CN117726764A - Shallow lake topography and water level storage relation construction method and system considering high-intensity human activity influence - Google Patents
Shallow lake topography and water level storage relation construction method and system considering high-intensity human activity influence Download PDFInfo
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Abstract
The invention provides a shallow lake topography and water level storage relation construction method and system considering high-intensity human activity influence, comprising the following steps: acquiring multi-time phase satellite images of a lake region, identifying the shape of ground objects, and dividing the ground objects of the lake region into natural lake basins, reclamation beach lands, embankments and river channels; selecting a proper water index and a threshold value thereof, and identifying a water surface area; and combining the water level of the current period of the remote sensing image, and carrying out contour fine construction by taking the contour of the water surface area of the current period as a contour range under a certain elevation. The invention takes satellite remote sensing information extraction as a main means, integrates the existing survey data, unmanned aerial vehicle height measurement and unmanned ship depth measurement data to supplement and evidence, reconstructs the elevation of the lake bottom, and realizes the fine construction of the water level and storage relation.
Description
Technical Field
The invention relates to the technical field of lake research, in particular to a method and a system for constructing a relationship between shallow lake topography and water level storage taking high-intensity human activity influence into consideration.
Background
Lakes are important regulation units in hydrologic cycle, have important roles in regulating runoff, reducing flood, conserving water sources and the like, are also key ecological carriers, and play an irreplaceable role in maintaining ecological environment and species diversity.
The eastern region of China is densely populated, a plurality of shallow lakes are distributed in the region, precious resources are provided for life production of people, and people can change the shape of the lakes while carrying out production development activities by utilizing the lakes. Under the influence of high-intensity human activities, the lakes no longer have complete natural appearances, but form complex landforms of natural lake basins, beach lands, surrounding ridges in lakes and ditches in lakes, wherein the beach lands are often divided and surrounded by the surrounding ridges and used for fishery cultivation or agricultural planting in a dead water period. Under the condition that the water level of the lake naturally drops in the dry season, the ground object units have obvious influence on the communication pattern of the water surface of the lake, so that the river-lake two-phase change landscape of which the high water is the lake and the low water forms the river is generated, and near-artificial landscapes of which the lake surface, the field blocks in the lake, the pond, the ditch and the canal are staggered can be generated in a part of lake areas with obvious human activity traces. The dynamic change of the landscape pattern of the lake influences the reserves of the lake water, changes the hydrologic situation of the lake, and has important influence on water resources, shipping and ecology.
The lake topography is basic data for revealing the lake water flow morphology, hydrologic situation and sediment accumulation law, provides boundary conditions for lake water and sediment simulation, is an important base plate for constructing a digital twin lake, and has important significance for guiding flood prevention and drought resistance, water resource development and utilization and water ecological environment protection. Part of lakes have special lake bottom elevation survey data, but because of manual measurement, the density of sampling points is limited, and the topography change of the lakes is difficult to accurately reflect; the unmanned aerial vehicle height measurement is a new technology which is increasingly widely applied, but is limited by range and sampling cost, and can only reflect the topography of a limited area. The satellite remote sensing can obtain the ground feature information in a large scale, the return visit period is short, the multi-time sequence image of the ground feature landscape can be obtained, and for lakes, the image features under different water level conditions are reflected, so that a new view angle is opened for finely and quantitatively analyzing the topography and the landform of the lake. Some researches are applied to inversion researches of lakes, reservoir terrains and water storage capacity, and related laws are revealed. However, most of the researches reflect the topography distribution of the lake and reservoir in a larger space scale, the resolution is usually more than 100m, and the achievements mainly provide basic data for hydrological weather and hydrological geographic researches on a large space-time scale; for shallow lakes with obvious human activity intensity, the coarse resolution is difficult to characterize fine terrains and landforms, so that the guiding effect of the shallow lakes on the relevant research and management of the lakes is limited, and more researches are needed in the aspect.
Disclosure of Invention
The invention aims to provide a shallow lake topography and water level storage relation construction method and system considering high-intensity human activity influence, which adopts a high-resolution multispectral satellite remote sensing image, combines water level data and field investigation data, and provides powerful data support for constructing high-precision shallow lake topography.
In order to achieve the above purpose, the present invention proposes the following technical scheme:
in a first aspect, a method for constructing a relationship between topography and water level storage in a shallow lake considering the influence of high-intensity human activities is provided, including:
acquiring remote sensing images of a plurality of time phases of a lake region, identifying the ground object of the lake region and drawing a vector boundary; the remote sensing image is a high-resolution multispectral remote sensing image, any one of the remote sensing images comprises a complete lake surface area, the ground object of the lake area comprises a natural lake basin and an unnatural lake basin, and the unnatural lake basin comprises a reclamation beach, a embankment and a river channel;
identifying the water surface area of the remote sensing image at each time phase by adopting a water index, and determining the contour lines of the natural lake surface area and the natural lake basin;
determining elevation values of land features of each lake region of the unnatural lake basin according to the remote sensing images, the on-site investigation data and the water surface region identification result;
Analyzing and obtaining elevation raster data of a lake area under a set resolution according to the remote sensing images, the natural lake basin contour lines and the elevation values of the ground features of each lake area of the unnatural lake basin at each time sequence;
and constructing a lake water level storage relationship according to the elevation raster data.
Further, the process of obtaining remote sensing images of a plurality of time phases of the lake region, identifying the ground object of the lake region and drawing the vector boundary includes:
acquiring a plurality of remote sensing images corresponding to a lake area in a selected time period and remote sensing RGB images of the remote sensing images, wherein the selection standard of the selected time period is a time period comprising typical water level change characteristics;
determining a remote sensing RGB image as a reference base map, carrying out pixel point analysis on the reference base map, identifying the ground objects of a lake region and classifying the ground objects into natural lake basins, reclamation beach lands, river channels and embankments;
the boundary of each lake region feature is drawn and stored as a vector file.
Further, the process of identifying the water surface area of the remote sensing image in each time phase by adopting the water index and determining the contour line of the natural lake surface area and the natural lake basin comprises the following steps:
calculating a normalized water index and an improved normalized water index corresponding to the water level of each remote sensing image;
Judging the theoretical water surface area of each remote sensing image according to each calculated normalized water body index and improved normalized water body index;
correcting and obtaining a natural lake surface area according to the theoretical water surface area of the remote sensing image and the corresponding remote sensing RGB image; the method for correcting and obtaining the natural lake surface area is to select the theoretical water surface area with the highest overlap ratio and space polymerization degree with the natural lake basin area as the natural lake surface area;
extracting boundary lines of the natural lake surface area as contour lines of the natural lake basin; wherein the boundary line of the natural lake surface area comprises the boundary line of the water surface area of the natural lake surface area and the boundary line of the open beach sand in the dry period of the natural lake surface area.
Further, the process of determining the elevation value of each lake region feature of the unnatural lake basin according to the remote sensing image, the field investigation data and the water surface region recognition result comprises the following steps:
plotting the boundaries of the ground objects of each lake area of the unnatural lake basin into any remote sensing image, and marking the boundaries as grids with different colors;
determining elevation values of the river channel according to the land survey data, and determining elevation values of the reclamation beach and the embankment by adopting normalized water indexes of the remote sensing images under different water levels; the process for determining the elevation values of the reclamation beach and the embankment by adopting the normalized water indexes of the remote sensing images under different water levels comprises the following steps: counting water level values corresponding to the remote sensing images, and sequencing the remote sensing images from low to high according to the water level values; calculating normalized water indexes of two adjacent remote sensing images according to the sequence from low water level values to high water level values, and judging whether the water surface area coverage condition corresponding to the normalized water indexes of the two remote sensing images meets the condition that the water surface area with low water level values does not cover the reclamation beach or the embankment, and the water surface area with high water level values covers the reclamation beach or the embankment; if the water level of the remote sensing image is met, calculating the elevation value of the reclamation beach or the embankment as the average value of the water levels of the two remote sensing images; if not, sequentially calculating the normalized water indexes of the two adjacent remote sensing images until the condition is met.
Further, the process of analyzing and obtaining elevation grid data of the lake area under the set resolution according to the remote sensing images, the elevation lines of the natural lake basin and the ground object of each lake area of the non-natural lake basin at each time sequence is as follows:
dividing the lake region features into a plurality of feature analysis units, wherein the feature analysis units comprise a natural lake basin water level change region, a beach-exposing sand continent region, a reclamation beach region, a river channel and a embankment;
determining natural lake basin contour lines corresponding to different water levels according to the remote sensing images at each time sequence, and respectively interpolating the natural lake basin contour lines to obtain elevation raster data of the natural lake basin water level change area and the exposed beach sand area;
sampling to obtain elevation raster data of the reclamation beach, the river channel and the embankment according to elevation values of land features of each lake region of the unnatural lake basin;
and integrating elevation raster data of the natural lake basin water level change area and the exposed beach sand area and elevation raster data of the reclamation beach, the river channel and the embankment, thereby obtaining the elevation raster data of the lake area under the set resolution.
Further, the ground object analysis unit further comprises an underwater area positioned at the bottom of the natural lake basin; the method for acquiring the elevation raster data of the underwater region is obtained by extrapolation estimation according to the field reconnaissance data.
Further, the method further comprises the following steps: judging whether the lake area in any one of the remote sensing images is complete, and when the lake area in the remote sensing image is incomplete, cutting and splicing a plurality of remote sensing images shot in sequence to obtain the remote sensing image containing the complete lake area.
Further, the process of constructing the lake water level storage relationship according to the elevation raster data is as follows: according to different water level values, the depth from the water surface to the lake bottom is calculated, the grid area is taken as the calculation unit area, the lake storage under different water levels is obtained by adding the calculation unit areas one by one, and accordingly, the lake water level-storage relation is constructed and a relation curve is drawn.
In a second aspect, a shallow lake topography and water level storage relationship construction system considering the influence of high-intensity human activities is provided, which comprises:
the acquisition and identification module is used for acquiring remote sensing images of a plurality of time phases of the lake region, identifying the ground object of the lake region and drawing a vector boundary; the remote sensing image is a high-resolution multispectral remote sensing image, any one of the remote sensing images comprises a complete lake surface area, the ground object of the lake area comprises a natural lake basin and an unnatural lake basin, and the unnatural lake basin comprises a reclamation beach, a embankment and a river channel;
The first determining module is used for identifying the water surface area of the remote sensing image in each time phase by adopting a water index and determining the contour line of the natural lake surface area and the natural lake basin;
the second determining module is used for determining the elevation value of each lake region ground feature of the unnatural lake basin according to the remote sensing image, the field investigation data and the water surface region identification result;
the analysis acquisition module is used for analyzing and acquiring elevation grid data of the lake area under the set resolution according to the remote sensing images, the elevation lines of the natural lake basin and the elevation values of the ground objects of the lake areas of the non-natural lake basin at each time sequence;
and the construction module is used for constructing the lake water level storage relation according to the elevation raster data.
In a third aspect, an electronic device is presented, comprising a processor, a memory and a computer program stored in the memory, the computer program being configured to perform the above-described shallow lake topography and water level storage relationship construction method taking into account the influence of intensive human activity when run by the processor.
According to the technical scheme, the following beneficial effects are achieved:
1. the invention adopts the high-resolution multispectral remote sensing image to obtain the remote sensing image of the multi-temporal lake area, and combines the measured water level data to better describe the continuous change of the lake water surface, thereby increasing the contour density and improving the interpolation precision; the limitations of manual measurement of sampling area and sampling density are overcome.
2. The invention flexibly adopts a mode of combining remote sensing images and field measurement data, fully plays the advantages of different measurement means, and senses the lake terrain information in all directions.
3. The invention considers the terrain extension difference of different ground object units, divides the ground object units into different ground object analysis units, respectively interpolates the ground object units according to the characteristics of each unit, and objectively and reasonably considers the discontinuity of the lake region terrain under the influence of strong human activities. The obtained high-precision topography effectively reflects the fine topography and provides support for further revealing the morphological characteristics and change rules of lakes, high-precision hydrodynamic modeling, fine water resource management and water ecological environment protection.
It should be understood that all combinations of the foregoing concepts, as well as additional concepts described in more detail below, may be considered a part of the inventive subject matter of the present disclosure as long as such concepts are not mutually inconsistent.
The foregoing and other aspects, embodiments, and features of the present teachings will be more fully understood from the following description, taken together with the accompanying drawings. Other additional aspects of the invention, such as features and/or advantages of the exemplary embodiments, will be apparent from the description which follows, or may be learned by practice of the embodiments according to the teachings of the invention.
Drawings
The drawings are not intended to be drawn to scale with respect to true references. In the drawings, each identical or nearly identical component that is illustrated in various figures may be represented by a like numeral. For purposes of clarity, not every component may be labeled in every drawing. Embodiments of various aspects of the invention will now be described, by way of example, with reference to the accompanying drawings, in which:
FIG. 1 is a flow chart of a method for constructing the relationship between the topography and the water level storage of a shallow lake disclosed by the embodiment of the invention;
FIG. 2 (a) shows the selection range of the stone mortar lake region in the blue light, green light and near infrared band images according to the embodiment of the invention;
FIG. 2 (b) is the RGB image synthesized in FIG. 2 (a);
fig. 3 (a) is a first ridge identification chart of a local area of a stone mortar lake according to an embodiment of the invention;
fig. 3 (b) is a second ridge recognition chart of a local area of a stone mortar lake according to an embodiment of the invention;
FIG. 4 (a) is a flowchart showing the extraction of the water surface boundary and the exposed beach boundary of a lake area according to an embodiment of the present invention;
fig. 4 (b) is a second flowchart for extracting a water surface boundary and a beach exposure boundary of a lake area according to an embodiment of the present invention;
fig. 4 (c) is a flowchart of extracting a water surface boundary and a beach exposure boundary of a lake area according to an embodiment of the present invention;
FIG. 5 is a schematic illustration of an interpolation section of elevation below the lake surface in accordance with an embodiment of the present invention;
FIG. 6 is a 10m resolution elevation of a stone lake according to an embodiment of the present invention;
FIG. 7 is a graph showing the relationship between water level and energy storage of stone mortar and lake according to the embodiment of the invention;
FIG. 8 is a block diagram of a system for constructing the relationship between the topography and the water level storage of a shallow lake according to the embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. It will be apparent that the described embodiments are some, but not all, embodiments of the invention. All other embodiments, which can be made by a person skilled in the art without creative efforts, based on the described embodiments of the present invention fall within the protection scope of the present invention. Unless defined otherwise, technical or scientific terms used herein should be given the ordinary meaning as understood by one of ordinary skill in the art to which this invention belongs.
The terms "first," "second," and the like in the description and in the claims, are not used for any order, quantity, or importance, but are used for distinguishing between different elements. Also, unless the context clearly indicates otherwise, singular forms "a," "an," or "the" and similar terms do not denote a limitation of quantity, but rather denote the presence of at least one. The terms "comprises," "comprising," or the like are intended to cover a feature, integer, step, operation, element, and/or component recited as being present in the element or article that "comprises" or "comprising" does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. "up", "down", "left", "right" and the like are used only to indicate a relative positional relationship, and when the absolute position of the object to be described is changed, the relative positional relationship may be changed accordingly.
Shallow lakes with obvious human activity traces cannot be characterized with fine terrain and landform features at a coarser resolution based on the prior art, and guidance can not be provided for relevant research and management of lakes; therefore, the invention aims to provide a method and a system for constructing a shallow lake topography and water level storage relation by considering the influence of high-intensity human activities, which are used for carrying out lake region ground object analysis by utilizing high-resolution multispectral satellite remote sensing images and field investigation data, and constructing high-precision lake topography by respectively acquiring elevation grid data of a natural lake basin and an unnatural lake basin so as to obtain the lake water level storage relation.
Referring to fig. 1, the method for constructing the relationship between the topography and the water level storage of the shallow lake considering the influence of high-intensity human activities disclosed by the embodiment of the invention comprises the following steps:
s1, acquiring remote sensing images of a plurality of time phases of a lake region, identifying the ground object of the lake region and drawing a vector boundary; the remote sensing image is a high-resolution multispectral remote sensing image, any one of the remote sensing images comprises a complete lake surface area, the ground object of the lake area comprises a natural lake basin and an unnatural lake basin, and the unnatural lake basin comprises a reclamation beach, a embankment and a river channel; in order to save the workload, the acquired image is usually selected to acquire the remote sensing image for atmospheric correction and radiation calibration. In addition, it is also necessary to determine the integrity of the lake regions of the remote sensing images, that is, determine whether the lake region in any one of the remote sensing images is complete, and cut and splice a plurality of sequentially shot remote sensing images when the lake region in the remote sensing image is incomplete, so as to obtain the remote sensing image including the complete lake region.
Specifically, the process of identifying the ground object of the lake region and depicting the vector boundary comprises the following steps: acquiring a plurality of remote sensing images corresponding to a lake area in a selected time period and remote sensing RGB images of the remote sensing images, wherein the selection standard of the selected time period is a time period comprising typical water level change characteristics of a water body, and if the selected time period is required to contain a lake water-rich period, a water-free period and a constant water level state; determining a remote sensing RGB image as a reference base map, carrying out pixel point analysis on the reference base map, identifying the ground objects of a lake region and classifying the ground objects into natural lake basins, reclamation beach lands, river channels and embankments; the boundary of each lake region feature is drawn and stored as a vector file. The remote sensing RGB image can improve the visual effect and assist in unfolding analysis work.
S2, identifying the water surface area of the remote sensing image in each time phase by adopting a water index, and determining the contour lines of the natural lake surface area and the natural lake basin;
specifically, firstly calculating a normalized water index NDWI and an improved normalized water index MNDWI corresponding to the water level of each remote sensing image; the calculation formula is as follows:
NDWI= (Green-NIR)/( Green+NIR)；
MNDWI= (Green- MIR)/( Green+ MIR)；
wherein Green, NIR, MIR is green light wave band, near infrared wave band, short wave infrared wave band;
and then, judging the theoretical water surface area of each remote sensing image according to each calculated normalized water body index and improved normalized water body index. Then, correcting and obtaining a natural lake surface area according to the theoretical water surface area of the remote sensing image and the corresponding remote sensing RGB image; the method for correcting and obtaining the natural lake surface area is to select the theoretical water surface area with the highest overlap ratio and space polymerization degree with the natural lake basin area as the natural lake surface area; in an embodiment, the process is primarily determined by visual means. Finally, extracting boundary lines of the natural lake surface area as contour lines of the natural lake basin; wherein the boundary line of the natural lake surface area comprises the boundary line of the water surface area of the natural lake surface area and the boundary line of the open beach sand in the dry period of the natural lake surface area.
S3, determining elevation values of the ground features of each lake area of the unnatural lake basin according to the remote sensing images, the real-field investigation data and the water surface area identification result;
when the method is implemented, firstly, plotting the boundaries of the ground objects of each lake region of the unnatural lake basin into grids with different colors for data recording;
determining elevation values of the river channel according to the land survey data, and determining elevation values of the reclamation beach and the embankment by adopting normalized water indexes of the remote sensing images under different water levels; the process for determining the elevation values of the reclamation beach and the embankment by adopting the normalized water indexes of the remote sensing images under different water levels comprises the following steps: counting water level values corresponding to the remote sensing images, and sequencing the remote sensing images from low to high according to the water level values; calculating normalized water indexes of two adjacent remote sensing images according to the sequence from low water level values to high water level values, and judging whether the water surface area coverage condition corresponding to the normalized water indexes of the two remote sensing images meets the condition that the water surface area with low water level values does not cover the reclamation beach or the embankment, and the water surface area with high water level values covers the reclamation beach or the embankment; if the water level of the remote sensing image is met, calculating the elevation value of the reclamation beach or the embankment as the average value of the water levels of the two remote sensing images; if not, sequentially calculating the normalized water indexes of the two adjacent remote sensing images until the condition is met.
S4, analyzing and obtaining elevation grid data of the lake area under the set resolution according to the remote sensing images, the natural lake basin contour lines and the elevation values of the ground features of the lake areas of the unnatural lake basin at each time sequence;
based on the difference of artificial activities and interference between natural lake basin and non-natural lake basin areas, the terrain extension modes have great difference, and the terrain extension modes cannot be placed in the same interpolation area to calculate the elevation. Therefore, the acquisition of elevation grid data of the lake area under the set resolution is realized by dividing the area analysis units, respectively acquiring the elevation grid data of different ground objects, and then integrating. The method specifically comprises the following steps: dividing the lake region features into a plurality of feature analysis units, wherein the feature analysis units comprise a natural lake basin water level change region, a beach-exposing sand continent region, a reclamation beach region, a river channel and a embankment; determining natural lake basin contour lines corresponding to different water levels according to the remote sensing images at each time sequence, and respectively interpolating the natural lake basin contour lines to obtain elevation raster data of the natural lake basin water level change area and the exposed beach sand area; sampling to obtain elevation raster data of the reclamation beach, the river channel and the embankment according to elevation values of land features of each lake region of the unnatural lake basin; and integrating elevation raster data of the natural lake basin water level change area and the exposed beach sand area and elevation raster data of the reclamation beach, the river channel and the embankment, thereby obtaining the elevation raster data of the lake area under the set resolution.
Optionally, the ground object analysis unit further includes an underwater area located at the bottom of the natural lake basin, for example, a part of the lake water bottom may still be navigated by a ship in order to facilitate the dead water period, and a river ditch is arranged at the bottom of the lake basin, which also needs to acquire high Cheng Geshan data; in the implementation, the method for acquiring the elevation raster data of the underwater region is obtained by extrapolation estimation according to the field investigation data.
S5, constructing a lake water level energy storage relation according to the elevation raster data; specifically, according to different water level values, the depth from the water surface to the lake bottom is calculated, the grid area is taken as the area of a calculation unit, the lake storage under different water levels is obtained by adding the calculated areas one by one, and accordingly, a lake water level-storage relation is constructed and a relation curve is drawn.
The invention discloses a method and a system for constructing the relationship between the topography and the water level storage of a shallow lake, which considers the influence of high-intensity human activities, by combining the specific embodiments shown in the drawings.
Example 1
The embodiment of the invention uses the stone mortar lake as a research area, and illustrates the application of the steps in the aspect of extracting the high-precision topography of the stone mortar lake and constructing the precise water level-storage relation.
The stone mortar lake is a river-passing lake at the boundary of the Suwang river at the downstream of the Yangtze river, the inlet is a diversion river channel and a pond ditch of the Yangtze river, the outlet is a three-branch river, and the stone mortar lake is converged into the Yangtze river through the Guxi river. Area of lake water surface 214.7km 2 Bus area 969km 2 Mainly receives the water coming from Yangjiang river and catchment area, and the river water can flow back into the lake during the high water level of Yangtze river. Stone mortar lake is a natural huff and puff lake, the water level is greatly influenced by the water coming from Yangtze river and the hydrological weather in the catchment area, and a large water level difference is often generated in the annual year. In the period of dead water, the beaches are exposed, a large number of embankments left by the reclamation development activity of the 20 th century appear, channels from the pool river to the natural bridge river, ditches and ponds which are convenient for water taking and excavation along the line are arranged in the lake area, and the land features are combined in a staggered manner to form a natural artificial landscape mixed lake-beach-ridge-ditch composite landscape.
Step 1: acquiring remote sensing images of a plurality of time phases of a lake region, identifying the ground object of the lake region and drawing a vector boundary
Sentinel-2 satellite images at 10m-20m resolution were selected as the data source. Considering lake topography siltation change, the remote sensing image is not suitable for a long time to cross over years, and according to general experience, the remote sensing image within 5 years can be close to actual conditions, so 2019-2023 years are selected as downloading time periods of Sentinel-2 satellite images. And 2019 autumn and winter, 2022 autumn and winter and 2023 early spring are typical dead water periods, and 2020 summer is typical flood period, so that remote sensing images of the years can cover different water level conditions, and the topography analysis is facilitated. 78 remote sensing images of all the Setinel-2 passing stone mortar lake areas in 2019-2023 are taken as a total, and L2A-level remote sensing image data subjected to atmospheric correction and radiometric calibration are selected for downloading. All areas of the stone mortar lake are in the same image, so that splicing operation is not needed. As the visible light image, the infrared image and the water index distribution diagram are needed to be used in the later analysis, blue light, green light, red light and near infrared band images (B2, B3, B4 and B8) with the resolution of 10m and green light and short wave infrared band images (B3 and B11) with the resolution of 20m are selected, a proper lake range is framed, and batch cropping operation is carried out on the remote sensing images. In order to improve the visual effect and help the judgment and analysis, firstly, red, green and blue wave bands are combined into a true color image, the change of the stone mortar lake water surface area is approximately intuitively known, and the image source is Sentinel-2 remote sensing data of 2019.4.17, such as a wave band image shown in fig. 2 (a) and a remote sensing RGB image shown in fig. 2 (b) after synthesis.
And selecting a remote sensing RGB image of a corresponding period with a water level lower than 5 m (Wu Songgao Cheng Jimian, the same applies below) and a weather fine cloudless period as a reference base map for ground object division. Through comprehensive comparison, the water level of day 31 of 2023 is 4.85 meters, the condition of extremely low water level value is achieved, the weather of the day is fine, the RGB image is clear, and the landscapes of the center of the lake basin and the ground in the lake region can be well judged and read, so that the landscapes are selected as base images. And analyzing the pixel points of the remote sensing image by visual interpretation, classifying the types of the ground objects in the image into three typical ground object categories, namely a natural lake basin, a reclamation beach and a water storage river channel, and outlining the boundaries of the three ground object categories as vector files for storage. Wherein, a plurality of embankments are distributed on the reclamation beach, and the method is also taken as a typical object for analysis. Because the number of the embankments is numerous, the manual drawing workload is extremely high, and the definition of edges in an image recognition algorithm, namely, the place where the gray level difference between a target pixel and the background is obvious, is met in consideration of obvious morphological contrast between the embankments and the surrounding ground objects, namely, the position of a local maximum value of a first derivative of a certain point, and whether the pixel point is positioned at the edges can be judged by calculating the derivative value of the pixel point. The Canny edge detection operator is adopted here, and the result is shown in fig. 3 (a) and 3 (b), so that the Canny edge detection can well extract the profile of the bank.
Step 2: determining the contour line of the natural lake surface area and the natural lake basin
And determining the natural lake basin area outside the artificial activity trace according to the vector diagram representing the ground object unit. Considering the influence of various factors such as water color, vegetation, mud flat and the like, the method adopts NDWI and MNDWI to extract the water surface area simultaneously. NDWI can identify the edge details of the water body finely, and is very suitable for the shoal water body; and MNCWI can more clearly show the water surface area, thereby improving the recognition efficiency. According to the calculation results of NDWI and MNCWI, the corresponding judgment threshold is set, the NDWI threshold of the stone mortar lake area is generally-0.04 or-0.05, the MNCWI threshold is generally-0.20, the water surface area can be judged if the threshold is larger than the threshold, and the water surface area is determined by combining the spatial distribution of the NDWI and the MNCWI and the visual interpretation of an actual RGB image. And extracting water surface areas under water levels corresponding to dates of different remote sensing images by using the remote sensing images in each period as input materials, and selecting the water surface area with the distribution most coincident with the natural lake basin area and the highest space aggregation degree, thereby determining the water surface area as the water surface area of the lake area. And extracting boundary lines of the water surface area of the lake area, and determining the boundary lines as the demarcation basis of the contour lines of the natural lake basin. In the period of low water level, the lake basin area has exposed beach, and boundary lines are extracted for the lake basin area as shown in fig. 4 (a) -4 (c); the initial state is shown in fig. 4 (a), and the final state is shown in the area enclosed in the middle of the lake in fig. 4 (c).
Step 3: determining elevation values of features of each lake region of an unnatural lake basin
According to the analysis of the step 1, the types of the ground objects in the lake area comprise a lake basin, a reclamation beach, a river channel and a embankment; the reclamation beach, the river channel and the embankment have obvious human activity marks, and the topography cannot be calculated according to a natural contour interpolation method. The river channel area adopts a ground object vector plotting result, the reclamation beach area and the embankment adopt an edge detection result, and the result is marked as grids with different colors.
The river channel region is formed by manually excavating and dredging, and is mainly used for guaranteeing nearby water taking irrigation and navigation of small and medium ships, and the elevation of the river channel region is below the lowest water level of a lake and cannot be judged through the water surface covering condition. For such features, recent field measurement data is used to determine elevation values.
The reclamation beach and the embankment are usually above the lowest water level of the lake and are completely submerged when reaching higher water level, and the elevation is judged by adopting iterative comparison of the submerged conditions of high and low water level remote sensing images. The method comprises counting water levels corresponding to dates of remote sensing images, sorting the remote sensing images according to water level values from low to high, and collecting two images as a group, wherein the water levels are H low And H high Calculating the NDWI of the two images, and if the reclamation beach (bank) is not covered by the NDWI of the 2 nd image, indicating the elevation H shoal (H dike ) Greater than H high Selecting 3 rd and 4 th images to continue comparison, and continuously advancing until H low <H shoal (H dike )<H high . Because the long time sequence image can cover most water level conditions, H high And H low The average value of the elevation of the land is relatively close to the elevation true value of the reclamation land (embankment) and is limited, so that the average value of the two can be taken as the elevation of the reclamation land (embankment), namely:
。
step 4: obtaining elevation raster data of lake region under set resolution
The natural lake basin and the non-natural lake basin areas are treated as different analysis units because of different terrain spreading forms due to the interference difference of artificial activities. In accordance with the above analysis,
the lake region is divided into the following interpolation analysis units: the water level change area of the lake basin, the exposed beach sand area, the underwater area, the reclamation beach, the river channel and the embankment. Integrating the raster data together after interpolation of each analysis unit to obtain raster data of the whole lake area; the raster data resolution of this example takes 10 meters.
And (3) respectively interpolating different water level boundary lines and exposed beach sand in the lake basin area according to the analysis result of the step (2) to obtain elevation raster data of the lake basin area.
For a small part of lake basin below the lowest water level, adopting recent investigation data or actual measurement data, and utilizing limited measurement data to extrapolate and extend; the specific method comprises the steps of drawing a straight line which passes through a measuring point and is approximately orthogonal to a water level line, determining the position of the water level line and the intersection point of the water level line and the position of the measuring point, and carrying out linear interpolation extension on the trend of the intersection point of the water level line according to a Gao Cheng section schematic diagram of the measuring point. Since the bottom of the lake basin is generally U-shaped, the interpolation extension point is still spaced from the measurement point, as shown in FIG. 5. For interpolation analysis units such as river channels, reclamation beach lands, embankment banks and the like, the heights of the small units are determined through the analysis in the step 4, interpolation is not needed, and the small units are directly resampled to 10 m resolution. According to the analysis and calculation, the elevation grid data of the stone mortar lake area are produced as shown in figure 6.
Step 5: construction of water level-storage relation based on high-precision lake region topography
Through the steps of analysis, interpolation, correction and the like, high-precision terrain raster data of stone mortar lake areas are constructed, water levels in the past year are analyzed, low values are set to be 4.3m, high values are set to be 13.0m, each 10cm is a step length, water level values are sequentially increased, corresponding lake water demand is calculated, and accordingly a lake water level-storage relation is constructed and a curve is drawn, as shown in fig. 7.
In an embodiment of the present invention, there is also provided an electronic device including a processor, a memory, and a computer program stored in the memory, the computer program being configured to perform the above-described shallow lake topography and water level storage relationship construction method taking into account the influence of high intensity human activity when executed by the processor. Taking as an example an electronic device running on a computer, the electronic device may comprise one or more (only one is shown in the figure) processors (which may include, but are not limited to, processing means such as a microprocessor MCU or a programmable logic device FPGA), memory for storing data, and transmission means for communication functions. It will be appreciated by those skilled in the art that the arrangement is not limited to the structure of the electronic device described above.
The above-described programs may be run on a processor or may also be stored in memory (or referred to as computer-readable storage media), including both permanent and non-permanent, removable and non-removable media, and information storage may be implemented by any method or technique. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
These computer programs may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks and/or block diagram block or blocks, and corresponding steps may be implemented in different modules.
Embodiments of the present application provide an apparatus or system, referred to as shallow lake terrain versus water level energy storage construction, that takes into account the effects of high intensity human activity, comprising: the acquisition and identification module is used for acquiring remote sensing images of a plurality of time phases of the lake region, identifying the ground object of the lake region and drawing a vector boundary; the remote sensing image is a high-resolution multispectral remote sensing image, any one of the remote sensing images comprises a complete lake surface area, the ground object of the lake area comprises a natural lake basin and an unnatural lake basin, and the unnatural lake basin comprises a reclamation beach, a embankment and a river channel; the first determining module is used for identifying the water surface area of the remote sensing image in each time phase by adopting a water index and determining the contour line of the natural lake surface area and the natural lake basin; the second determining module is used for determining the elevation value of each lake region ground feature of the unnatural lake basin according to the remote sensing image, the field investigation data and the water surface region identification result; the analysis acquisition module is used for analyzing and acquiring elevation grid data of the lake area under the set resolution according to the remote sensing images, the elevation lines of the natural lake basin and the elevation values of the ground objects of the lake areas of the non-natural lake basin at each time sequence; and the construction module is used for constructing the lake water level storage relation according to the elevation raster data.
The system is used for realizing the functions of the shallow lake topography and water level storage relation construction method taking the influence of high-intensity human activities into consideration in the embodiment, and each module in the system corresponds to each step in the method, and has been described in the method, and will not be described in detail here.
For example, the process of acquiring the remote sensing images of a plurality of time phases of the lake region by the acquisition and identification module, identifying the ground object of the lake region and drawing the vector boundary comprises the following steps: acquiring a plurality of remote sensing images corresponding to a lake area in a selected time period and remote sensing RGB images of the remote sensing images, wherein the selection standard of the selected time period is a time period comprising typical water level change characteristics; determining a remote sensing RGB image as a reference base map, carrying out pixel point analysis on the reference base map, identifying the ground objects of a lake region and classifying the ground objects into natural lake basins, reclamation beach lands, river channels and embankments; the boundary of each lake region feature is drawn and stored as a vector file.
For another example, the first determination module determines a contour of the natural lake surface area and the natural lake basin, including: calculating a normalized water index and an improved normalized water index corresponding to the water level of each remote sensing image; judging the theoretical water surface area of each remote sensing image according to each calculated normalized water body index and improved normalized water body index; correcting and obtaining a natural lake surface area according to the theoretical water surface area of the remote sensing image and the corresponding remote sensing RGB image; the method for correcting and obtaining the natural lake surface area is to select the theoretical water surface area with the highest overlap ratio and space polymerization degree with the natural lake basin area as the natural lake surface area; extracting boundary lines of the natural lake surface area as contour lines of the natural lake basin; wherein the boundary line of the natural lake surface area comprises the boundary line of the water surface area of the natural lake surface area and the boundary line of the open beach sand in the dry period of the natural lake surface area.
For another example, the second determining module determines an elevation value of each lake region feature of the unnatural lake basin, including: plotting the boundaries of the ground objects of each lake area of the unnatural lake basin into any remote sensing image, and marking the boundaries as grids with different colors; determining elevation values of the river channel according to the land survey data, and determining elevation values of the reclamation beach and the embankment by adopting normalized water indexes of the remote sensing images under different water levels; the process for determining the elevation values of the reclamation beach and the embankment by adopting the normalized water indexes of the remote sensing images under different water levels comprises the following steps: counting water level values corresponding to the remote sensing images, and sequencing the remote sensing images from low to high according to the water level values; calculating normalized water indexes of two adjacent remote sensing images according to the sequence from low water level values to high water level values, and judging whether the water surface area coverage condition corresponding to the normalized water indexes of the two remote sensing images meets the condition that the water surface area with low water level values does not cover the reclamation beach or the embankment, and the water surface area with high water level values covers the reclamation beach or the embankment; if the water level of the remote sensing image is met, calculating the elevation value of the reclamation beach or the embankment as the average value of the water levels of the two remote sensing images; if not, sequentially calculating the normalized water indexes of the two adjacent remote sensing images until the condition is met.
For another example, the process of acquiring elevation raster data of the lake region under the set resolution by the analysis acquisition module includes: dividing the lake region features into a plurality of feature analysis units, wherein the feature analysis units comprise a natural lake basin water level change region, a beach-exposing sand continent region, a reclamation beach region, a river channel and a embankment; determining natural lake basin contour lines corresponding to different water levels according to the remote sensing images at each time sequence, and respectively interpolating the natural lake basin contour lines to obtain elevation raster data of the natural lake basin water level change area and the exposed beach sand area; sampling to obtain elevation raster data of the reclamation beach, the river channel and the embankment according to elevation values of land features of each lake region of the unnatural lake basin; and integrating elevation raster data of the natural lake basin water level change area and the exposed beach sand area and elevation raster data of the reclamation beach, the river channel and the embankment, thereby obtaining the elevation raster data of the lake area under the set resolution.
Optionally, the functions of acquiring the identification module further include: judging whether the lake area in any one of the remote sensing images is complete, and when the lake area in the remote sensing image is incomplete, cutting and splicing a plurality of remote sensing images shot in sequence to obtain the remote sensing image containing the complete lake area.
Optionally, the process of constructing the lake water level storage relationship by the construction module may be: according to different water level values, the depth from the water surface to the lake bottom is calculated, the grid area is taken as the calculation unit area, the lake storage under different water levels is obtained by adding the calculation unit areas one by one, and accordingly, the lake water level-storage relation is constructed and a relation curve is drawn.
The invention discloses a shallow lake topography and water level storage relation construction method and system considering high-intensity human activity influence, which are used for acquiring multi-time-phase lake region remote sensing images and combining measured water level data, identifying land features of natural lake basins and non-natural lake basins in a lake region, and knowing continuous change of the lake water surface under the condition of sensing fine topography information of the lake in all directions; the method considers the discontinuity of the topography of the lake region under the influence of strong human activities objectively and reasonably, and provides powerful data support for revealing the morphological characteristics and the change rule of the lake, modeling the hydrodynamic force with high precision, managing the water resources with refinement and protecting the water ecological environment.
While the invention has been described with reference to preferred embodiments, it is not intended to be limiting. Those skilled in the art will appreciate that various modifications and adaptations can be made without departing from the spirit and scope of the present invention. Accordingly, the scope of the invention is defined by the appended claims.
Claims (10)
1. A shallow lake topography and water level storage relation construction method considering the influence of high-intensity human activities is characterized by comprising the following steps:
acquiring remote sensing images of a plurality of time phases of a lake region, identifying the ground object of the lake region and drawing a vector boundary; the remote sensing image is a high-resolution multispectral remote sensing image, any one of the remote sensing images comprises a complete lake surface area, the ground object of the lake area comprises a natural lake basin and an unnatural lake basin, and the unnatural lake basin comprises a reclamation beach, a embankment and a river channel;
identifying the water surface area of the remote sensing image at each time phase by adopting a water index, and determining the contour lines of the natural lake surface area and the natural lake basin;
determining elevation values of land features of each lake region of the unnatural lake basin according to the remote sensing images, the on-site investigation data and the water surface region identification result;
analyzing and obtaining elevation raster data of a lake area under a set resolution according to the remote sensing images, the natural lake basin contour lines and the elevation values of the ground features of each lake area of the unnatural lake basin at each time sequence;
and constructing a lake water level storage relationship according to the elevation raster data.
2. The method for constructing the relationship between the topography and the water level storage of the shallow lake taking the influence of the high-intensity human activities into consideration as set forth in claim 1, wherein the process of acquiring the remote sensing images of the phases of the lake region, identifying the features of the lake region and describing the vector boundaries comprises the steps of:
Acquiring a plurality of remote sensing images corresponding to a lake area in a selected time period and remote sensing RGB images of the remote sensing images, wherein the selection standard of the selected time period is a time period comprising typical water level change characteristics;
determining a remote sensing RGB image as a reference base map, carrying out pixel point analysis on the reference base map, identifying the ground objects of a lake region and classifying the ground objects into natural lake basins, reclamation beach lands, river channels and embankments;
the boundary of each lake region feature is drawn and stored as a vector file.
3. The method for constructing the relationship between the topography and the water level storage of the shallow lake taking the influence of the high-intensity human activities into consideration as set forth in claim 1, wherein the process of identifying the water surface area of the remote sensing image in each time phase by using the water index and determining the contour lines of the natural lake surface area and the natural lake basin comprises the following steps:
calculating a normalized water index NDWI and an improved normalized water index MNDWI corresponding to the water level of each remote sensing image;
according to the calculated normalized water body indexes and the improved normalized water body indexes, judging the water surface area of each remote sensing image;
correcting and obtaining a natural lake surface area according to the theoretical water surface area of the remote sensing image and the corresponding remote sensing RGB image; the method for correcting and obtaining the natural lake surface area is to select the theoretical water surface area with the highest overlap ratio and space polymerization degree with the natural lake basin area as the natural lake surface area;
Extracting boundary lines of the natural lake surface area as contour lines of the natural lake basin; wherein the boundary line of the natural lake surface area comprises the boundary line of the water surface area of the natural lake surface area and the boundary line of the open beach sand in the dry period of the natural lake surface area.
4. The method for constructing a shallow lake topography and water level storage relationship taking into account high-intensity human activity effects according to claim 1, wherein the process of determining elevation values of land features of each lake region of an unnatural lake basin according to the remote sensing image, the in-field survey data and the water surface region identification result comprises the following steps:
plotting the boundaries of the ground objects of each lake area of the unnatural lake basin into any remote sensing image, and marking the boundaries as grids with different colors;
determining elevation values of the river channel according to the land survey data, and determining elevation values of the reclamation beach and the embankment by adopting normalized water indexes of the remote sensing images under different water levels; the process for determining the elevation values of the reclamation beach and the embankment by adopting the normalized water indexes of the remote sensing images under different water levels comprises the following steps: counting water level values corresponding to the remote sensing images, and sequencing the remote sensing images from low to high according to the water level values; calculating normalized water indexes of two adjacent remote sensing images according to the sequence from low water level values to high water level values, and judging whether the water surface area coverage condition corresponding to the normalized water indexes of the two remote sensing images meets the condition that the water surface area with low water level values does not cover the reclamation beach or the embankment, and the water surface area with high water level values covers the reclamation beach or the embankment; if the water level of the remote sensing image is met, calculating the elevation value of the reclamation beach or the embankment as the average value of the water levels of the two remote sensing images; if not, sequentially calculating the normalized water indexes of the two adjacent remote sensing images until the condition is met.
5. The method for constructing the relationship between the topography and the water level storage of the shallow lake taking the influence of the high-intensity human activities into consideration according to claim 1, wherein the process of analyzing and obtaining the elevation raster data of the lake area under the set resolution according to the elevation values of the remote sensing image, the natural lake basin contour line and the ground feature of the non-natural lake basin at each time sequence is as follows:
dividing the lake region features into a plurality of feature analysis units, wherein the feature analysis units comprise a natural lake basin water level change region, a beach-exposing sand continent region, a reclamation beach region, a river channel and a embankment;
determining natural lake basin contour lines corresponding to different water levels according to the remote sensing images at each time sequence, and respectively interpolating the natural lake basin contour lines to obtain elevation raster data of the natural lake basin water level change area and the exposed beach sand area;
sampling to obtain elevation raster data of the reclamation beach, the river channel and the embankment according to elevation values of land features of each lake region of the unnatural lake basin;
and integrating elevation raster data of the natural lake basin water level change area and the exposed beach sand area and elevation raster data of the reclamation beach, the river channel and the embankment, thereby obtaining the elevation raster data of the lake area under the set resolution.
6. The method for constructing a shallow lake topography and water level storage relationship taking into account high intensity human activity effects according to claim 5, wherein the ground object analysis unit further comprises an underwater region at the bottom of the natural lake basin; the method for acquiring the elevation raster data of the underwater region is obtained by extrapolation estimation according to the field reconnaissance data.
7. The method for constructing a shallow lake topography and water level storage relationship taking into account the influence of high intensity human activities according to claim 2, further comprising:
judging whether the lake area in any one of the remote sensing images is complete, and when the lake area in the remote sensing image is incomplete, cutting and splicing a plurality of remote sensing images shot in sequence to obtain the remote sensing image containing the complete lake area.
8. The method for constructing the relationship between the topography and the water level in the shallow lake taking the influence of the high-intensity human activities into consideration as claimed in claim 1, wherein the process of constructing the relationship between the water level in the lake according to the elevation raster data is as follows: according to different water level values, the depth from the water surface to the lake bottom is calculated, the grid area is taken as the calculation unit area, the lake storage under different water levels is obtained by adding the calculation unit areas one by one, and accordingly, the lake water level-storage relation is constructed and a relation curve is drawn.
9. A shallow lake topography and water level storage relationship construction system considering the influence of high-intensity human activities, comprising:
the acquisition and identification module is used for acquiring remote sensing images of a plurality of time phases of the lake region, identifying the ground object of the lake region and drawing a vector boundary; the remote sensing image is a high-resolution multispectral remote sensing image, any one of the remote sensing images comprises a complete lake surface area, the ground object of the lake area comprises a natural lake basin and an unnatural lake basin, and the unnatural lake basin comprises a reclamation beach, a embankment and a river channel;
the first determining module is used for identifying the water surface area of the remote sensing image in each time phase by adopting a water index and determining the contour line of the natural lake surface area and the natural lake basin;
the second determining module is used for determining the elevation value of each lake region ground feature of the unnatural lake basin according to the remote sensing image, the field investigation data and the water surface region identification result;
the analysis acquisition module is used for analyzing and acquiring elevation grid data of the lake area under the set resolution according to the remote sensing images, the elevation lines of the natural lake basin and the elevation values of the ground objects of the lake areas of the non-natural lake basin at each time sequence;
and the construction module is used for constructing the lake water level storage relation according to the elevation raster data.
10. An electronic device comprising a processor, a memory and a computer program stored in the memory, the computer program being configured to, when executed by the processor, perform the shallow lake topography-to-water level storage relationship construction method of any one of claims 1-8 taking into account the effects of high intensity human activity.
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