CN114078140B - Landslide track extraction method based on landslide boundary polygons and slope map - Google Patents
Landslide track extraction method based on landslide boundary polygons and slope map Download PDFInfo
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Abstract
The application provides a landslide track extraction method which can be applied to the field of remote sensing. The method comprises the following steps: and obtaining a slope diagram of the landslide area to be detected and a plurality of landslide boundary polygons, wherein the slope diagram comprises a plurality of different landslide directions. And extracting first skeleton lines corresponding to the plurality of landslide boundary polygons respectively, wherein one first skeleton line represents one landslide track, and connecting a plurality of interrupted first skeleton lines belonging to the same landslide direction in a plurality of different landslide directions into a second skeleton line, wherein the second skeleton line is the landslide track of the same landslide direction. According to the landslide track extraction method based on the landslide boundary polygons and the landslide map, the plurality of identified landslide directions in the region to be detected are utilized, and the skeleton lines extracted from the landslide polygons are combined, so that discontinuous tracks belonging to the same landslide direction are connected, complete and accurate landslide tracks are provided, and support is provided for follow-up research of landslide motion.
Description
Technical Field
The invention belongs to the field of remote sensing, and particularly relates to a landslide track extraction method based on landslide boundary polygons and a landslide map.
Background
Landslide is a serious geological disaster, particularly, secondary landslide caused by earthquake has a large influence range and is sudden, and the continuous occurrence of landslide even can block a rescue route and field investigation, so that the landslide is very important to quickly positioning and evaluating. The method for drawing landslide by using the optical remote sensing image is an effective means for analyzing landslide disasters. Attributes such as landslide area and volume are required to be counted in a landslide record graph frequently, so that the landslide disaster area can be estimated later, the scale of the landslide is estimated, and effective data support is provided for quick emergency response of earthquake relief. It is therefore necessary to identify the boundary of the landslide.
Many researches have been made at present for extracting landslide characteristics from remote sensing images, and automatic landslide cartography based on remote sensing images generally automatically draws a landslide shape through a computer technology to obtain a landslide polygon, and generates a landslide track according to the landslide polygon.
In the optical remote sensing image recognition, due to the reasons of vegetation restoration, shadow shielding and the like of a landslide area, the landslide is difficult to be completely recognized, and a drawn landslide polygon cannot completely draw the whole landslide area. I.e. one landslide area corresponds to a plurality of landslide polygons. However, each landslide polygon corresponds to one landslide track, so that one landslide corresponds to a plurality of discontinuous tracks, and the tracks cannot truly reflect the starting point and the end point of the sliding of a slope body, thereby limiting further research and application of the landslide track map.
Disclosure of Invention
The invention provides a landslide track extraction method based on landslide boundary polygons and a landslide map, which connects discontinuous tracks belonging to the same landslide area, provides complete and accurate landslide tracks and provides support for follow-up research of landslide motion.
In a first aspect, a landslide trajectory extraction method based on a landslide boundary polygon and a slope diagram is provided, which includes: and acquiring a slope diagram of the landslide area to be detected and a plurality of landslide boundary polygons, wherein the slope diagram comprises a plurality of different landslide directions. And extracting corresponding first skeleton lines according to the plurality of landslide boundary polygons, wherein one first skeleton line represents one landslide track. And connecting a plurality of interrupted first skeleton lines belonging to the same landslide direction in a plurality of different landslide direction into a second skeleton line, wherein the second skeleton line is a landslide track of the same landslide direction. Wherein the first skeleton line comprises broken skeleton lines in the same slope range. The second skeleton line refers to a complete skeleton line connected by interrupted skeleton lines.
According to the landslide track extraction method based on the landslide boundary polygons and the landslide map, the plurality of identified landslide directions in the region to be detected are combined with the plurality of interrupt skeleton lines extracted from the plurality of landslide polygons, and discontinuous tracks belonging to the same landslide direction are connected, so that a complete and accurate landslide track is provided, and support is provided for follow-up research of landslide motion.
In a possible implementation manner of the first aspect, the connecting n interrupted first skeleton lines in the same landslide direction in the plurality of different landslide direction into the second skeleton line includes: determining the plane distance between the ith skeleton line and the rest unconnected skeleton lines in a plurality of interrupted first skeleton lines belonging to the same landslide slope direction, and connecting the ith skeleton line with the (i + 1) th skeleton line corresponding to the minimum plane distance. Wherein i is 1, 2, 3, … …, n. The plane distance is the distance between a first end point and a second end point, and the first end point and the second end point belong to different first skeleton lines. In this implementation, the trajectory lines are connected by identifying the trajectory lines that are interrupted in the same slope direction, resulting in a complete and accurate landslide trajectory.
In a possible implementation manner of the first aspect, the planar distance includes a planar euclidean distance and a planar gradient distance. The minimum planar distance means: the plane Euclidean distance is smaller than or equal to a first threshold value, and the plane slope distance is smaller than or equal to a second threshold value. The first threshold and the second threshold are set according to specific situations, and are not limited herein. Therefore, when the two end points satisfy the first threshold and the second threshold simultaneously, the two corresponding end points are connected by a straight line or a curved line, that is, an uninterrupted line, to form a complete second skeleton line, and a complete landslide track is obtained. In the implementation mode, the distance and the angle of the two end points are identified to carry out accurate calculation, so that the interruption tracks in the same slope direction can be accurately identified.
In a possible implementation manner of the first aspect, the second skeleton line is processed by using a smoothing algorithm to obtain a final landslide track. In this implementation, the landslide trajectory resulting from smoothing the second skeleton line may eliminate the remaining interference factors.
In a possible implementation manner of the first aspect, obtaining a plurality of landslide boundary polygons of a landslide area to be measured includes: and acquiring a plurality of landslide boundary polygons from the landslide area to be detected according to an automatic algorithm, a semi-automatic algorithm or a manual work, wherein the landslide boundary polygons are polygon raster data reflecting the landslide range and boundaries. In the implementation mode, the landslide polygon can be obtained in various forms, and follow-up research is facilitated.
In a possible implementation manner of the first aspect, a slope diagram of the area to be measured is determined according to a Digital Elevation Model (DEM). In the implementation mode, the data obtained by the DEM are high in precision and good in data quality, and specific requirements of users can be met.
In a second aspect, there is provided a landslide trajectory extraction apparatus comprising at least one processor and a memory, the at least one processor being configured to perform the method of the first aspect above or any possible implementation manner of the first aspect.
In a third aspect, there is provided a landslide trajectory extraction apparatus comprising a device as in the second aspect, the device being configured to perform the method of the first aspect above or any possible implementation manner of the first aspect.
In a fourth aspect, a computer program product is provided, the computer program product comprising a computer program for performing the method of the first aspect or any possible implementation form of the first aspect, when the computer program is executed by a processor.
In a fifth aspect, a computer-readable storage medium is provided, having stored thereon a computer program for performing the method of the first aspect or any possible implementation manner of the first aspect, when the computer program is executed.
In a sixth aspect, there is provided a chip or an integrated circuit, comprising: a processor configured to invoke and run the computer program from the memory, so that the device on which the chip or the integrated circuit is installed performs the method of the first aspect or any possible implementation manner of the first aspect.
Compared with the prior art, the invention has the beneficial effects that:
the application provides a landslide track extraction method based on landslide boundary polygons and a landslide map. The elevation model is used for identifying the slope directions of a plurality of landslides in a region to be detected, the skeleton lines extracted from the landslide polygons are combined, and discontinuous tracks belonging to the same landslide slope direction are connected by utilizing the principle that the slope directions of slopes of points close in distance on the same sliding path are generally consistent, so that complete and accurate landslide tracks are provided, and support is provided for subsequent research of landslide motion.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a schematic flow chart of an implementation of a landslide trajectory line extraction method provided in an embodiment of the present invention;
FIG. 2 is a schematic diagram illustrating a landslide track break phenomenon in a remote sensing image according to an embodiment of the present invention;
fig. 3 is a diagram of a preliminary landslide trajectory obtained by a skeleton line algorithm according to a landslide polygon image according to an embodiment of the present invention;
FIG. 4 is a diagram of a landslide trajectory with a superimposed slope diagram provided by an embodiment of the present invention;
FIG. 5 is a diagram of a landslide trajectory after breaking a trajectory connection provided by an embodiment of the present invention;
FIG. 6 is a diagram of a landslide trajectory after smoothing as provided by an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more clearly understood, the present application is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of and not restrictive on the broad application.
In the following, the terms "first", "second" are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the embodiments of the present application, "a plurality" means two or more unless otherwise specified.
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
These and other aspects of embodiments of the invention will be apparent with reference to the following description and attached drawings. In the description and drawings, particular embodiments of the invention have been disclosed in detail as being indicative of some of the ways in which the principles of the embodiments of the invention may be practiced, but it is understood that the scope of the embodiments of the invention is not limited correspondingly. On the contrary, the embodiments of the invention include all changes, modifications and equivalents coming within the spirit and terms of the claims appended hereto.
Landslide is one of the main natural disasters in mountainous areas, and often causes great loss, some even devastating disasters, to industrial and agricultural production and people's life and property. Earthquake is one of the direct causes generated by landslide. Landslide is generated to cause casualties and economic loss, landslide caused by a large earthquake can cause burying of a house, damage to roads and formation of a barrier lake, and particularly, damage to the roads can directly cause blockage of a rescue channel and influence the rescue speed. The landslide boundary is rapidly extracted, the landslide disaster area is estimated, the landslide scale is estimated, and effective data support is provided for rapid emergency response of earthquake relief.
At present, the research on landslide boundaries is mainly based on optical remote sensing images, in the identification of the optical remote sensing images, landslides are difficult to be completely identified due to vegetation restoration, shadow shielding and the like of landslide regions, and drawn landslide polygons cannot completely draw the whole landslide region. I.e. one landslide area corresponds to a plurality of landslide polygons. However, each landslide polygon corresponds to one landslide track, so that one landslide corresponds to a plurality of discontinuous tracks, and the tracks cannot truly reflect the starting point and the end point of the sliding of the slope body, thereby limiting further research and application of the landslide track map.
According to the landslide track extraction method based on the landslide boundary polygons and the landslide map, the plurality of identified landslide directions in the area to be detected are utilized, and the skeleton lines extracted from the landslide polygons are combined, so that discontinuous tracks belonging to the same landslide direction are connected, complete and accurate landslide tracks are provided, and support is provided for follow-up research of landslide motion.
A method for extracting a landslide track based on a landslide boundary polygon and a slope diagram provided in the present application is described in detail below with reference to fig. 1, where fig. 1 is a schematic flowchart of a landslide track extraction method 100 according to an embodiment of the present application.
As shown in fig. 1, the method 100 includes:
s101, obtaining a slope diagram of a landslide area to be detected and a plurality of landslide boundary polygons, wherein the slope diagram comprises a plurality of different landslide directions.
In step S101, fig. 2 shows a landslide polygon obtained according to an automatic landslide detection algorithm superimposed on an aerial image of a landslide area, and it can be seen that the landslide polygon detected automatically is incomplete. The map of the area to be measured can obtain DEM data according to airborne laser radar point cloud (LiDAR) of the area to be measured, or the DEM data can be obtained in other modes. Therefore, the slope diagram of the area to be measured corresponding to a plurality of different landslide slope directions can be obtained.
S102, extracting first skeleton lines corresponding to the multiple landslide boundary polygons respectively, wherein one first skeleton line represents one landslide track.
In step S102, fig. 3 shows a preliminary landslide locus map obtained by the skeleton line extraction algorithm. And extracting a plurality of landslide polygons into a first skeleton line by using the obtained landslide boundary polygons. The skeleton line extraction method relates to the basic technology of the remote sensing field of morphological operation, and can be used for refining raster polygon data into a line, wherein the line is used for refining a landslide polygon into a skeleton line. Since the direction, path, etc. of the grid polygon can substantially reflect the real slope body sliding path, the skeleton line can be regarded as a landslide locus. As can be seen from the area a shown in fig. 3, three broken skeleton lines 1, 2 and 3, namely, the landslide locus has a discontinuous problem.
S103, connecting a plurality of interrupted first skeleton lines belonging to the same landslide direction in a plurality of different landslide direction into a second skeleton line, wherein the second skeleton line is a landslide track of the same landslide direction.
In step S103, the first skeleton line refers to the broken skeleton lines in the same slope range, and the second skeleton line refers to the complete skeleton lines connected by the broken skeleton lines. And regarding two end points with the closest plane distance as interrupted landslide tracks, and connecting the interrupted landslide tracks by line segments. The two end points are positioned on two different skeleton lines in the same slope direction range. The method comprises the following specific steps: generating a slope diagram according to DEM data, and giving a landslide trajectory diagram with the slope diagram superimposed as shown in FIG. 4, wherein different slope ranges in the slope diagram are given according to different gray levels, and the slope diagram generated by the DEM can show that the slope diagram comprises a plurality of landslide slope directions. And it can be seen that the slope directions of different skeleton lines in the same landslide area are the same or similar. As can be seen from the area a shown in fig. 4, three broken skeleton lines 1, 2, and 3 are located in the same landslide area. And calculating plane Euclidean distances and slope distances between the end points of different first framework lines within the same slope range.
Optionally, as a possible implementation manner, the planar euclidean distance herein refers to a shortest straight line distance calculated according to the coordinates, and the slope distance is an absolute value of a difference between slope values of the end points at corresponding positions of the slope map. Two skeleton lines with the plane Euclidean distance smaller than a first threshold value and the slope direction distance smaller than a second threshold value are taken as interrupted landslide tracks; the first threshold and the second threshold are set according to specific situations, and are not limited herein. Therefore, when the two end points simultaneously satisfy the first threshold value and the second threshold value, the two corresponding end points are connected by a straight line to form a complete second skeleton line, and a complete landslide track is obtained. As shown in fig. 5, the graph of the landslide locus after the connection of the three interrupted traces of the region a is 1, 2 and 3, it can be seen that the interrupted traces belonging to the same landslide region are connected to constitute the finished landslide locus.
Optionally, as a possible implementation manner, the second skeleton line is smoothed by using a smoothing algorithm to obtain a final landslide track. In this implementation, the landslide trajectory resulting from smoothing the second skeleton line may eliminate the remaining interference factors. The smoothing algorithm is a basic technology in the field of remote sensing. The area a shown in fig. 6 is a smoothed landslide trajectory graph obtained by using a smoothing algorithm after three interrupted trajectory lines of 1, 2, and 3 are connected, that is, a final landslide trajectory extraction result.
Optionally, as a possible implementation manner, the landslide boundary polygon includes polygon raster data that reflects the landslide range and the boundary and is extracted from the remote sensing image by an automatic algorithm, a semi-automatic algorithm or a manual operation. In the implementation mode, the landslide polygon can be obtained in various forms, and follow-up research is facilitated.
Optionally, as a possible implementation manner, the slope diagram of the region to be measured is determined according to the DEM data. In the implementation mode, the data obtained by the DEM is high in precision and good in data quality, and specific requirements of users can be met.
The embodiment of the present application further provides a landslide extraction apparatus, which includes at least one processor and a memory, where the at least one processor is configured to execute the method for landslide trajectory extraction in the method 100.
The embodiment of the present application further provides a landslide extraction apparatus, which includes the above device, and is used for executing the method for landslide trajectory extraction in the method 100.
The present embodiment also provides a computer readable medium for storing a computer program code, where the computer program includes instructions for executing the method of landslide trajectory extraction of the present embodiment in the method 100 described above. The readable medium may be a read-only memory (ROM) or a Random Access Memory (RAM), which is not limited in this embodiment of the present application.
The present application also provides a computer program product comprising instructions that, when executed, cause the target-identifying apparatus to perform operations corresponding to the landslide trajectory extraction in the method 100 described above, respectively.
An embodiment of the present application further provides a chip or an integrated circuit, where the chip or the integrated circuit includes: a processor for calling and running the computer program from the memory so that the device on which the chip or the integrated circuit is installed performs the method of landslide trajectory extraction in the method 100.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.
Claims (7)
1. A landslide trajectory extraction method, the method comprising:
acquiring a slope drawing of a landslide area to be tested and a plurality of landslide boundary polygons, wherein the slope drawing comprises a plurality of different landslide directions;
extracting first skeleton lines corresponding to the plurality of landslide boundary polygons respectively, wherein one first skeleton line represents a landslide track;
connecting a plurality of interrupted first skeleton lines belonging to the same landslide direction in the plurality of different landslide direction into a second skeleton line, wherein the second skeleton line is a landslide track of the same landslide direction;
the method for connecting n interrupted first skeleton lines in the same landslide direction to form a second skeleton line comprises the following steps:
determining plane distances between the ith skeleton line and the rest unconnected skeleton lines in a plurality of interrupted first skeleton lines belonging to the same landslide slope direction;
connecting the ith skeleton line with the (i + 1) th skeleton line corresponding to the minimum plane distance;
wherein i =1, 2, 3, … …, n;
the plane distance is the distance between a first end point and a second end point, and the first end point and the second end point belong to different first skeleton lines;
the plane distance comprises a plane Euclidean distance and a plane slope distance, and the minimum plane distance is as follows:
the plane Euclidean distance is smaller than or equal to a first threshold value, the plane slope distance is smaller than or equal to a second threshold value, the plane Euclidean distance refers to the shortest straight line distance, and the slope distance is the absolute value of the difference of the slope values of the end points at the corresponding positions of the slope diagram.
2. The landslide trajectory extraction method of claim 1, further comprising:
and processing the second skeleton line by using a smoothing algorithm to obtain a final landslide track.
3. The landslide trajectory extraction method of claim 1, wherein said obtaining a plurality of landslide boundary polygons of a landslide area to be tested comprises:
and acquiring the plurality of landslide boundary polygons from a landslide area to be detected according to an automatic algorithm, a semi-automatic algorithm or a manual work, wherein the plurality of landslide boundary polygons are polygon raster data reflecting landslide ranges and boundaries.
4. The landslide trajectory extraction method of claim 1, wherein said obtaining a slope map of a landslide area to be tested comprises:
and determining the slope map according to a digital elevation model in the obtained landslide area to be detected.
5. A landslide trajectory extraction device comprising at least one processor coupled to at least one memory;
the at least one processor configured to execute a computer program or instructions stored in the at least one memory to cause the apparatus to perform the method of landslide trajectory extraction of any one of claims 1-4.
6. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 4.
7. A chip, comprising: a processor for calling and running a computer program from a memory so that a communication device in which the chip is installed performs the method of any one of claims 1 to 4.
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Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102314609A (en) * | 2011-09-13 | 2012-01-11 | 中国科学院地理科学与资源研究所 | Skeleton extraction method and device for polygonal image |
CN105740807A (en) * | 2016-01-28 | 2016-07-06 | 武汉大学 | Method for extracting continuous river skeleton lines from remote sensing image based on mathematical morphology |
CN108629760A (en) * | 2017-03-22 | 2018-10-09 | 香港理工大学深圳研究院 | A kind of remote sensing image Changing Area Detection method and device |
CN108957447A (en) * | 2018-04-16 | 2018-12-07 | 长江水利委员会水文局长江下游水文水资源勘测局 | A kind of ship base radar water boundaries method for automatic measurement |
CN109783967A (en) * | 2019-01-25 | 2019-05-21 | 深圳大学 | A kind of Prediction of Landslide and system |
CN110288602A (en) * | 2019-05-10 | 2019-09-27 | 香港理工大学深圳研究院 | Come down extracting method, landslide extraction system and terminal |
Family Cites Families (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20200150668A1 (en) * | 2018-11-12 | 2020-05-14 | Alberto Daniel Lacaze | Autonomous Truck Unloading for Mining and Construction Applications |
-
2020
- 2020-08-19 CN CN202010836036.9A patent/CN114078140B/en active Active
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102314609A (en) * | 2011-09-13 | 2012-01-11 | 中国科学院地理科学与资源研究所 | Skeleton extraction method and device for polygonal image |
CN105740807A (en) * | 2016-01-28 | 2016-07-06 | 武汉大学 | Method for extracting continuous river skeleton lines from remote sensing image based on mathematical morphology |
CN108629760A (en) * | 2017-03-22 | 2018-10-09 | 香港理工大学深圳研究院 | A kind of remote sensing image Changing Area Detection method and device |
CN108957447A (en) * | 2018-04-16 | 2018-12-07 | 长江水利委员会水文局长江下游水文水资源勘测局 | A kind of ship base radar water boundaries method for automatic measurement |
CN109783967A (en) * | 2019-01-25 | 2019-05-21 | 深圳大学 | A kind of Prediction of Landslide and system |
CN110288602A (en) * | 2019-05-10 | 2019-09-27 | 香港理工大学深圳研究院 | Come down extracting method, landslide extraction system and terminal |
Non-Patent Citations (2)
Title |
---|
Methodological Validation for Automated Lineament Extraction by LINE Method in PCI Geomatica and MATLAB based Hough Transformation;Chalantika Laha Salui;《JOURNAL GEOLOGICAL SOCIETY OF INDIA》;20180930;全文 * |
Preprocessing and postprocessing for skeleton-based fingerprint minutiae extraction;Feng Zhao et al.;《Pattern Recognition》;20071231;全文 * |
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