CN117237557B - Urban mapping data processing method based on point cloud data - Google Patents
Urban mapping data processing method based on point cloud data Download PDFInfo
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- 238000013507 mapping Methods 0.000 title claims abstract description 47
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- 238000007781 pre-processing Methods 0.000 claims abstract description 12
- 238000012545 processing Methods 0.000 claims description 44
- 238000010606 normalization Methods 0.000 claims description 7
- 230000001502 supplementing effect Effects 0.000 claims description 4
- 238000012800 visualization Methods 0.000 claims description 4
- 238000005516 engineering process Methods 0.000 claims description 3
- 238000012876 topography Methods 0.000 description 4
- 238000004140 cleaning Methods 0.000 description 2
- 238000007726 management method Methods 0.000 description 2
- 238000002759 z-score normalization Methods 0.000 description 2
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Abstract
The invention discloses a point cloud data-based urban mapping data processing method, which relates to the technical field of urban mapping and comprises the following steps of: setting a first acquisition area and a second acquisition area, obtaining first point cloud data and second point cloud data of the first acquisition area and the second acquisition area, and preprocessing the first point cloud data and the second point cloud data to obtain first available data and second available data; acquiring an overlapping region of the first acquisition region and the second acquisition region, acquiring an available data set of the overlapping region, and performing data fusion on the available data set to acquire overlapping region data; obtaining urban mapping data according to the first available data, the second available data and the overlapping region data, and modeling and visualizing all regions according to the urban mapping data; the method can effectively improve the comprehensiveness of data acquisition, improve the accuracy of point cloud data in the edge area and reduce errors caused by data acquisition.
Description
Technical Field
The invention relates to the technical field of urban mapping, in particular to a method for processing urban mapping data based on point cloud data.
Background
In the city construction and development process, a topography is needed to summarize the city, the traditional two-dimensional topography can only reflect the plane position of the city infrastructure, and the integrated information management and information display of the overground, ground and underground spaces can not be realized, and the comprehensive overall planning and intelligent decision of later-stage information can not be supported, so that a whole city space information frame based on a three-dimensional topography is needed to be established so as to meet the fine management requirements of various industries, various levels and various fields;
in the prior art, the three-dimensional topography is constructed by acquiring point cloud data of a city, a plurality of acquisition points are often required to acquire the point cloud data, and the situation that the acquisition of the data of an edge area is inaccurate in the acquisition area of different acquisition points often occurs, so that the actual situation in the city cannot be effectively reflected by final three-dimensional modeling.
Disclosure of Invention
The invention aims to provide a city mapping data processing method based on point cloud data.
The aim of the invention can be achieved by the following technical scheme: a city mapping data processing method based on point cloud data comprises the following steps:
step S1: setting a first acquisition area and a second acquisition area, acquiring point cloud data of the first acquisition area and the second acquisition area to obtain corresponding first point cloud data and second point cloud data, and preprocessing the obtained first point cloud data and second point cloud data to obtain corresponding first available data and second available data;
step S2: acquiring an overlapping area of the first acquisition area and the second acquisition area according to the first available data and the second available data, acquiring an available data set of the overlapping area, and performing data fusion on the acquired available data set to acquire corresponding overlapping area data;
step S3: and obtaining urban mapping data of all areas according to the first available data, the second available data and the overlapping area data, and modeling and visualizing all areas according to the obtained urban mapping data.
Further, the process of setting the first acquisition region and the second acquisition region includes:
selecting a place in a city as a first acquisition point, taking the first acquisition point as a circle center, obtaining a circular area with a radius of R, wherein R is a preset fixed distance, and marking the obtained circular area as a first acquisition area;
taking the first acquisition areas as references, respectively setting a first acquisition point at a preset fixed distance twice as long as the first acquisition points in the forward east direction, the forward west direction, the forward south direction and the forward north direction, respectively obtaining the first acquisition areas of the first acquisition points by adopting the same method, and the like to obtain a plurality of first acquisition points and the first acquisition areas corresponding to the first acquisition points until the first acquisition areas of all the first acquisition points completely cover the whole city;
taking any four adjacent first acquisition areas as an example, obtaining four intersection points of the four first acquisition areas, respectively connecting the obtained four intersection points, and marking the intersection points of two diagonal lines as second acquisition points corresponding to the four first acquisition areas;
and taking the second acquisition point as a circle center, equally acquiring a circular area with the radius of R, marking the acquired circular area as a second acquisition area, and the like, adopting the same method to respectively acquire other second acquisition points and corresponding second acquisition areas, wherein the acquired intersection point of the second acquisition area and the first acquisition area is the same as the acquired intersection point.
Further, the process of acquiring the point cloud data of the first acquisition region and the second acquisition region to obtain corresponding first point cloud data and second point cloud data includes:
setting a first acquisition unit at a first acquisition point, acquiring point cloud data of a first acquisition area through the first acquisition unit, and marking the acquired point cloud data as first point cloud data, wherein the first point cloud data refers to three-dimensional space information of the first acquisition area, including but not limited to three-dimensional coordinates, reflection intensity, color information and category labels;
setting a second acquisition unit at a second acquisition point, acquiring point cloud data of a second acquisition area through the second acquisition unit, marking the acquired point cloud data as second point cloud data, setting a database, and uploading the acquired first point cloud data and second point cloud data to the database for storage.
Further, the process of preprocessing the obtained first point cloud data and second point cloud data to obtain corresponding first available data and second available data includes:
setting a data processing unit, performing data preprocessing on first point cloud data through the data processing unit, wherein the processing procedure of the data processing unit on the first point cloud data comprises the following steps: outlier processing, missing value processing and normalization processing;
the outlier processing is used for cleaning the outlier cloud data, an absolute median outlier processing method is adopted in the outlier processing, outliers in the first point cloud data are judged based on the absolute median of the absolute outliers, and the outlier cloud data at the outliers are cleaned;
the missing value processing is used for filling missing point cloud data, the missing value processing adopts a statistic filling method, the missing point cloud data is filled according to the distribution condition of the first point cloud data, the normalization processing is used for unifying the first point cloud data format, and the normalization processing adopts a Z-Score normalization method to transform the first point cloud data format;
and marking the first point cloud data obtained after processing as first available data, and similarly, adopting the same method to perform data preprocessing on the second point cloud data to obtain corresponding second available data.
Further, the process of obtaining the available data set of the overlapping region according to the first available data and the second available data includes:
each first acquisition region is intersected with four second acquisition regions, and likewise, each second acquisition region is intersected with four first acquisition regions, and taking any two intersected first acquisition regions and second acquisition regions as examples, the intersected regions are marked as corresponding overlapping regions;
and obtaining point cloud data of the overlapping area according to the first available data obtained by the first acquisition area, marking the point cloud data as first overlapping data, and likewise obtaining second overlapping data of the overlapping area according to the second available data obtained by the second acquisition area, and incorporating the obtained first overlapping data and second overlapping data into an available data set of the overlapping area, and the like, and respectively obtaining other overlapping areas and the corresponding available data sets by adopting the same method.
Further, the process of performing data fusion on the obtained available data set to obtain corresponding overlapping region data includes:
setting a data fusion unit, carrying out data fusion on first overlapping data and second overlapping data in the obtained available data set through the data fusion unit, taking two items of point cloud data of a certain geographic position as an example, and registering the obtained first overlapping data and second overlapping data by using a characteristic point matching method so as to align the first overlapping data and the second overlapping data into a unified reference coordinate system;
interpolation is carried out on the registered point cloud data by adopting a nearest neighbor interpolation method so as to fill in missing point cloud data or holes, the registered point cloud data is projected onto a plane to be fused so as to obtain corresponding overlapping area data, and the overlapping area data is single point cloud data formed by fusing two pieces of point cloud data.
Further, the process of obtaining urban mapping data of all areas according to the first available data, the second available data and the overlapped area data comprises the following steps:
taking any two intersected first acquisition areas and second acquisition areas as examples, deleting first overlapped data in first available data obtained by the first acquisition areas, and similarly deleting second overlapped data in second available data obtained by the second acquisition areas;
and supplementing the obtained overlapping region data into the overlapping region between the first acquisition region and the second acquisition region, and similarly, replacing each item of overlapping region data into the corresponding overlapping region by adopting the same method to obtain urban mapping data of all regions, wherein the urban mapping data comprises first available data and second available data of non-overlapping regions and overlapping region data of overlapping regions.
Further, the modeling and visualization process for all the areas according to the obtained urban mapping data comprises the following steps:
classifying the obtained urban mapping data to classify the urban mapping data into different categories including but not limited to ground points, building points, tree points and the like, and extracting various characteristic information in the urban mapping data including but not limited to surface normals, edges, geometric structures and the like;
modeling is carried out according to urban mapping data and the extracted characteristic information, the point cloud data is converted into a three-dimensional model by utilizing a voxelization algorithm, the obtained texture information is mapped with the constructed three-dimensional model, a virtual map of the city is constructed by utilizing a GIS technology, and the obtained three-dimensional model is uploaded to the virtual map of the city for visualization processing.
Compared with the prior art, the invention has the beneficial effects that:
1. on the basis of dividing the city into a plurality of first acquisition areas, setting corresponding second acquisition areas for the edge areas or the areas which cannot be acquired of the first acquisition areas, so that the comprehensiveness of data acquisition can be effectively improved;
2. according to the first available data and the second available data, the first overlapping data and the second overlapping data of the overlapping area are obtained, and the data fusion is carried out on the first overlapping data and the second overlapping data to obtain corresponding overlapping area data, so that the accuracy of point cloud data of the edge area can be effectively improved, and errors caused by data acquisition can be reduced;
3. and deleting the first overlapping data and the second overlapping data, supplementing the fused overlapping region data into the overlapping region, so that urban mapping data of all regions can be obtained, modeling and visualizing are performed according to the obtained urban mapping data, and the three-dimensional model of the city is facilitated to be checked.
Drawings
Fig. 1 is a schematic diagram of the present invention.
Detailed Description
As shown in fig. 1, a method for processing urban mapping data based on point cloud data comprises the following steps:
step S1: setting a first acquisition area and a second acquisition area, acquiring point cloud data of the first acquisition area and the second acquisition area to obtain corresponding first point cloud data and second point cloud data, and preprocessing the obtained first point cloud data and second point cloud data to obtain corresponding first available data and second available data;
step S2: acquiring an overlapping area of the first acquisition area and the second acquisition area according to the first available data and the second available data, acquiring an available data set of the overlapping area, and performing data fusion on the acquired available data set to acquire corresponding overlapping area data;
step S3: and obtaining urban mapping data of all areas according to the first available data, the second available data and the overlapping area data, and modeling and visualizing all areas according to the obtained urban mapping data.
It should be further noted that, in the implementation process, the process of setting the first acquisition region and the second acquisition region includes:
selecting a place in a city as a first acquisition point, taking the first acquisition point as a circle center, obtaining a circular area with a radius of R, wherein R is a preset fixed distance, and marking the obtained circular area as a first acquisition area;
taking the first acquisition areas as references, respectively setting a first acquisition point at a preset fixed distance twice as long as the first acquisition points in the forward east direction, the forward west direction, the forward south direction and the forward north direction, respectively obtaining the first acquisition areas of the first acquisition points by adopting the same method, and the like to obtain a plurality of first acquisition points and the first acquisition areas corresponding to the first acquisition points until the first acquisition areas of all the first acquisition points completely cover the whole city;
taking any four adjacent first acquisition areas as an example, obtaining four intersection points of the four first acquisition areas, respectively connecting the obtained four intersection points, and marking the intersection points of two diagonal lines as second acquisition points corresponding to the four first acquisition areas;
and taking the second acquisition point as a circle center, equally acquiring a circular area with the radius of R, marking the acquired circular area as a second acquisition area, and the like, adopting the same method to respectively acquire other second acquisition points and corresponding second acquisition areas, wherein the acquired intersection point of the second acquisition area and the first acquisition area is the same as the acquired intersection point.
It should be further noted that, in the implementation process, the process of acquiring the point cloud data of the first acquisition area and the second acquisition area to obtain the corresponding first point cloud data and second point cloud data includes:
setting a first acquisition unit at a first acquisition point, acquiring point cloud data of a first acquisition area through the first acquisition unit, and marking the acquired point cloud data as first point cloud data, wherein the first point cloud data refers to three-dimensional space information of the first acquisition area, including but not limited to three-dimensional coordinates, reflection intensity, color information and category labels;
the three-dimensional coordinates refer to accurate three-dimensional coordinates of each point and are used for representing position information of the points in space, the reflection intensity refers to reflection intensity or echo intensity information of each point, the color information refers to color information and texture information of a specific object, and the category labels refer to additional information for classifying or marking the points;
setting a second acquisition unit at a second acquisition point, acquiring point cloud data of a second acquisition area through the second acquisition unit, marking the acquired point cloud data as second point cloud data, setting a database, and uploading the acquired first point cloud data and second point cloud data to the database for storage.
It should be further noted that, in the implementation process, the process of preprocessing the obtained first point cloud data and second point cloud data to obtain corresponding first available data and second available data includes:
taking the first point cloud data as an example, the obtained first point cloud data is numbered and denoted as i, wherein i=1, 2, … … n, and the obtained first point cloud data is denoted as W i Wherein W is i =(W 1 ，W 2 ，……W n )；
Setting a data processing unit, performing data preprocessing on first point cloud data through the data processing unit, wherein the processing procedure of the data processing unit on the first point cloud data comprises the following steps: outlier processing, missing value processing and normalization processing;
the outlier processing is used for cleaning the outlier cloud data, an absolute median outlier processing method is adopted in the outlier processing, outliers in the first point cloud data are judged based on the absolute median of the absolute outliers, and the outlier cloud data at the outliers are cleaned;
the missing value processing is used for filling missing point cloud data, the missing value processing adopts a statistic filling method, the missing point cloud data is filled according to the distribution condition of the first point cloud data, the normalization processing is used for unifying the first point cloud data format, and the normalization processing adopts a Z-Score normalization method to transform the first point cloud data format;
marking the first point cloud data obtained after processing as first available data, renumbering the first available data, and marking the first available data as j, wherein j=1, 2, … …, m, and marking the first available data as W Kj Wherein W is Kj =(W K1 ，W K2 ，……W Km ) And similarly, performing data preprocessing on the second point cloud data by adopting the same method to obtain corresponding second available data.
It should be further noted that, in the implementation process, the process of obtaining the available data set of the overlapping area according to the first available data and the second available data includes:
each first acquisition region is intersected with four second acquisition regions, and likewise, each second acquisition region is intersected with four first acquisition regions, and taking any two intersected first acquisition regions and second acquisition regions as examples, the intersected regions are marked as corresponding overlapping regions;
and obtaining point cloud data of the overlapping area according to the first available data obtained by the first acquisition area, marking the point cloud data as first overlapping data, and likewise obtaining second overlapping data of the overlapping area according to the second available data obtained by the second acquisition area, and incorporating the obtained first overlapping data and second overlapping data into an available data set of the overlapping area, and the like, and respectively obtaining other overlapping areas and the corresponding available data sets by adopting the same method.
It should be further noted that, in the implementation process, the process of performing data fusion on the obtained available data set to obtain corresponding overlapping region data includes:
setting a data fusion unit, carrying out data fusion on first overlapping data and second overlapping data in the obtained available data set through the data fusion unit, taking two items of point cloud data of a certain geographic position as an example, and registering the obtained first overlapping data and second overlapping data by using a characteristic point matching method so as to align the first overlapping data and the second overlapping data into a unified reference coordinate system;
interpolation is carried out on the registered point cloud data by adopting a nearest neighbor interpolation method so as to fill in missing point cloud data or holes, the registered point cloud data is projected onto a plane to be fused so as to obtain corresponding overlapping area data, and the overlapping area data is single point cloud data formed by fusing two pieces of point cloud data.
It should be further noted that, in the implementation process, the process of obtaining the urban mapping data of all the areas according to the first available data, the second available data and the overlapping area data includes:
taking any two intersected first acquisition areas and second acquisition areas as examples, deleting first overlapped data in first available data obtained by the first acquisition areas, and similarly deleting second overlapped data in second available data obtained by the second acquisition areas;
and supplementing the obtained overlapping region data into the overlapping region between the first acquisition region and the second acquisition region, and similarly, replacing each item of overlapping region data into the corresponding overlapping region by adopting the same method to obtain urban mapping data of all regions, wherein the urban mapping data comprises first available data and second available data of non-overlapping regions and overlapping region data of overlapping regions.
It should be further noted that, in the implementation process, the process of modeling and visualizing all the areas according to the obtained urban mapping data includes:
classifying the obtained urban mapping data to classify the urban mapping data into different categories including but not limited to ground points, building points, tree points and the like, and extracting various characteristic information in the urban mapping data including but not limited to surface normals, edges, geometric structures and the like;
modeling is carried out according to urban mapping data and the extracted characteristic information, the point cloud data is converted into a three-dimensional model by utilizing a voxelization algorithm, the obtained texture information is mapped with the constructed three-dimensional model, a virtual map of the city is constructed by utilizing a GIS technology, and the obtained three-dimensional model is uploaded to the virtual map of the city for visualization processing.
The above embodiments are only for illustrating the technical method of the present invention and not for limiting the same, and it should be understood by those skilled in the art that the technical method of the present invention may be modified or substituted without departing from the spirit and scope of the technical method of the present invention.
Claims (7)
1. The urban mapping data processing method based on the point cloud data is characterized by comprising the following steps of:
step S1: setting a first acquisition area and a second acquisition area, acquiring point cloud data of the first acquisition area and the second acquisition area to obtain corresponding first point cloud data and second point cloud data, and preprocessing the obtained first point cloud data and second point cloud data to obtain corresponding first available data and second available data;
step S2: acquiring an overlapping area of the first acquisition area and the second acquisition area according to the first available data and the second available data, acquiring an available data set of the overlapping area, and performing data fusion on the acquired available data set to acquire corresponding overlapping area data;
step S3: obtaining urban mapping data of all areas according to the first available data, the second available data and the overlapping area data, and modeling and visualizing all areas according to the obtained urban mapping data;
the process of setting the first acquisition region and the second acquisition region includes:
setting first acquisition points, setting first acquisition areas based on the first acquisition points, obtaining a plurality of first acquisition points and first acquisition areas corresponding to the first acquisition points, setting second acquisition points according to any four adjacent first acquisition areas, setting second acquisition areas based on the second acquisition points, and obtaining all second acquisition points and second acquisition areas corresponding to the second acquisition points;
the process of setting the first acquisition region and the second acquisition region includes:
selecting a place in a city as a first acquisition point, taking the first acquisition point as a circle center, obtaining a circular area with a radius of R, wherein R is a preset fixed distance, and marking the obtained circular area as a first acquisition area;
taking the first acquisition areas as a reference, respectively setting a first acquisition point at a preset fixed distance twice as long as the first acquisition points in the east-west direction, the south-south direction and the north-north direction, respectively obtaining the first acquisition areas of the first acquisition points by adopting the same method, and obtaining a plurality of first acquisition points and the first acquisition areas corresponding to the first acquisition points until the first acquisition areas of all the first acquisition points completely cover the whole city;
four adjacent first acquisition areas are taken, four intersection points of the four first acquisition areas are obtained, the obtained four intersection points are respectively connected, and the intersection points of two diagonal lines are marked as second acquisition points corresponding to the four first acquisition areas;
and taking the second acquisition point as a circle center, also obtaining a circular area with the radius of R, marking the obtained circular area as a second acquisition area, and adopting the same method to respectively obtain other second acquisition points and the second acquisition areas corresponding to the other second acquisition points.
2. The method of claim 1, wherein the step of acquiring the point cloud data of the first acquisition region and the second acquisition region to obtain the corresponding first point cloud data and second point cloud data comprises:
setting a first acquisition unit at a first acquisition point, acquiring first point cloud data of a first acquisition area through the first acquisition unit, setting a second acquisition unit at a second acquisition point, acquiring second point cloud data of a second acquisition area through the second acquisition unit, setting a database, and uploading the acquired first point cloud data and second point cloud data to the database for storage.
3. The method for processing urban mapping data based on point cloud data according to claim 2, wherein the process of preprocessing the obtained first and second point cloud data to obtain the corresponding first and second available data comprises:
the method comprises the steps of setting a data processing unit, carrying out data preprocessing on first point cloud data and second point cloud data through the data processing unit to obtain corresponding first available data and second available data, wherein the processing process of the data processing unit on the first point cloud data and the second point cloud data comprises the following steps: outlier processing, missing value processing and normalization processing.
4. A method of urban mapping data processing based on point cloud data according to claim 3, wherein obtaining an overlap region of the first acquisition region and the second acquisition region from the first available data and the second available data, and obtaining an available data set of the overlap region from the first available data and the second available data comprises:
marking the intersected areas of any two intersected first acquisition areas and second acquisition areas as corresponding overlapping areas, obtaining first overlapping data of the overlapping areas according to first available data, obtaining second overlapping data of the overlapping areas according to second available data, and incorporating the obtained first overlapping data and second overlapping data into an available data set of the overlapping areas.
5. The method for processing urban mapping data based on point cloud data according to claim 4, wherein the process of data fusion of the obtained available data sets to obtain corresponding overlapping area data comprises:
the method comprises the steps of setting a data fusion unit, registering first overlapping data and second overlapping data into a unified reference coordinate system through the data fusion unit, interpolating the registered point cloud data to fill in missing point cloud data or holes, and projecting the registered point cloud data onto a plane to be fused to obtain corresponding overlapping area data.
6. The method for processing urban mapping data based on point cloud data according to claim 5, wherein the step of obtaining the urban mapping data of all areas according to the first available data, the second available data and the overlapping area data comprises:
deleting first overlapping data in the first available data, deleting second overlapping data in the second available data, supplementing overlapping area data into an overlapping area between the first acquisition area and the second acquisition area, and replacing all overlapping area data into an overlapping area corresponding to the overlapping area data to obtain urban mapping data of all areas.
7. The method for processing urban mapping data based on point cloud data according to claim 6, wherein the process of modeling and visualizing all areas according to the obtained urban mapping data comprises:
classifying urban mapping data, extracting characteristic information in the urban mapping data, modeling according to the urban mapping data and the characteristic information, converting point cloud data into a three-dimensional model by utilizing a voxelization algorithm, constructing a virtual map of the city by utilizing a GIS technology, and uploading the three-dimensional model to the virtual map of the city for visualization.
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