A method and device for identifying flow lines in flood storage and detention areas

Abstract

The present invention provides a method and device for identifying streamlines in a flood storage and detention area, the method comprising: step 1, obtaining a remote sensing image of the flood storage and detention area, and performing noise reduction preprocessing on the remote sensing image; step 2, performing rough streamline extraction on the remote sensing image after noise reduction preprocessing, and segmenting streamline patches therefrom; step 3, using a point density analysis method to obtain the density distribution of each point of the streamline patch, and determining each point core as each feature point for streamline extraction; step 4, linearizing and smoothing all feature points to obtain the streamlines in the flood storage and detention area. The present invention can realize accurate identification of streamlines, improve production efficiency, save manpower and material costs, and has strong streamline extraction performance.

Description

Technical Field

[0001] The invention relates to the technical field of hydrological remote sensing and computer vision, and in particular to a method and device for identifying streamlines in a flood storage and detention area. Background Art

[0002] The existing technology mainly uses ground-based observation methods to select observation points in the flood storage area to measure the flow velocity, and then input it into the model to solve and draw streamlines. There are three main methods:

[0003] (1) Method based on numerical integration, that is, first determine a seed point, then use mathematical integration method to obtain the position of the point at a fixed time step inside the vector field, and then connect these points with line segments. The streamlines obtained in this way are essentially broken line segments.

[0004] (2) Streamline generation method based on stream function, that is, first obtain the stream function through analytical methods, and then the streamline can be generated by extracting the contour lines of the stream function, and on the contour lines of the stream function, the value of the stream function is constant. Streamlines can also be traced by starting from a certain point in the flow field and integrating along the direction of the stream function gradient. The specific method is to start from the seed point, integrate along the direction of the stream function gradient, and repeat the integration process until the predetermined streamline length is reached or a specific termination condition is met to obtain the streamline.

[0005] (3) Streamline representation based on deep learning technology, that is, the compression of the flow field is achieved through a two-stage deep learning method. After interpolating the velocity of each point, a low-resolution flow field is established, and then the high-resolution flow field is reconstructed using a convolutional neural network by imitating the image super-resolution algorithm.

[0006] In practice, the streamline construction based on numerical integration is simple to calculate and conforms to the discrete idea in fluid calculation, so it has become the main streamline construction method. However, the amount of calculation for streamline identification in a large range of water bodies is too large to obtain results quickly. The streamline generation method based on stream function is not applicable when facing complex flows. Usually, numerical methods (such as finite element method, finite difference method, etc.) are required to solve the stream function, which has complicated steps. Although the deep learning method provides new ideas and technical means for the precise analysis and drawing of streamlines, it has high requirements for equipment configuration.

[0007] The above methods all obtain streamlines through ground-based observation methods such as numerical calculations. Ground-based observation methods have some significant limitations, such as time-consuming and labor-intensive acquisition of measured velocity data, limited by terrain and climate factors, not applicable to large-scale water bodies, and complex solution processes. Remote sensing monitoring has the ability to perceive underlying surface information in large areas, high frequencies, high efficiency, and all-weather, and is an effective monitoring method. However, there are currently few studies on streamline extraction and identification using remote sensing methods, especially space-borne Ka SAR.

[0008] Therefore, based on the image data of Luojia-2-01 satellite, this paper proposes a space-based monitoring method suitable for streamline identification in flood storage areas. This method effectively verifies the streamline identification performance of Luojia-2-01 satellite, provides a new idea for large-scale streamline identification in emergency situations, and has important scientific research and practical significance. Summary of the invention

[0009] The purpose of the present invention is to provide a method and device for identifying streamlines in flood storage and detention areas, which is used to solve the problems of large amount of calculation, complex steps, high equipment configuration requirements, etc. in the prior art of streamline identification. It can realize accurate identification of streamlines, improve production efficiency, save manpower and material costs, and has strong streamline extraction performance.

[0010] In order to achieve the above-mentioned object, in a first aspect, the present invention provides a method for identifying flow lines in a flood storage area, comprising:

[0011] Step 1, obtaining remote sensing images of the flood storage area, and performing noise reduction preprocessing on the remote sensing images;

[0012] Step 2: Perform a rough streamline extraction on the remote sensing image after noise reduction preprocessing, and segment the streamline pattern from it;

[0013] Step 3: Use the point density analysis method to obtain the density distribution of each point of the streamline pattern, and determine each point core as each feature point for streamline extraction;

[0014] Step 4: Linearize and smooth all feature points to obtain the streamlines of the flood storage area.

[0015] According to a method for identifying flow lines in a flood storage area provided by the present invention, in step 1, a remote sensing image is acquired through a remote sensing satellite, and a Markov random field model method is used to perform noise reduction preprocessing on the remote sensing image.

[0016] According to a method for identifying flow lines in a flood storage area provided by the present invention, the remote sensing satellite is Luojia-2 01.

[0017] According to a method for identifying streamlines in a flood storage area provided by the present invention, step 2 implements coarse extraction of streamlines through threshold segmentation.

[0018] According to a method for identifying streamlines in a flood storage area provided by the present invention, step 2 specifically includes: first analyzing the pixel threshold for distinguishing streamline patches from other landforms in the remote sensing image after noise reduction preprocessing, and then using the Con statement in the raster calculator of ArcGIS to segment the corresponding streamline patches to achieve rough extraction of streamlines.

[0019] According to a method for identifying streamlines in a flood storage area provided by the present invention, step 3 specifically includes: converting the remote sensing image after the streamlines are roughly extracted from a raster into a point feature through the raster to point tool of ArcGIS, obtaining the density distribution of each point of the streamline map after point density analysis and determining each point core.

[0020] According to a method for identifying streamlines in a flood storage and detention area provided by the present invention, step 4 specifically includes: converting all point cores into broken line segments using the point-to-line tool of ArcGIS, and then smoothing the broken line segments using the Bezier interpolation method to obtain the streamlines in the flood storage and detention area.

[0021] In a second aspect, the present invention further provides a flow line identification device for a flood storage area, comprising:

[0022] A preprocessing unit is used to obtain remote sensing images of the flood storage area and perform noise reduction preprocessing on the remote sensing images;

[0023] A coarse extraction unit is used to perform coarse streamline extraction on the remote sensing image after noise reduction preprocessing, and segment streamline patches therefrom;

[0024] An analysis unit, used to obtain the density distribution of each point of the streamline pattern by using a point density analysis method, and determine each point core as each feature point for streamline extraction;

[0025] The processing unit is used to linearize and smooth all characteristic points to obtain the streamlines of the flood storage area.

[0026] The present invention provides a method and device for identifying streamlines in a flood storage and detention area, the method comprising: step 1, obtaining a remote sensing image of the flood storage and detention area, and performing noise reduction preprocessing on the remote sensing image; step 2, performing a rough streamline extraction on the remote sensing image after noise reduction preprocessing, and segmenting the streamline pattern from it; step 3, using a point density analysis method to obtain the density distribution of each point of the streamline pattern, and determining each point core as each feature point for streamline extraction; step 4, linearizing and smoothing all feature points to obtain the streamlines of the flood storage and detention area. The present invention can realize accurate identification of streamlines, improve production efficiency, save manpower and material costs, and has strong streamline extraction performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0028] In the attached picture:

[0029] Figure 1A schematic diagram of the rough extraction results of step 2 of the method for identifying flow lines in a flood storage area provided by the present invention;

[0030] Figure 2 A schematic diagram of the point density analysis results of step 3 of the flood storage and detention area streamline identification method provided by the present invention;

[0031] Figure 3 A schematic diagram of streamline identification results of step 4 of the method for identifying streamlines in a flood storage area provided by the present invention;

[0032] Figure 4 The present invention provides a flow chart of the method for identifying flow lines in flood storage and detention areas. DETAILED DESCRIPTION

[0033] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0034] Some embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0035] There are many kinds of floating objects on the water surface of the flood storage area during the water withdrawal process. These floating objects naturally gather with the flow of water, and often appear as bright spots on remote sensing images, so they can be used as a means of tracing streamlines. The method for identifying streamlines in the flood storage area provided by the present invention is based on point density analysis, using the SAR (synthetic aperture radar) image acquired by the Luojia-2 01 satellite as a specific implementation, identifying areas with high density of streamline spots in the remote sensing image of the Luojia-2 01 satellite, and selecting "point cores" as the characteristic control points of the streamlines through the attribute table sorted from high to low in ArcGIS. Linearization and smoothing of each "point core" can realize the extraction and remote sensing identification of streamlines. The following will be described in detail.

[0036] See also Figure 4 The present invention provides a method for identifying flow lines in a flood storage area, comprising the following steps:

[0037] Step 1, obtaining remote sensing images of the flood storage area, and performing noise reduction preprocessing on the remote sensing images;

[0038] Specifically, in step 1, remote sensing images are acquired through remote sensing satellites, such as Luojia-2 01. In the process of generation, transmission, reception and recording, remote sensing image signals are often affected by various atmospheric effects and ionospheric radiation, thereby generating various noises and interfering with the extraction of target information. Therefore, remote sensing image denoising preprocessing is the basis for subsequent processing such as image feature extraction, target detection, classification and recognition. The Markov Random Field (MRF) model method not only utilizes grayscale information, but also introduces image spatial information, which can suppress noise very well. The present invention can use the MRF method to perform denoising preprocessing on the original image of the remote sensing identification area of ​​Luojia-2 01.

[0039] Step 2: Perform a rough streamline extraction on the remote sensing image after noise reduction preprocessing, and segment the streamline pattern from it;

[0040] It should be noted that the radar waves of remote sensing satellites are similar to mirror reflections on smooth water surfaces. Therefore, the dark areas on remote sensing images are mostly water bodies, and the brightness of other landforms is relatively high. In particular, Luojia-2 01 is a Ka-band (a high-frequency band closer to visible light) satellite with outstanding ability to depict water body details. The pixel values ​​of water bodies and other landforms in its SAR images are quite different, while the pixel values ​​of streamline patches are higher than those of water bodies. Therefore, it is suitable to use threshold segmentation to achieve rough extraction of streamlines. The specific approach is to first analyze the pixel threshold that distinguishes streamline patches from other landforms in the remote sensing images after denoising preprocessing, and then use the Con statement in the ArcGIS raster calculator to segment the corresponding streamline patches for rough extraction. The rough extraction results are shown below. Figure 1 shown. Figure 1 In the figure, there are original images of ten areas of the original image of the remote sensing identification area of ​​Luojia-2-01 satellite, which are recorded as area 1, area 2, ..., area 10, and the images of each area after rough extraction.

[0041] Step 3: Use the point density analysis method to obtain the point density distribution of the streamline pattern in the remote sensing image, determine the area with higher point density, and select the point cores by sorting the attribute table as the feature points for streamline extraction;

[0042] Specifically, density analysis is to obtain the known quantity of certain phenomena and expand it in the entire landscape based on the quantity measured at each location and the spatial relationship between the locations of the measured quantities, so as to obtain the aggregation situation. Point density analysis can calculate the density of point features around each output raster pixel. It can be used as a fast and efficient clustering analysis method and has important applications in cartographic generalization and data analysis. The point density calculation formula is:

[0043]

[0044] In the formula, d is the point density, pieces / km²; n represents the number of point sets, pieces; s represents the area of ​​the study, km².

[0045] The remote sensing image of Luojia-2-01 in the present invention is taken at the water withdrawal stage of the Dongdian flood storage area. Affected by the flood, the water surface produces many floating objects such as domestic garbage, plastics, and vegetation. These floating objects flow with the water withdrawal process to produce streamlines, so streamline tracing can be performed. In addition, after preliminary manual visual interpretation, the streamlines have obvious aggregation characteristics, so it is suitable to apply point density analysis to determine high-density point cores, which can be used as a basis for subsequent streamline extraction. The specific method is to use the raster to point tool in ArcGIS to convert the image after rough extraction from a raster to a point feature, and after point density analysis, the density situation can be obtained and each point core can be determined. Figure 2 This is the result of point density analysis, where the red dots represent “point cores”. Figure 2 , a point density analysis result diagram of region 1, region 2, ..., region 10 is shown.

[0046] Step 4: Linearize and smooth all feature points to obtain the streamlines of the flood storage area.

[0047] The point cores obtained by the point density analysis method will be used as feature points for streamline extraction. These feature points are all point feature vector data. The point-to-line tool is used in ArcGIS to achieve preliminary streamline identification results, but the extraction results are mostly polyline segments, that is, all point cores are converted into polyline segments, and the polyline segments need to be smoothed by the Bezier interpolation method to obtain the streamlines of the flood storage area. The final streamline identification results of the flood storage area are shown in Figure 1. Figure 3 shown. Figure 3 , the streamline recognition result diagrams of region 1, region 2, ..., region 10 are shown.

[0048] Based on the same inventive concept, the present invention provides a flow line identification device for a flood storage area, which corresponds to the method of the above embodiment, and comprises:

[0049] A preprocessing unit is used to obtain remote sensing images of the flood storage area and perform noise reduction preprocessing on the remote sensing images;

[0050] A coarse extraction unit is used to perform coarse streamline extraction on the remote sensing image after noise reduction preprocessing, and segment streamline patches therefrom;

[0051] An analysis unit, used to obtain the density distribution of each point of the streamline pattern by using a point density analysis method, and determine each point core as each feature point for streamline extraction;

[0052] The processing unit is used to linearize and smooth all characteristic points to obtain the streamlines of the flood storage area.

[0053] In summary, the method and device for identifying flow lines in a flood storage area provided by the present invention have at least the following beneficial effects:

[0054] 1. High production efficiency and can be widely promoted. The present invention can effectively realize the extraction and identification of streamlines in inland water bodies such as flood storage areas, and quickly produce related products. Based on the acquired remote sensing images, the present invention realizes accurate identification of streamlines through relevant processing means, which can greatly improve the production efficiency of streamline thematic products in remote sensing image products. Compared with traditional methods, it greatly saves manpower and financial resources, is scalable, and is suitable for most inland water areas.

[0055] 2. Save manpower and material costs. Traditional ground-based observation methods require measurement stations or technicians to measure hydrological parameters such as flow velocity on site as input parameters for numerical integration. The present invention can obtain streamline information and produce streamline products without field measurement.

[0056] 3. Strong streamline extraction performance. The streamline extraction and identification results of the flood storage area of ​​the present invention have higher error accuracy compared with the actual streamlines, which can significantly improve the streamline extraction performance.

[0057] Those skilled in the art will readily appreciate other embodiments of the present invention after considering the specification and practicing the embodiments disclosed herein. The present invention is intended to cover any variations, uses or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art that are not disclosed by the present invention. It should be understood that the present invention is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A method for identifying flow lines in a flood storage area, characterized in that: include: Step 1, obtaining a remote sensing image of the flood storage area, and performing noise reduction preprocessing on the remote sensing image; Step 2: Perform a rough streamline extraction on the remote sensing image after noise reduction preprocessing, and segment the streamline pattern from it; Step 3, using the point density analysis method to obtain the density distribution of each point of the streamline pattern, and determine each point core as each feature point for streamline extraction; Step 4: Linearize and smooth all feature points to obtain the streamlines of the flood storage area.

2. The method for identifying flow lines in a flood storage area according to claim 1, characterized in that: In the step 1, a remote sensing image is acquired through a remote sensing satellite, and a Markov random field model method is used to perform noise reduction preprocessing on the remote sensing image.

3. The method for identifying flow lines in a flood storage area according to claim 2, characterized in that: The remote sensing satellite is Luojia-2 01.

4. The method for identifying flow lines in a flood storage area according to claim 2, characterized in that: The step 2 realizes the rough extraction of streamlines through threshold segmentation.

5. The method for identifying flow lines in a flood storage area according to claim 4, characterized in that: The step 2 specifically includes: firstly analyzing the pixel threshold for distinguishing streamline patches from other objects in the remote sensing image after noise reduction preprocessing, and then using the Con statement in the raster calculator of ArcGIS to segment the corresponding streamline patches to realize the rough extraction of streamlines.

6. The method for identifying flow lines in a flood storage area according to claim 5, characterized in that: The step 3 specifically includes: converting the remote sensing image after the streamline rough extraction from raster to point feature through ArcGIS raster to point tool, obtaining the density distribution of each point of the streamline map after point density analysis and determining each point core.

7. The method for identifying flow lines in a flood storage area according to claim 6, characterized in that: The step 4 specifically includes: converting all point cores into polyline segments by using the point-to-line tool of ArcGIS, and then smoothing the polyline segments by using the Bezier interpolation method to obtain the streamlines of the flood storage area.

8. A device for identifying flow lines in a flood storage area, characterized in that: include: A preprocessing unit, used to obtain remote sensing images of the flood storage area and perform noise reduction preprocessing on the remote sensing images; A coarse extraction unit is used to perform coarse streamline extraction on the remote sensing image after noise reduction preprocessing, and segment streamline patches therefrom; An analysis unit, used for obtaining the density distribution of each point of the streamline pattern by using a point density analysis method, and determining each point core as each feature point for streamline extraction; The processing unit is used to linearize and smooth all characteristic points to obtain the streamlines of the flood storage area.

Images