true scope and spirit of the present application are indicated by the claims.

[0131] It should be understood that the present application is not limited to the exact structures described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for extracting reservoir damming and branching information based on a digital elevation model, characterized in that: include: S1: Obtain the reservoir digital elevation model, flood control limit water level, flood control high water level, target resolution, maximum dam width, minimum water area, minimum acute angle and reservoir surface seed points; S2: preprocessing the digital elevation model according to the flood control limit water level, flood control high water level and target resolution, and extracting corresponding water level contour line datasets, range boundaries and slope data based on the preprocessed digital elevation model; S3: Classifying the contour line dataset, using the reservoir water surface seed points and the minimum water area and performing faceting and spatial relationship operations to generate different types of patch datasets, namely, a main flood control limit water level patch dataset, a secondary flood control limit water level patch dataset, and a secondary flood control high water level patch dataset; S4: traversing the secondary flood control high water level patch dataset and the secondary flood control limit water level patch dataset, and forming a damming water area patch object set through spatial inclusion relationship query and judgment processing; S5: Traversing the dammed water area patch object set, calculating the closest point and minimum distance between each patch and the main flood control restricted water level patch, forming a dammed branch object and adding it to the dammed branch object set after using the maximum dam width judgment and the minimum acute angle constraint, and marking the water area patch object at the same time; S6: traversing the dammed water area patch object set, determining the water area patch object mark, respectively calculating the closest point and minimum distance between the water area patch object set and the dammed water area patch object set, and forming a dammed branch object after using the maximum dam width determination and the minimum acute angle constraint, and adding it to the dammed branch object set; S7: traverse the damming and branching object set, and calculate the dam crest plane area, the dam crest average elevation, the lost storage capacity due to damming and branching, and the storage capacity affected by damming and branching respectively in combination with the slope data.

2. The method according to claim 1, characterized in that Preprocessing the digital elevation model refers to checking the current digital elevation model format and grid size. When the digital elevation model format is an irregular triangulated network, it needs to be converted into a digital elevation model raster format according to the target resolution; when the digital elevation model is in a raster format and the resolution is greater than the target resolution, it needs to be resampled to the target resolution using the cubic convolution interpolation method.

3. The method according to claim 1, characterized in that The contour dataset is classified, and different types of patch datasets are generated using the reservoir water surface seed points and the minimum water area through faceting and spatial relationship operations, including: S31: dividing the contour line dataset into a flood control limit water level contour line dataset and a flood control high water level contour line dataset according to the elevation value, and shrinking the range boundary to form an inner range boundary; S32: The inner range boundary and the flood control limit water level contour line dataset are uniformly constructed to form multiple polygons of the global flood control limit water level, and the largest area polygon is taken to perform intersection judgment with the reservoir water surface seed point. If they intersect, the inner ring of the largest area polygon is deleted and recorded as the main flood control limit water level patch; if the largest area polygon does not intersect with the reservoir water surface seed point, the inner ring of the second largest area polygon is deleted and recorded as the main flood control limit water level patch; the flood control limit water level contour line dataset is directly constructed to form the reservoir flood control limit water level polygon, and the main flood control limit water level patch is used for erasing analysis. The resulting polygons are first merged and then scattered, and then traversed. If the area is smaller than the minimum water area, the next traversal is performed; otherwise, it is added to the secondary flood control limit water level patch dataset; S33: The inner range boundary and the flood control high water level contour line dataset are uniformly constructed to form multiple polygons of the global flood control high water level. The polygon with the largest area is taken to perform intersection judgment with the reservoir water surface seed point. If they intersect, the inner ring of the polygon with the largest area is deleted and recorded as the main flood control high water level patch. If the polygon with the largest area does not intersect with the reservoir water surface seed point, the inner ring of the polygon with the second largest area is deleted and recorded as the main flood control high water level patch. The flood control high water level contour line dataset is directly constructed to form the reservoir flood control high water level polygon. The main flood control high water level patch is used for erasing analysis. The resulting polygons are first merged and then broken up, and then traversed. If the area is smaller than the minimum water area, it enters the next traversal, otherwise it is added to the secondary flood control high water level patch dataset.

4. The method according to claim 1, wherein Traverse the secondary flood control high water level patch dataset and the secondary flood control limit water level patch dataset, and through spatial inclusion relationship query and judgment processing, form a dammed water area patch object set, including: S41: traverse the secondary flood control high water level patch dataset, obtain the secondary flood control high water level patch, use its polygon as the search range and the spatial inclusion relationship as the search condition, query the secondary flood control limit water level patch dataset, and record the query result as the associated secondary flood control limit water level patch; if the associated secondary flood control limit water level patch is not empty, add a first label to it and save it, and take its polygon as the dammed water area polygon; if the query result is empty, then the secondary flood control high water level patch is recorded as the dammed water area polygon; construct a first dammed water area patch object that includes the dammed water area polygon, the secondary flood control high water level patch, and the associated secondary flood control limit water level patch, and add it to the dammed water area patch object set; S42: Traverse the secondary flood control limit water level map dataset, obtain the secondary flood control limit water level map, and judge its label. If it is the first label, enter the next traversal; if not, the polygon of the secondary flood control limit water level map is recorded as the dammed water area polygon, which is recorded as the associated secondary flood control limit water level map; construct a second dammed water area map object containing the dammed water area polygon and the associated secondary flood control limit water level map, and add it to the dammed water area map object set.

5. The method according to claim 1, wherein Traverse the dammed water area patch object set, calculate the closest point and minimum distance between it and the main flood control limit water level patch, and form a dammed branch object after using the maximum dam width judgment and the minimum acute angle constraint and add it to the dammed branch object set. At the same time, mark the water area patch object, including: S51: Traverse the dammed water area patch object set, obtain the dammed water area patch object, take the dammed water area polygon as the target polygon, calculate the closest point and minimum distance between the target polygon and the main flood control limit water level patch; if the minimum distance is greater than or equal to n times the maximum width of the dam, directly enter the next traversal; S52: If the minimum distance is less than n times the maximum width of the dam, calculate the neighboring points of the nearest point on the target polygon; construct a straight line with the nearest point and the neighboring points, take points on the straight line according to the target resolution, and obtain the elevation value of the point on the digital elevation model. If the maximum elevation value appears at the nearest point or the neighboring point, enter the next traversal; record the average of the elevation value of the nearest point and the elevation value of the neighboring point as the elevation of the bottom of the dam; with the neighboring point as the center, take points at equal intervals on the boundary of the target polygon, calculate the distance to the main flood control limit water level patch, and intercept the boundary of the target polygon with two points whose distance is equal to the maximum width of the dam, which is counted as the first inner boundary; with the nearest point as the center, take points at equal intervals on the boundary of the main flood control limit water level patch, calculate the distance to the target polygon, and intercept the boundary of the main flood control limit water level patch with two points whose distance is equal to the maximum width of the dam, which is counted as the first outer boundary; S53: Construct a polygon based on the first inner boundary and the first outer boundary, and use the minimum acute angle constraint to process the spikes of the polygon. The processed polygon is recorded as the dam branch polygon, and the average distance between the first inner boundary and the first outer boundary is calculated and recorded as the average width of the dam body. The area of ​​the dam branch polygon is divided by the average width of the dam body and recorded as the average length of the dam body. Create a dam branch object with the dam branch polygon, the dam bottom elevation, the average width of the dam body, the average length of the dam body, and the dam water area map object, and add it to the dam branch object set; at the same time, add a second label to the dam water area map object and save it.

6. The method according to claim 5, characterized in that Traversing the dammed water area patch object set, determining the water area patch object mark, respectively calculating the closest point and minimum distance between the water area patch object set and the dammed water area patch object set, and forming a dammed branch object and adding it to the dammed branch object set after using the dammed water area patch object set to determine the maximum width and the minimum acute angle constraint, including: S61: traverse the dammed water area patch object set, obtain the dammed water area patch object, determine the water area patch object label, if it is the second label, then enter the next traversal; if not, take the dammed water area polygon as the target polygon; S62: The target polygon uses n times the maximum width of the dam as the search radius to query the dammed water area map object set. If the query result is empty, enter the next traversal; if the query result is not empty, the dammed water area polygon to which the queried dammed water area map object belongs is recorded as the reference polygon, and the nearest point and the minimum distance between the target polygon and the reference polygon are calculated; the nearest point of the nearest point on the target polygon is calculated, and a straight line is constructed with the nearest point and the nearest point. A point is taken on the straight line according to the target resolution to obtain the elevation value of the point on the digital elevation model. If the maximum elevation value is If it appears at the nearest point or the nearest neighbor point, the next traversal will begin; the average of the elevation values ​​of the nearest point and the nearest neighbor point is recorded as the dam bottom elevation; with the nearest neighbor point as the center, points are taken at equal intervals on the boundary of the target polygon, and the distance to the reference polygon is calculated. The boundary of the target polygon is intercepted by two points whose distance is equal to the maximum width of the dam, and this is counted as the second inner boundary; with the nearest point as the center, points are taken at equal intervals on the boundary of the reference polygon, and the distance to the target polygon is calculated. The boundary of the reference polygon is intercepted by two points whose distance is equal to the maximum width of the dam, and this is counted as the second outer boundary; S63: Construct a polygon based on the second inner boundary and the second outer boundary, and use the minimum acute angle constraint to process the spikes of the polygon. The processed polygon is recorded as the dam-building branch polygon. The average distance between the second inner boundary and the second outer boundary is calculated and recorded as the average width of the dam body. The area of ​​the dam-building branch polygon is divided by the average width of the dam body to obtain the average length of the dam body. Create a dam-building branch object with the dam-building branch polygon, the dam bottom elevation, the average width of the dam body, the average length of the dam body, and the dam water area map object, and add it to the dam-building branch object set.

7. The method according to claim 1, characterized in that Traverse the damming and intercepting branch object set and calculate the dam crest plane area, dam crest average elevation, damming and intercepting branch loss storage capacity, and damming and intercepting branch impact storage capacity based on slope data, including: S71: Traverse the dam and branch object set to obtain the dam and branch objects, clip the slope data according to the dam and branch polygons of the dam and branch objects, and record the result as the dam and branch slope data. Reclassify the data according to whether the slope is greater than the flat land standard, and construct a polygon collection for the data with a slope less than the flat land standard. Traverse the polygon collection to calculate the average elevation within the polygon. If the average elevation is less than the average of the flood control high water level and the flood control limit water level, delete the polygon. Merge the traversed polygon collection, and record the resulting polygon as the dam crest plane polygon, whose area is the dam crest plane area. Calculate the average of the average elevations of the polygon collection, and record the result as the dam crest average elevation. S72: The dam crest polygon is used as the top surface of the pyramid, the dam-barrier polygon is used as the bottom surface of the pyramid, and the dam crest average elevation minus the dam bottom elevation is used as the pyramid height. The storage capacity loss due to dam-barrier is calculated according to the pyramid volume formula. S73: Based on the dammed water area patch object to which the dammed branch object belongs, if the secondary flood control high water level patch is not empty, its polygon is recorded as the dammed water area polygon; if it is empty, the polygon of the associated secondary flood control limit water level patch is recorded as the dammed water area polygon; with the dammed water area polygon as the boundary, the digital elevation model data is clipped and its average elevation value is calculated; the flood control high water level minus the average elevation value is recorded as the average height of the dammed water area patch, and the reservoir capacity affected by the dammed branch is calculated according to the area of ​​the dammed water area polygon multiplied by the average height of the dammed water area patch.

8. A device for extracting reservoir damming and branching information based on a digital elevation model, characterized in that: include: The acquisition module is used to obtain the digital elevation model of the reservoir, flood control limit water level, flood control high water level, target resolution, maximum dam width, minimum water area, minimum acute angle and reservoir surface seed points; a preprocessing and extraction module, configured to preprocess the digital elevation model according to the flood control limit water level, the flood control high water level, and the target resolution, and extract corresponding water level contour line datasets, range boundaries, and slope data based on the preprocessed digital elevation model; A patch dataset generation module is used to classify the contour line dataset, and generate different types of patch datasets by using the reservoir water surface seed points and the minimum water area and performing faceting and spatial relationship operations, namely, a main flood control limit water level patch dataset, a secondary flood control limit water level patch dataset, and a secondary flood control high water level patch dataset; A water area patch object set generation module is used to traverse the secondary flood control high water level patch dataset and the secondary flood control limit water level patch dataset, and form a damming water area patch object set through spatial inclusion relationship query and judgment processing; A first barrier object set generation module is configured to traverse the dammed water area patch object set, calculate the closest point and minimum distance between the dammed water area patch and the main flood control limit water level patch, and generate a dammed barrier object after using the maximum dam width judgment and the minimum acute angle constraint, and add the dammed barrier object to the dammed barrier object set, while marking the water area patch object. A second barrier object set generation module is configured to traverse the dammed water area patch object set, determine the water area patch object mark, calculate the closest point and minimum distance between the water area patch object and the dammed water area patch object set, and generate a dammed barrier object using the maximum dam width determination and minimum acute angle constraint, and add the dammed barrier object to the dammed barrier object set; The calculation module is used to traverse the damming and intercepting object set, and calculate the dam top plane area, the dam top average elevation, the lost storage capacity due to damming and intercepting, and the storage capacity affected by damming and intercepting in combination with the slope data.

9. An electronic device, characterized in that: include: one or more processors; a memory for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having computer instructions stored thereon, characterized in that: When the instruction is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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