CN112035592B - Road network isolated mesh elimination method based on stroke tip characteristics - Google Patents

Road network isolated mesh elimination method based on stroke tip characteristics Download PDF

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CN112035592B
CN112035592B CN202010930440.2A CN202010930440A CN112035592B CN 112035592 B CN112035592 B CN 112035592B CN 202010930440 A CN202010930440 A CN 202010930440A CN 112035592 B CN112035592 B CN 112035592B
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李成名
吴伟
武鹏达
戴昭鑫
殷勇
张成成
郭沛沛
刘晓丽
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Chinese Academy of Surveying and Mapping
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Abstract

The invention discloses a road network isolated mesh elimination method based on stroke tip characteristics, which is applied to the technical field of geography and cartography and comprises the steps of obtaining original road network data of a topographic map; constructing a node-arc segment-polygon topology for original road network data; calculating the density of each mesh in the original road network, determining a mesh density threshold value by using a sample graph statistical method, and defining the meshes with the mesh density exceeding the threshold value as small meshes; constructing a road stroke, and identifying a tail arc segment of the road stroke; extracting small meshes containing the tail arc sections of the roads, and defining the small meshes as tail end meshes, and small meshes not containing the tail arc sections of the roads as tail non-tail meshes; putting the click peripheral meshes obtained in the step 5 into a candidate set of meshes to be processed; and the like. The invention defines the mesh classification in the road network, defines the small meshes related to the road edge as the end meshes and eliminates the end meshes, thereby avoiding the unreasonable damage of road mesh elimination to the road connectivity and integrity.

Description

Road network isolated mesh elimination method based on stroke tip characteristics
Technical Field
The invention relates to the technical field of geography cartography, in particular to a road network isolated mesh eliminating method based on stroke tip characteristics.
Background
The road network on the map is an objective construction of the communication and distribution condition of the road network in the real geographic world, and is a skeleton element of the map. Generally, road networks have various grades, complex relationships and network shapes, so how to well realize multi-scale continuous expression of the road networks is a difficult problem. The road network is formed by connecting all the road sections to form a series of meshes, and when multi-scale continuous expression is carried out, the meshes of the road network need to be scientifically eliminated, so that the connectivity and integrity of the road can be maintained, and the spatial shape and the density characteristics of the road network can be accurately reflected when the multi-scale expression is ensured.
Mesh elimination of road networks has been a hot spot of multi-scale continuous expression studies of road networks. Internationally, in 1996 research by the scholars of Wanning and Muller et al, a mesh elimination method based on graph theory is proposed, which is easy to organize road network data in the elimination process and effectively maintains road network topological relation, but the method cannot describe road shape and road network structure. Therefore, in the studies of Thomson in 1999 and 2006, the visual perception lattice tower theory is introduced into the elimination of the road network meshes, and a method for eliminating the road meshes based on the stroke features is provided, so that the accuracy of mesh elimination is improved. In the research of Liu Yan forest, Argentina, Huyunshu and the like in 2016 2007 in China, on the basis of the Thomson method, the importance of road click is calculated by using the length, connectivity, road semantic features, road net mesh density and the like of roads, and elimination of road meshes and selection of road nets are carried out. The method can effectively eliminate road meshes in dense road areas such as cities, but in some special areas, the meshes eliminated by the method are positioned in the middle of a road network, so that the connectivity and integrity of the road are damaged.
Therefore, the invention provides a road network isolated mesh elimination method based on stroke ending characteristics, which is different from the conventional research method, defines mesh classification in a road network, defines small meshes related to road edges as ending meshes and eliminates the ending meshes, and avoids unreasonable damage to road connectivity and integrity caused by road mesh elimination.
Therefore, it is an urgent need of the skilled person to provide a method for removing isolated meshes in a road network based on the click tip feature, which can avoid the damage to the connectivity and integrity of the road due to the unreasonable removal of meshes in the road.
Disclosure of Invention
In view of the above, the present invention provides a road network isolated mesh elimination method based on stroke tip characteristics.
In order to achieve the purpose, the invention adopts the following technical scheme:
a road network isolated mesh elimination method based on stroke tip characteristics comprises the following steps:
step 1: acquiring original road network data of a topographic map;
step 2: constructing a node-arc section-polygon topology for original road network data, wherein a closed area corresponding to a topological polygon is a mesh;
and step 3: calculating the density of each mesh in the original road network, determining a mesh density threshold value by using a sample graph statistical method, and defining the meshes with the mesh density exceeding the threshold value as small meshes;
and 4, step 4: constructing a road stroke, and identifying a tail arc segment of the road stroke;
and 5: extracting small meshes containing the tail arc sections of the roads, and defining the small meshes as tail end meshes, and small meshes not containing the tail arc sections of the roads as tail non-tail meshes;
step 6: putting the click peripheral meshes obtained in the step 5 into a candidate set of meshes to be processed;
and 7: sorting the stroke end meshes in the mesh candidate set by adopting a mesh density descending mode, selecting the stroke end meshes with the maximum mesh density to process, and merging the processed stroke end meshes with adjacent meshes to form new meshes;
and 8: calculating the density of the new meshes obtained in the step 7, judging whether the density exceeds a density threshold value, and if so, entering a step 9; if not, entering step 10;
and step 9: judging whether the new mesh entering the step comprises a road stroke terminal arc section or not, if so, putting the mesh into the step 6 and updating the candidate set of the meshes to be processed; if not, entering step 10;
step 10: judging whether a new mesh containing a tip arc section exists in the adjacent meshes entering the step, if so, calculating the density of the adjacent meshes, judging whether the density exceeds a density threshold value, if so, putting and updating a candidate set of meshes to be processed, and if so, entering the step 11; if not, entering step 11;
step 11: judging whether all the click end meshes in the candidate set of meshes to be processed are processed, and if so, entering step 12; if not, returning to the step 7;
and step 12, reserving the non-peripheral meshes of the strokes to obtain an elimination result.
Preferably, in the step 3, the mesh density threshold calculation method compares mesh density distribution curves of two scales before and after the synthesis of the road network, and takes the corresponding value of the split node with obviously different curves as the density threshold.
Preferably, in step 4, the stroke tip arc segment is determined by a method in which the number of intersecting nodes between the arc segment itself and other arc segments in the same road stroke is less than 2(1 or 0), and the arc segment is defined as a tip arc segment.
Preferably, in step 5, the stroke distal mesh and the stroke non-distal mesh are determined by defining the small mesh relating to the distal segment as the stroke distal mesh and defining the remaining mesh as the stroke non-distal mesh.
Preferably, the treatment of the distal mesh in step 7 comprises: and (3) calculating the importance of each terminal arc segment in the stroke terminal meshes, deleting the terminal arc segment with the lowest importance, judging whether the stroke terminal meshes have adjacent meshes, and if the adjacent meshes are merged, repeating the step (7).
Preferably, in step 7, the importance of the tip arc segment is calculated as follows:
I＝max{C,DSLS,L} (1)
in the formula (1), C is road grade, DSIn the click class, LSAnd setting the importance of the parameters in descending order, and calculating to obtain the maximum value, namely the importance of the tip arc segment.
Compared with the prior art, the isolated mesh elimination method for the road network based on the stroke peripheral characteristics is characterized in that mesh classification in the road network is defined, small meshes related to road edges are defined as peripheral meshes and eliminated, and damage to road connectivity and integrity due to unreasonable elimination of road meshes is avoided.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is a flow chart of a mesh elimination method of the present invention;
FIG. 2 illustrates a density threshold determination method according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a tip arc section and a tip mesh in an embodiment of the present invention, wherein FIG. 3.1 is an outermost peripheral area of a road network, and FIG. 3.2 is an inner single loop area and a communication area of the road network;
FIG. 4 is data used in the experiment of the embodiment of the present invention, in which FIG. 4.1 is 1:10000 original road data, and FIG. 4.2 is 1:50000 sample data;
FIG. 5 is a comparison of mesh elimination sequences performed in experiments in accordance with the present invention, wherein FIG. 5.1 is a sequence of a comparative method and FIG. 5.2 is a sequence of a method of the present invention;
fig. 6 is a comparison of the results of the elimination of the peripheral meshes of three typical zones in an example of the invention, wherein fig. 6.1 is the minimum mesh elimination result of the comparative method, fig. 6.2 is the minimum mesh elimination result of the method of the invention, fig. 6.3 is the medium mesh elimination result of the comparative method, fig. 6.4 is the medium mesh elimination result of the method of the invention, fig. 6.5 is the maximum mesh elimination result of the comparative method, and fig. 6.6 is the maximum mesh elimination result of the method of the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the invention provides a road network isolated mesh elimination method based on stroke tip characteristics, which comprises the following steps:
step 1: acquiring original road network data of a topographic map;
step 2: constructing a node-arc section-polygon topology for original road network data, wherein a closed area corresponding to a topological polygon is a mesh;
and step 3: calculating the density of each mesh in the original road network, determining a mesh density threshold value by using a sample graph statistical method, and defining the meshes with the mesh density exceeding the threshold value as small meshes;
and 4, step 4: constructing a road stroke, and identifying a tail arc segment of the road stroke;
and 5: extracting small meshes containing the tail arc sections of the roads, and defining the small meshes as tail end meshes, and small meshes not containing the tail arc sections of the roads as tail non-tail meshes;
step 6: putting the click peripheral meshes obtained in the step 5 into a candidate set of meshes to be processed;
and 7: sorting the stroke end meshes in the mesh candidate set by adopting a mesh density descending mode, selecting the stroke end meshes with the maximum mesh density to process, and merging the processed stroke end meshes with adjacent meshes to form new meshes;
and 8: calculating the density of the new meshes obtained in the step 7, judging whether the density exceeds a density threshold value, and if so, entering a step 9; if not, entering step 10;
and step 9: judging whether the new mesh entering the step comprises a road stroke terminal arc section or not, if so, putting the mesh into the step 6 and updating the candidate set of the meshes to be processed; if not, entering step 10;
step 10: judging whether a new mesh containing a tip arc section exists in the adjacent meshes entering the step, if so, calculating the density of the adjacent meshes, judging whether the density exceeds a density threshold value, if so, putting and updating a candidate set of meshes to be processed, and if so, entering the step 11; if not, entering step 11;
step 11: judging whether all the click end meshes in the candidate set of meshes to be processed are processed, and if so, entering step 12; if not, returning to the step 7;
and step 12, reserving the non-peripheral meshes of the strokes to obtain an elimination result.
In the step 3, the mesh density threshold value calculation method compares mesh density distribution curves of two scales before and after the road network is synthesized, and takes the corresponding values of the split nodes with obviously different curves as the density threshold value. In step 4, the method for determining the click tip arc segment is that the number of the intersection nodes between the arc segment itself and other arc segments in the same road click is less than 2(1 or 0), and the arc segment is defined as the click tip arc segment. In step 5, the method for determining the stroke distal mesh and the stroke non-distal mesh is such that the small mesh relating to the distal arc segment is defined as the stroke distal mesh, and the remaining meshes are defined as the stroke non-distal meshes. The treatment of the distal mesh in step 7 includes: and (3) calculating the importance of each terminal arc segment in the stroke terminal meshes, deleting the terminal arc segment with the lowest importance, judging whether the stroke terminal meshes have adjacent meshes, and if the adjacent meshes are merged, repeating the step (7). In step 7, the importance of the tip arc segment is calculated as follows:
I＝max{C,DSLS,L} (1)
in the formula (1), C is road grade, DSIn the click class, LSAnd setting the importance of the parameters in descending order, and calculating to obtain the maximum value, namely the importance of the tip arc segment.
Example one
As shown in fig. 2, the present embodiment is explained with respect to step S3. In order to determine a suitable mesh density threshold, the invention employsAnd (4) carrying out a statistical algorithm by using the sample data. As shown in fig. 2, the mesh density distribution curves of the road network in two scales before and after integration are statistically compared, each curve representing the relationship between the mesh number and the mesh density, taking the scale from 1:10000 to 1:50000 as an example. And taking the corresponding values of the splitting nodes with obviously different curves as density thresholds. In FIG. 2, when the mesh density is equal to 0.016m/m2When the two curves are very different from each other, 0.016m/m is used for the two curves2Considered to be a mesh density threshold of 1: 50000. Accordingly, cells having a cell density exceeding the threshold value are defined as small cells.
Example two
As shown in fig. 3, the present embodiment is explained with respect to steps S4 and S5, i.e., identification of the tip arc segment, the tip mesh, and the non-tip mesh.
A tip arc segment: for a road segment, if the number of intersection nodes of itself with other arcs in the same road segment is less than 2 (i.e., 0 or 1), the arc is defined as a distal arc. As shown in fig. 3.1, the distal arcs of the route segment S1 are AB and CD, the distal arcs of the route segment S2 are EF and GH, and the distal arcs of the route segment S5 are CG and KN. If there is a closed road segment whose starting and ending nodes coincide, that road segment is also a distal arc segment.
Terminal and non-terminal meshes: cells associated with the terminal arc segment and not adjacent to other small cells are defined as terminal cells, and small cells not associated with the road stroke edge segment are defined as non-terminal cells. For example, in fig. 3.1, mesh I is a peripheral mesh and mesh II is a non-peripheral mesh. It can be seen that the fundamental difference between the terminal mesh I and the non-terminal mesh II is the presence of one or more terminal arc segments. For the tip mesh, there are tip arcs, which if deleted, do not affect the road connectivity. In contrast, for non-distal meshes, where there are no distal arcs, the connectivity of the associated strokes may be broken when any arcs in the mesh are deleted.
In general, the peripheral cells are concentrated primarily in three regions: the road network outermost area, the road network inner single loop area and the road form a communication area. As shown in fig. 3.1, the peripheral mesh I is located in the outermost peripheral region of the road network; in fig. 3.2, the arc AB is a terminal arc, so the cells I containing the arc are terminal cells, which are located in the communication zone formed by the road; arc segment CD is also a distal arc segment, and thus, cell III is a distal cell, which is located in the single loop area inside the road network.
EXAMPLE III
As shown in fig. 4-6, are tests performed in this example to verify the reliability and superiority of the method of the present invention.
FIG. 4.1 shows the original road data in a 1:10000 topographic map of a region of Jiangsu province, with a data range of 14.91 × 15.67km2There are 1064 road targets, and the target scale for data integration is 1: 50000. The threshold value of the mesh density used was set to 0.016m/m at a ratio of 1:500002FIG. 4.2 shows sample data at 1:50000, manually synthesized by the draftsman.
Fig. 5.1 and 5.2 illustrate the mesh elimination sequence of the mesh-based method proposed by moustache et al and the test road network data obtained by the method of the present invention, respectively. The elimination sequences calculated by the two methods are completely different and are marked with red numbers, respectively. And adopting a mesh-based method to identify and eliminate 376 small meshes according to the descending order of mesh density. In contrast, 365 terminal cells out of 376 small cells were eliminated based on the method of the present invention, and 11 non-terminal cells were retained for better connectivity.
In order to quantitatively compare the elimination effect, the elimination result was subjected to statistical analysis in the examples, and the results are shown in table 1. It can be seen that 43 road segments are suspended in the 1:10000 original data, and 40 road segments are suspended in the 1:50000 sample data, indicating that in the mesh elimination process, the draftsman manually eliminates 3 suspended road segments. In contrast, the mesh-based method retained 48 suspension sections, and the inventive method retained 41, which is closer to the results obtained by manual elimination. In addition, the method of the present invention retained 11 more cells than the cell-based method, and was also closer to the manual elimination result, indirectly indicating that the results obtained by the method were more reasonable. Finally, both methods resulted in a total mesh area of 192.65km2Showing that the overall shape of the area formed by the road meshes retained in both methods is substantially the sameThe same is true.
TABLE 1 statistics of elimination results
Figure BDA0002670024020000091
In order to further verify the reliability and superiority of the mesh elimination result of the method of the present invention, the maximum similarity and the average connectivity were calculated and compared in the examples, and the results are shown in table 2. It can be seen that the maximum similarity of the results obtained with the method of the present invention to the results of the 1:50000 sample data is as high as 91.64%, which is higher than the 89.52% results obtained with the mesh-based method. In addition, the corrected average connectivity of the mesh elimination result obtained by the method is 1, which shows that the method effectively retains the road connectivity of all the road strokes, does not damage any strokes and does not generate an isolated road section, and the corrected average connectivity of the mesh elimination result obtained by the mesh-based method is 0.95, which shows that part of the road strokes are damaged.
TABLE 2 maximum similarity and average connectivity contrast
Figure BDA0002670024020000092
Fig. 6 is a comparison of the results of the elimination of peripheral meshes for three exemplary zones using the mesh-based method and the method of the present invention. Wherein for the three zones, the mesh-based approach eliminates the arc segment b, since b is the least important arc segment, while the road stroke where b is located is divided into two strokes in the middle, as shown in fig. 6.1, 6.3, 6.5. In the method, the terminal arc segment is used as an elimination unit, the arc segment b is reserved, and the terminal arc segment a is eliminated, so that the road strokes where the arc segments a and b are located are reserved, the visual continuity is better, and the overall structure of a road network obtained by the method is more similar to the manual elimination result, as shown in fig. 6.2, 6.4 and 6.6.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (3)

1. A road network isolated mesh elimination method based on stroke tip characteristics is characterized by comprising the following steps:
step 1: acquiring original road network data of a topographic map;
step 2: constructing a node-arc section-polygon topology for original road network data, wherein a closed area corresponding to a topological polygon is a mesh;
and step 3: calculating the density of each mesh in the original road network, determining a mesh density threshold value by using a sample graph statistical method, and defining the meshes with the mesh density exceeding the threshold value as small meshes;
and 4, step 4: constructing a road stroke, and identifying a tail arc segment of the road stroke;
and 5: extracting small meshes containing the tail arc sections of the roads, and defining the small meshes as tail end meshes, and small meshes not containing the tail arc sections of the roads as tail non-tail meshes;
step 6: putting the click peripheral meshes obtained in the step 5 into a candidate set of meshes to be processed;
and 7: sorting the stroke end meshes in the mesh candidate set by adopting a mesh density descending mode, selecting the stroke end meshes with the maximum mesh density to process, and merging the processed stroke end meshes with adjacent meshes to form new meshes;
and 8: calculating the density of the new meshes obtained in the step 7, judging whether the density exceeds a density threshold value, and if so, entering a step 9; if not, entering step 10;
and step 9: judging whether the new mesh entering the step comprises a road stroke terminal arc section or not, if so, putting the mesh into the step 6 and updating the candidate set of the meshes to be processed; if not, entering step 10;
step 10: judging whether a new mesh containing a tip arc section exists in the adjacent meshes entering the step, if so, calculating the density of the adjacent meshes, judging whether the density exceeds a density threshold value, if so, putting and updating a candidate set of meshes to be processed, and if not, entering the step 11; if not, entering step 11;
step 11: judging whether all the click end meshes in the candidate set of meshes to be processed are processed, and if so, entering step 12; if not, returning to the step 7;
step 12, retaining the click non-peripheral meshes to obtain an elimination result;
the treatment of the distal mesh in step 7 includes: and (3) calculating the importance of each terminal arc segment in the stroke terminal meshes, deleting the terminal arc segment with the lowest importance, judging whether the stroke terminal meshes have adjacent meshes, and if the adjacent meshes are merged, repeating the step (7).
2. The method for eliminating isolated meshes in road network based on stroke tip characteristics according to claim 1, wherein in step 4, the stroke tip arc segment is defined as a tip arc segment if the number of intersection nodes between the arc segment itself and other arc segments in the same road stroke is less than 2.
3. The road network isolated mesh elimination method based on stroke tip characteristics according to claim 1, wherein in step 7, the tip arc segment importance calculation method is as follows:
I＝max{C,DSLS,L} (1)
in the formula (1), C is road grade, DSIn the click class, LSAnd setting the importance of the parameters in descending order, and calculating to obtain the maximum value, namely the importance of the tip arc segment.
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WO2006042687A1 (en) * 2004-10-18 2006-04-27 Societe De Technologie Michelin Route calculation device and method with progressive elimination of data corresponding to the road network
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