CN103175484B - A kind of tree crown measuring method based on three-dimensional laser scanning system - Google Patents
A kind of tree crown measuring method based on three-dimensional laser scanning system Download PDFInfo
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Abstract
The embodiment of the invention discloses a kind of tree crown measuring method based on three-dimensional laser scanning system, comprising: the spatial point cloud data obtaining the target trees that three-dimensional laser scanning system gathers; Described spatial point cloud data is vertically slit into multiple contour differentiation section by tree crown top to tree crown bottom part; According to the spatial point cloud data structure polygon in described differentiation section; According to described polygonal structure tree crown three-dimensional model.Adopt the present invention, by introducing plane right-angle coordinate and adopting a point quadrant to construct polygonal method, the spatial point cloud data distinguished in section is carried out Screening Treatment, accurately extract tree crown surface point to build tree crown three-dimensional model.
Description
Technical field
The present invention relates to a kind of tree crown measuring method, particularly relate to a kind of tree crown measuring method based on three-dimensional laser scanning system.
Background technology
Tree crown is the overall of the whole branch of trees and leaf, and it is that arboreal growth is grown and the architecture basics of other function.The shape of tree crown depends on hereditary capacity and the environmental factor of trees, the tree crown come in every shape, and brings difficulty to relevant research work.
Mainly Feng Zhong section and student thereof study the method for current measurement tree crown." precision forestry [M] " and " crown biomass based on 3 D laser scanning imaging system studies [J] " of the document You Fengzhong section delivered, Xiong Nina " a kind of research of measuring Tree Crown Volume method based on three-dimensional laser scanning system---for Chinese pine [J] ", " application of three-dimensional laser scanning system in the determination of volume of tree [J] " of Deng Xiangrui, the PhD dissertation " measurement science of forest based on 3 D laser scanning mapping system studies [D] " of Luo Xu and the PhD dissertation " estimation of city, Beijing six district three-dimensional green amount and analysis and research [D] " of Tang Xuehai.The technology path of above several method is basically identical, is all tree crown to be regarded as a conicle and multiple round platform, obtains Tree Crown Volume by cumulative for the volume of round platform circular cone.Wherein, the method that the irregular base area proposed with Tang Xuehai serves as round platform base area is comparatively accurate.
Tang Xuehai utilizes three-dimensional laser scanning system to obtain single wooden cloud data, form complete single ebon hat cloud data, then a standing tree is vertically divided into some contour differentiation sections, the whole tree crown of Dan Mu is regarded as by top conicle and the solid that forms of n round platform below, and Tree Crown Volume is this circular cone and n round platform volume sum (see Fig. 1).Wherein, the base area of circular cone and round platform obtains by carrying out measurement to the point of tree crown part, by this part data projection of intercepting on XY coordinate plane, becomes irregular cycle, carry out areal calculation to irregular cycle by these data construct.With being parallel to the vertical curve of Y-axis perpendicular to X-axis, irregular cycle is divided into the individual wide segment of n.The area of irregular cycle is regarded as two triangles and n-2 trapezoidal sum end to end and carry out reference area (see Fig. 2).
Its cubature formula is:
Wherein, V is Tree Crown Volume, and n is the quantity of round platform and circular cone, and h is frustum cone height, and S is area of section.
Its surface area formula is:
Wherein, S is Crown surface area, S
ifor tree crown area of section, and S
0=S
n=0.
But, tree crown is a transparent spatial entities of non-close, three-dimensional laser scanner is utilized to scan, use is parallel to the vertical curve of Y-axis perpendicular to X-axis and is divided into by irregular cycle n wide segment to carry out computing nodes area, do not consider the impact of internal point, the floorage calculating gained like this can be less than actual value.Therefore, current method exist precision not high, Crown surface area cannot be calculated, the problems such as tree crown digital surface model cannot be formed.
As can be seen here, how introducing new data processing method, obtain the surface point of tree crown, structure tree crown digital surface model, and ask calculation Tree Crown Volume and surface area at a high speed, accurately based on this, is the key issue that tree crown measures.
Summary of the invention
Embodiment of the present invention technical matters to be solved is, a kind of tree crown measuring method based on three-dimensional laser scanning system is provided, by introducing plane right-angle coordinate and adopting a point quadrant to construct polygonal method, the spatial point cloud data distinguished in section is carried out Screening Treatment, accurately extracts tree crown surface point to build tree crown three-dimensional model.
In order to solve the problems of the technologies described above, embodiments provide a kind of tree crown measuring method based on three-dimensional laser scanning system, comprising: the spatial point cloud data obtaining the target trees that three-dimensional laser scanning system gathers; Described spatial point cloud data is vertically slit into multiple contour differentiation section by tree crown top to tree crown bottom part; According to the spatial point cloud data structure polygon in described differentiation section; According to described polygonal structure tree crown three-dimensional model.
As the improvement of such scheme, the described spatial point cloud data according to distinguishing in section constructs polygonal step and comprises: project in same plane by the spatial point cloud data in described differentiation section; Build the first plane right-angle coordinate according to described spatial point cloud data, make described spatial point cloud data be distributed in first quartile; In described spatial point cloud data, extract impact point, described impact point comprises the point nearest apart from the X-axis of described first plane right-angle coordinate, distance X-axis point farthest, the point nearest apart from Y-axis, distance Y-axis point farthest; Calculate the intermediate value of the X-axis coordinate of described impact point and the intermediate value of Y-axis coordinate; With the intermediate value of the intermediate value of described X-axis coordinate and Y-axis coordinate for initial point, build the second plane right-angle coordinate according to described impact point; According to the distribution situation structure polygon of described impact point at the second plane right-angle coordinate.
As the improvement of such scheme, the described step extracting impact point in spatial point cloud data comprises: in the X-axis and Y-axis of described first plane right-angle coordinate, set up the first dot matrix; Divide wide interval along X-axis, make the point of the first dot matrix in described X-axis and the wide interval one_to_one corresponding of described X-axis; In the wide interval of described X-axis, extracting apart from the some spatial point cloud data recently, farthest of the first dot matrix corresponding to the wide interval of described X-axis is first reconnaissance; Divide wide interval along Y-axis, make the point of the first dot matrix in described Y-axis and the wide interval one_to_one corresponding of described Y-axis; In the wide interval of described Y-axis, extracting apart from the point first reconnaissance recently, farthest of the first dot matrix corresponding to the wide interval of described Y-axis is impact point.
As the improvement of such scheme, describedly construct polygonal step according to impact point in the distribution situation of the second plane right-angle coordinate and comprise: the distribution situation according to described impact point each quadrant in described second plane right-angle coordinate extracts surface point, when have in four or two quadrants containing impact point time, extracting apart from the X-axis impact point farthest of described second plane right-angle coordinate in containing the quadrant of impact point is surface point, when have in three quadrants containing impact point time, the quadrant adjacent with the quadrant not containing impact point along Y direction extract nearest apart from the X-axis of described second plane right-angle coordinate, impact point is farthest surface point, all the other quadrants extracting apart from the X-axis impact point farthest of described second plane right-angle coordinate is surface point, connect described surface point clockwise or counterclockwise to construct polygon.
As the improvement of such scheme, the described millet cake of connection table clockwise or counterclockwise also comprises after constructing polygonal step: clockwise or counterclockwise, extract continuous print four surface points, described four surface points are followed successively by starting point, the first reference point, the second reference point, the 3rd reference point; Distance between starting point described in comparison and described first reference point, the second reference point, the 3rd reference point, is connected surface point nearest for starting point described in described first reference point, the second reference point, the 3rd reference point middle distance with described starting point; Be new starting point with the surface point that starting point described in described first reference point, the second reference point, the 3rd reference point middle distance is nearest, again extract the first reference point, the second reference point, the 3rd reference point, until all surface points all complete comparison.
As the improvement of such scheme, the described tree crown measuring method based on three-dimensional laser scanning system also comprises: utilize mathematical model 1.
calculate the area of a polygon in described differentiation section, wherein, S is area of a polygon, and m is polygon vertex number, and x is the X-coordinate of polygon vertex, and y is the Y-coordinate of polygon vertex.
As the improvement of such scheme, the described tree crown measuring method based on three-dimensional laser scanning system also comprises: utilize mathematical model 2.
calculate Tree Crown Volume, wherein V is Tree Crown Volume, and n is the polygon number in tree crown three-dimensional model, and H is the height distinguishing section.
As the improvement of such scheme, the described tree crown measuring method based on three-dimensional laser scanning system also comprises: utilize mathematical model 3.
calculate the Crown surface area of target trees, wherein, S
tablefor Crown surface area, C
kfor every layer of polygonal girth.
Implement the embodiment of the present invention, there is following beneficial effect: introduce plane right-angle coordinate, the spatial point cloud data distinguished in section is carried out Screening Treatment, a point quadrant is adopted to construct polygonal method, eliminate the internal point of tree crown, and be successfully extracted the surface point of tree crown, solve the three-dimensional modeling problem that non-close can penetrate object.
In addition, can the height of setting district segmentation according to the actual requirements to set up high-precision tree crown three-dimensional model, show the true form of tree crown better, reflect the detail characteristic of tree crown, for calculating Tree Crown Volume and surface area provides the foundation.
Accompanying drawing explanation
Fig. 1 is the schematic diagram that Tang Xuehai vertically becomes tree crown segmentation some contour differentiation sections;
Fig. 2 is Tang Xuehai with the schematic diagram being parallel to the vertical curve of Y-axis perpendicular to X-axis and being divided into by irregular cycle multiple wide segment;
Fig. 3 is the first embodiment process flow diagram of a kind of tree crown measuring method based on three-dimensional laser scanning system of the present invention;
Fig. 4 is the schematic diagram in Fig. 3, spatial point cloud data being vertically slit into multiple contour differentiation section by tree crown top to tree crown bottom part;
Fig. 5 is the second embodiment process flow diagram of a kind of tree crown measuring method based on three-dimensional laser scanning system of the present invention;
Fig. 6 is the first plane right-angle coordinate schematic diagram constructed by the spatial point cloud data distinguished in section;
Fig. 7 extracts the first plane right-angle coordinate schematic diagram after impact point to Fig. 6;
Fig. 8 is the second plane right-angle coordinate schematic diagram constructed by impact point;
Fig. 9 be by screening after impact point carry out connecting after the polygon schematic diagram that constructs;
Figure 10 is the process flow diagram extracting impact point in Fig. 5 in spatial point cloud data;
Figure 11 is the first plane right-angle coordinate schematic diagram after arranging the first dot matrix;
Figure 12 is the first plane right-angle coordinate schematic diagram after dividing wide interval;
Figure 13 constructs polygonal process flow diagram according to impact point in the distribution situation of the second plane right-angle coordinate in Fig. 5;
Figure 14 is when having in four quadrants containing the surface point schematic diagram extracted during impact point;
Figure 15 is when having in two quadrants containing the surface point schematic diagram extracted during impact point;
Figure 16 is when having in three quadrants containing the surface point schematic diagram extracted during impact point;
Figure 17 is according to impact point distribution situation structure another process flow diagram polygonal at the second plane right-angle coordinate in Fig. 5;
Figure 18 is the schematic diagram that extraction continuous print four surface points are compared;
Figure 19 is after in Figure 18, all surface point all completes comparison, the polygonal schematic diagram formed;
Figure 20 is in the wide interval of X-axis, extracts the schematic diagram of impact point;
Figure 21 is the polygonal schematic diagram that embodiment 1 and reference example 1 construct.
Embodiment
For making the object, technical solutions and advantages of the present invention clearly, below in conjunction with accompanying drawing, the present invention is described in further detail.
Fig. 3 is the first embodiment process flow diagram of a kind of tree crown measuring method based on three-dimensional laser scanning system of the present invention, comprising:
S100, obtains the spatial point cloud data of the target trees that three-dimensional laser scanning system gathers.
It should be noted that, before utilizing three-dimensional laser scanning system to gather the spatial point cloud data of target trees, need the height according to trees, crown projection and scanner specification, the running parameter of scanner and the position of scanning website are set.Every strain target trees at least need to arrange three ground based scanning websites, and tall and big trees can erecting scaffold scanning tree crown top.Correspondingly, according to the running parameter of scanner, the ultimate range D of scanner distance tree crown can be calculated
max,
In above formula, i is the interval of point adjacent in the required three dimensions point gathered, and n is the angle synchronizing frequency of scanner.Operator arranges scanning website according to the ultimate range calculated, and is located at by scanner on scanning website.
When using FaroFocus3D scanner to gather, arranging n is 0.036 °, and i is 0.01m, calculates D
max=15.91m, so the ultimate range of scanning website and tree crown must be less than 15.91m.
When using RieglVZ-1000 scanner to gather, arranging n is 0.0024 °, and i is 0.01m, calculates D
max=238.73m, then the ultimate range of scanning movement and tree crown must be less than 238.73m.
In addition, if need the spatial point cloud data unification gathered by scanner to earth coordinates, then need to lay around trees to control target, ensure that each scanning website at least observes three targets.Or, public target ball directly can be utilized to carry out data splicing, use coordinate system.
During work, scanner is utilized to scan tree crown, after collecting the spatial point cloud data of target trees, three-dimensional laser scanning system passes through coordinate matching, by the spatial point cloud data unification of different scanning website under the same coordinate system, and the spatial point cloud data of deleting around individual plant target trees, under plan view angle, the spatial point cloud data bottom first place to trees alive is deleted again, then through the outer acnode of selective body, minimizing noise and statistical conversion operation, the spatial point cloud data of goal tree ebon hat is obtained.
S101, is vertically slit into multiple contour differentiation section by tree crown top to tree crown bottom part by described spatial point cloud data.
As shown in Figure 4, by the elevation interval of spatial point cloud data according to 1cm, vertically by tree crown top to the dividing regions segmentation of tree crown bottom part, correspondingly, namely the tree crown of target trees is also divided into multiple differentiation section according to the elevation interval of 1cm.
S102, according to the spatial point cloud data structure polygon in described differentiation section.
It should be noted that, spatial point cloud data in each differentiation section all comprises tree crown surface point and internal point, therefore needs again to process spatial point cloud data, rejects internal point, extract tree crown surface point structure polygon, make the actual form of polygon closer to target trees of structure.Wherein, distinguish section and polygon one_to_one corresponding, a spatial point cloud data distinguished in section can construct a polygon.
S103, according to described polygonal structure tree crown three-dimensional model.
Polygon corresponding to connected differentiation section is connected between two, the overall tree crown three-dimensional model of target trees can be formed, owing to again processing spatial point cloud data in step S102, make the actual form of polygon closer to target trees of structure, correspondingly, by described polygon construct the actual form of tree crown three-dimensional model closer to target trees, degree of accuracy is higher.
Fig. 5 is the second embodiment process flow diagram of a kind of tree crown measuring method based on three-dimensional laser scanning system of the present invention, comprising:
S200, obtains the spatial point cloud data of the target trees that three-dimensional laser scanning system gathers.
It should be noted that, before utilizing three-dimensional laser scanning system to gather the spatial point cloud data of target trees, need the height according to trees, crown projection and scanner specification, the running parameter of scanner and the position of scanning website are set.Every strain target trees at least need to arrange three ground based scanning websites, and tall and big trees can erecting scaffold scanning tree crown top.Correspondingly, according to the running parameter of scanner, the ultimate range D of scanner distance tree crown can be calculated
max,
In above formula, i is the interval of point adjacent in the required three dimensions point gathered, and n is the angle synchronizing frequency of scanner.Operator arranges scanning website according to the ultimate range calculated, and is located at by scanner on scanning website.In addition, if need the spatial point cloud data unification gathered by scanner to earth coordinates, then need to lay around trees to control target, ensure that each scanning website at least observes three targets.Or, public target ball directly can be utilized to carry out data splicing, use coordinate system.
During work, scanner is utilized to scan tree crown, after collecting the spatial point cloud data of target trees, three-dimensional laser scanning system passes through coordinate matching, by the spatial point cloud data unification of different scanning website under the same coordinate system, and the spatial point cloud data of deleting around individual plant target trees, under plan view angle, the spatial point cloud data bottom first place to trees alive is deleted again, then through the outer acnode of selective body, minimizing noise and statistical conversion operation, the spatial point cloud data of goal tree ebon hat is obtained.
S201, is vertically slit into multiple contour differentiation section by tree crown top to tree crown bottom part by described spatial point cloud data.
As shown in Figure 4, by the elevation interval of spatial point cloud data according to 1cm, vertically by tree crown top to the dividing regions segmentation of tree crown bottom part, correspondingly, namely the tree crown of target trees is also divided into multiple differentiation section according to the elevation interval of 1cm.
S202, projects to the spatial point cloud data in described differentiation section in same plane.
S203, builds the first plane right-angle coordinate according to described spatial point cloud data, and described spatial point cloud data is distributed in first quartile.
It should be noted that, spatial point cloud data in each differentiation section all comprises tree crown surface point and internal point, therefore needs again to process spatial point cloud data, rejects internal point, extract tree crown surface point to construct polygon, make the actual form of polygon closer to target trees of structure.Wherein, distinguish section and polygon one_to_one corresponding, a spatial point cloud data distinguished in section can construct a polygon.
As shown in Figure 6, during structure polygon, need to build the first plane right-angle coordinate according to the spatial point cloud data in described differentiation section, described spatial point cloud data is distributed in first quartile.
S204, extracts impact point in described spatial point cloud data.
It should be noted that, the impact point extracted in described spatial point cloud data comprises: the point nearest apart from the X-axis of described first plane right-angle coordinate, the X-axis point farthest apart from described first plane right-angle coordinate, the point nearest apart from the Y-axis of described first plane right-angle coordinate, Y-axis point farthest apart from described first plane right-angle coordinate.
As shown in Figure 7, after described spatial point cloud data is extracted, effectively internal point can be rejected.
S205, calculates the intermediate value of the X-axis coordinate of described impact point and the intermediate value of Y-axis coordinate.
S206, with the intermediate value of the intermediate value of described X-axis coordinate and Y-axis coordinate for initial point, builds the second plane right-angle coordinate (see Fig. 8) according to described impact point.
Such as, have impact point A (1,2), B (2,2), C (4,3) and D (7,3), the intermediate value calculating the X-axis coordinate of known impact point is 4, and the intermediate value of Y-axis coordinate is 2.5.Now, with (4,2.5) for initial point, the second plane right-angle coordinate containing impact point A, B, C, D should be built.
S207, according to the distribution situation structure polygon of described impact point at the second plane right-angle coordinate.
As shown in Figure 9, after impact point being placed in the second plane right-angle coordinate, centered by true origin, according to the distribution situation of impact point at the second plane right-angle coordinate, impact point is screened again, reject internal point, and the impact point after screening is connected, structure polygon.
S208, according to described polygonal structure tree crown three-dimensional model.
Polygon corresponding to connected differentiation section is connected between two, the overall tree crown three-dimensional model of target trees can be formed, owing to again carrying out Screening Treatment to spatial point cloud data in step S202 ~ S207, make the actual form of polygon closer to target trees of structure, correspondingly, by described polygon construct the actual form of tree crown three-dimensional model closer to target trees, degree of accuracy is higher.
Figure 10 is the process flow diagram extracting impact point in Fig. 5 in spatial point cloud data, comprising:
S300, the X-axis and Y-axis of described first plane right-angle coordinate set up the first dot matrix.
As shown in figure 11, the first dot matrix is arranged in X-axis and Y-axis, and the dot spacing of the first dot matrix in X-axis is equal, and the dot spacing of the first dot matrix in Y-axis is equal.Preferably, the spacing of the point on the first dot matrix is 1cm.
More preferably, can to be worth most according to the X-axis coordinate of spatial point cloud data on the first plane right-angle coordinate and Y-axis coordinate is worth arranges the first dot matrix most, make the first dot matrix in described X-axis within the scope of the most value of described X-axis coordinate, correspondingly, make the first dot matrix in described Y-axis within the scope of the most value of described Y-axis coordinate.
S301, divides wide interval along X-axis, makes the point of the first dot matrix in described X-axis and the wide interval one_to_one corresponding (see Figure 12) of described X-axis.
S301, in the wide interval of described X-axis, extracting apart from the some spatial point cloud data recently, farthest of the first dot matrix corresponding to the wide interval of described X-axis is first reconnaissance.
It should be noted that, in the wide interval of each X-axis, can the nearest spatial point cloud data of point containing the first dot matrix corresponding to a wide interval apart from described X-axis, and apart from described X-axis wide interval corresponding to the some spatial point cloud data farthest of the first dot matrix.Otherwise, when only having a point or do not put in the wide interval of X-axis, then skip this wide interval.
As shown in figure 20, some A is point in the first dot matrix, and in the wide interval at an A place, the nearest point of range points A be that some A1, range points A point is farthest for putting an A2.
S302, divides wide interval along Y-axis, makes the point of the first dot matrix in described Y-axis and the wide interval one_to_one corresponding (see Figure 12) of described Y-axis.
S303, in the wide interval of described Y-axis, extracting apart from the point first reconnaissance recently, farthest of the first dot matrix corresponding to the wide interval of described Y-axis is impact point.
In the wide interval of each Y-axis, can the nearest first reconnaissance of point containing the first dot matrix corresponding to a wide interval apart from described Y-axis, and apart from described Y-axis wide interval corresponding to the point first reconnaissance farthest of the first dot matrix.Otherwise, when only having a point or do not put in the wide interval of Y-axis, then skip this wide interval.
Figure 13 constructs polygonal process flow diagram according to impact point in the distribution situation of the second plane right-angle coordinate in Fig. 5, comprising:
S400, the distribution situation according to described impact point each quadrant in described second plane right-angle coordinate extracts surface point.
When having in four or two quadrants containing impact point, extracting apart from the X-axis impact point farthest of described second plane right-angle coordinate in containing the quadrant of impact point is surface point.
As shown in figure 14, all containing impact point in first quartile, the second quadrant, third quadrant, fourth quadrant, now, should extract apart from the X-axis impact point farthest of described second plane right-angle coordinate in first quartile, the second quadrant, third quadrant, fourth quadrant is surface point.
As shown in figure 15, only have all containing impact point in the second quadrant fourth quadrant, now, should extract apart from the X-axis impact point farthest of described second plane right-angle coordinate in the second quadrant, fourth quadrant is surface point.
When have in three quadrants containing impact point time, it is surface point that the quadrant adjacent with the quadrant not containing impact point along Y direction extracts apart from the X-axis impact point recently, farthest of described second plane right-angle coordinate, and all the other quadrants extracting apart from the X-axis impact point farthest of described second plane right-angle coordinate is surface point.
As shown in figure 16, all containing impact point in first quartile, the second quadrant, fourth quadrant, and third quadrant is not containing impact point.Correspondingly, be the second quadrant along the quadrant that Y direction is adjacent with third quadrant, therefore, should extract distance the second dot matrix impact point recently, farthest on the second quadrant is surface point, meanwhile, first quartile and fourth quadrant extracting apart from described second dot matrix impact point is farthest surface point.
It should be noted that, when extracting surface point, the second dot matrix can be set up in the X-axis of described second plane right-angle coordinate, make the dot spacing of the second dot matrix equal.Divide wide interval along X-axis, make the point of the second dot matrix in described X-axis and the wide interval one_to_one corresponding of described X-axis.Then, according to actual demand, in the wide interval of described X-axis, extract the some spatial point cloud data recently or farthest apart from the second dot matrix corresponding to the wide interval of described X-axis.
Preferably, the spacing of the point on the second dot matrix is 1cm.
More preferably, can be worth most according to the X-axis coordinate of impact point on the second plane right-angle coordinate and the second dot matrix is set, make the second dot matrix within the scope of the most value of described X-axis coordinate.
S402, connects described surface point clockwise or counterclockwise to construct polygon.
Figure 17 constructs another process flow diagram polygonal according to impact point in the distribution situation of the second plane right-angle coordinate in Fig. 5, comprising:
S500, the distribution situation according to described impact point each quadrant in described second plane right-angle coordinate extracts surface point.
When having in four or two quadrants containing impact point, extracting apart from the X-axis impact point farthest of described second plane right-angle coordinate in containing the quadrant of impact point is surface point.
When have in three quadrants containing impact point time, it is surface point that the quadrant adjacent with the quadrant not containing impact point along Y direction extracts apart from the X-axis impact point recently, farthest of described second plane right-angle coordinate, and all the other quadrants extracting apart from the X-axis impact point farthest of described second plane right-angle coordinate is surface point.
It should be noted that, when extracting surface point, the second dot matrix can be set up in the X-axis of described second plane right-angle coordinate, make the dot spacing of the second dot matrix equal.Divide wide interval along X-axis, make the point of the second dot matrix in described X-axis and the wide interval one_to_one corresponding of described X-axis.Then, according to actual demand, in the wide interval of described X-axis, extract the some spatial point cloud data recently or farthest apart from the second dot matrix corresponding to the wide interval of described X-axis.
Preferably, the spacing of the point on the second dot matrix is 1cm.
More preferably, can be worth most according to the X-axis coordinate of impact point on the second plane right-angle coordinate and the second dot matrix is set, make the second dot matrix within the scope of the most value of described X-axis coordinate.
S501, connects described surface point clockwise or counterclockwise to construct polygon.
S502, clockwise or counterclockwise, extract continuous print four surface points, described four surface points are followed successively by starting point, the first reference point, the second reference point, the 3rd reference point.
As shown in figure 18, P0, P1, P2, P3 are continuous print four surface points in the counterclockwise direction, and correspondingly, P0 is starting point, P1 is the first reference point, P2 is the second reference point, P3 is the 3rd reference point.
S503, the distance between starting point described in comparison and described first reference point, the second reference point, the 3rd reference point, is connected surface point nearest for starting point described in described first reference point, the second reference point, the 3rd reference point middle distance with described starting point.
As shown in figure 18, because P3 distance P0 is nearest, therefore P3 and P0 is linked.
S504, is new starting point with the surface point that starting point described in described first reference point, the second reference point, the 3rd reference point middle distance is nearest, again extracts the first reference point, the second reference point, the 3rd reference point, until all surface points all complete comparison.
As shown in figure 18, linking after P3 and P0, take P3 as starting point, and extraction P4 is the first reference point again, P5 is the second reference point, P6 is the 3rd reference point, until all surface points all complete comparison.
As shown in figure 19, after all surface point all completes comparison, comparatively level and smooth polygon can be formed, closer to goal tree wood crown projection.
Below in conjunction with specific embodiment, the present invention is described in further detail.
Embodiment 1
Adopt method of the present invention, use FaroFocus3D scanner to gather spatial point cloud data, spatial point cloud data is vertically divided into multiple contour differentiation section; Spatial point cloud data according to distinguishing in section builds the first plane right-angle coordinate and extracts impact point; Then, build the second plane right-angle coordinate, according to the distribution situation structure polygon of impact point; Finally, according to the spacing between impact point, extract surface point, structure polygon.
Correspondingly, according to method of the present invention, construct 5 polygons distinguished in section respectively.
Reference example 1
Use FaroFocus3D scanner, the irregular base area adopting Tang Xuehai to propose serves as the method for round platform base area, constructs 5 polygons distinguished in section respectively.
See in Figure 21, figure, A is classified as the polygon that embodiment 1 constructs, and B is classified as the polygon that reference example 1 constructs.As seen from the figure, adopt the method for reference example 1, Screening Treatment is not carried out to the spatial point cloud data distinguished in section, directly construct polygon, the impact of passing through a little cannot be got rid of, differ very large with actual cross-section.Correspondingly, adopt the method for embodiment 1, be extracted the surface point of tree crown more accurately, eliminate internal point, closer to the actual form of tree crown.
More preferably, utilize mathematical model 1.
can calculate the area of a polygon in described differentiation section, wherein, S is area of a polygon, and m is polygon vertex number, and x is the X-coordinate of polygon vertex, and y is the Y-coordinate of polygon vertex.
More preferably, utilize mathematical model 2.
can calculate Tree Crown Volume, wherein V is Tree Crown Volume, and n is the polygon number in tree crown three-dimensional model, and H is the height distinguishing section.
Below in conjunction with specific embodiment, the present invention is described in further detail.
Embodiment 2
Adopt method of the present invention, use FaroFocus3D scanner to gather spatial point cloud data, spatial point cloud data is vertically divided into multiple contour differentiation section, the height H distinguishing section is lcm; Spatial point cloud data according to distinguishing in section builds the first plane right-angle coordinate and extracts impact point; Then, build the second plane right-angle coordinate, according to the distribution situation structure polygon of impact point; Finally, the spacing of asking according to impact point, extracts surface point, structure polygon.
Correspondingly, according to method of the present invention, respectively the Tree Crown Volume of eight sample trees is calculated.
Reference example 2
Use FaroFocus3D scanner, the irregular base area adopting Tang Xuehai to propose serves as the method for round platform base area, makes the height H of differentiation section be lcm, calculates respectively to the Tree Crown Volume of eight sample trees.
Table one is the result of calculation contrast of above-described embodiment and reference example:
Table one
| Tree name | The height of tree/m | Projected area/m | Embodiment 2/m 3 | Reference example 2/m 3 |
| High mountain Banyan | 5.577 | 15.8797 | 15.5489 | 5.83606 |
| Banaba | 6.7227 | 25.1232 | 41.227l | 12.6845 |
| Bischofia javanica Bl | 7.4243 | 12.0l | 29.2327 | 11.484 |
| Bischofia javanica Bl | 7.685 | 12.5042 | 28.6044 | 11.0182 |
| Spire banyan | 7.68 | 12.6905 | 29.1278 | 5.52668 |
| Cloudy fragrant | 5.7364 | 15.1348 | 26.646 | 8.78362 |
| Noodles are set | 10.165 | 24.8361 | 54.3775 | 17.7323 |
| Noodles are set | 10.5682 | 23.2291 | 46.1063 | 14.9058 |
As shown in Table 1, adopt method of the present invention, be extracted the surface point of tree crown more accurately, eliminate internal point, the Tree Crown Volume making calculated Tree Crown Volume obviously be greater than reference example 2 to calculate, closer to the actual form of tree crown.
More preferably, utilize mathematical model 3.
calculate the Crown surface area of target trees, wherein, S
tablefor Crown surface area, C
kfor every layer of polygonal girth.
Below in conjunction with specific embodiment, the present invention is described in further detail.
Embodiment 3
Adopt method of the present invention, use FaroFocus3D scanner to gather spatial point cloud data, spatial point cloud data is vertically divided into multiple contour differentiation section, the height H distinguishing section is 1cm; Spatial point cloud data according to distinguishing in section builds the first plane right-angle coordinate and extracts impact point; Then, build the second plane right-angle coordinate, according to the distribution situation structure polygon of impact point; Finally, according to the spacing between impact point, extract surface point, structure polygon.
Correspondingly, according to method of the present invention, respectively the Crown surface area of eight sample trees is calculated.
Reference example 3
Use FaroFocus3D scanner, the irregular base area adopting Tang Xuehai to propose serves as the method for round platform base area, makes the height H of differentiation section be 1cm, calculates respectively to the Crown surface area of eight sample trees.
Table two is the result of calculation contrast of above-described embodiment 3 and reference example 3:
Table two
| Tree name | The height of tree/m | Embodiment 3/m 2 | Reference example 3/m 2 |
| High mountain Banyan | 5.577 | 145.367 | 75.8036 |
| Banaba | 6.7227 | 165.1159 | 185.864 |
| Bischofia javanica Bl | 7.4243 | 127.9847 | 171.135 |
| Bischofia javanica Bl | 7.685 | 128.8961 | 175.586 |
| Spire banyan | 7.68 | 117.4374 | 146.285 |
| Cloudy fragrant | 5.7364 | 126.493 | 152.681 |
| Noodles are set | 10.165 | 159.1046 | 264.574 |
| Noodles are set | 10.5682 | 137.9969 | 235.082 |
As shown in Table 2, adopt method of the present invention, be extracted the surface point of tree crown more accurately, eliminate internal point, the Crown surface area making calculated Tree Crown Volume be significantly less than reference example 3 to calculate, closer to the actual form of tree crown.
As from the foregoing, adopt the present invention, the spatial point cloud data of acquisition is vertically slit into multiple contour differentiation section by tree crown top to tree crown bottom part, spatial point cloud data according to distinguishing in section builds the first plane right-angle coordinate and extracts impact point, simultaneously, the second plane right-angle coordinate is built according to impact point, and according to the distribution situation structure polygon of described impact point at the second plane right-angle coordinate.Contrast prior art, after only the spatial point cloud data of acquisition being vertically slit into multiple contour differentiation section by tree crown top to tree crown bottom part, Screening Treatment is not carried out to the spatial point cloud data distinguished in section, direct structure polygon, the impact of passing through a little cannot be got rid of, differ very large with actual cross-section.And the present invention effectively can reject the internal point of tree crown, accurately extract the surface point of tree crown, and according to surface point structure polygon, solve the three-dimensional modeling problem that non-close can penetrate object.In addition, also can the height of setting district segmentation according to the actual requirements to set up high-precision tree crown three-dimensional model, show the true form of tree crown better, reflect the detail characteristic of tree crown, for calculating Tree Crown Volume and surface area provides the foundation.
Correspondingly, after structure tree crown three-dimensional model, mathematical model can be utilized 1.
calculate the area of a polygon in each differentiation section.Utilize mathematical model 2.
calculate Tree Crown Volume.Utilize mathematical model 3.
calculate the Crown surface area of target trees.
The above is the preferred embodiment of the present invention; it should be pointed out that for those skilled in the art, under the premise without departing from the principles of the invention; can also make some improvements and modifications, these improvements and modifications are also considered as protection scope of the present invention.
Claims (6)
1., based on a tree crown measuring method for three-dimensional laser scanning system, it is characterized in that, comprising:
Obtain the spatial point cloud data of the target trees that three-dimensional laser scanning system gathers;
Described spatial point cloud data is vertically slit into multiple contour differentiation section by tree crown top to tree crown bottom part;
According to the spatial point cloud data structure polygon in described differentiation section;
According to described polygonal structure tree crown three-dimensional model;
The described spatial point cloud data according to distinguishing in section constructs polygonal step and comprises:
Spatial point cloud data in described differentiation section is projected in same plane;
Build the first plane right-angle coordinate according to described spatial point cloud data, make described spatial point cloud data be distributed in first quartile;
In described spatial point cloud data, extract impact point, described impact point comprises the point nearest apart from the X-axis of described first plane right-angle coordinate, distance X-axis point farthest, the point nearest apart from Y-axis, distance Y-axis point farthest;
Calculate the intermediate value of the X-axis coordinate of described impact point and the intermediate value of Y-axis coordinate;
With the intermediate value of the intermediate value of described X-axis coordinate and Y-axis coordinate for initial point, build the second plane right-angle coordinate according to described impact point;
According to the distribution situation structure polygon of described impact point at the second plane right-angle coordinate;
Describedly construct polygonal step according to impact point in the distribution situation of the second plane right-angle coordinate and comprise:
Distribution situation according to described impact point each quadrant in described second plane right-angle coordinate extracts surface point, when have in four or two quadrants containing impact point time, extracting apart from the X-axis impact point farthest of described second plane right-angle coordinate in containing the quadrant of impact point is surface point, when have in three quadrants containing impact point time, the quadrant adjacent with the quadrant not containing impact point along Y direction extract nearest apart from the X-axis of described second plane right-angle coordinate, impact point is farthest surface point, all the other quadrants extracting apart from the X-axis impact point farthest of described second plane right-angle coordinate is surface point,
Connect described surface point clockwise or counterclockwise to construct polygon.
2., as claimed in claim 1 based on the tree crown measuring method of three-dimensional laser scanning system, it is characterized in that, the described step extracting impact point in spatial point cloud data comprises:
The X-axis and Y-axis of described first plane right-angle coordinate set up the first dot matrix;
Divide wide interval along X-axis, make the point of the first dot matrix in described X-axis and the wide interval one_to_one corresponding of described X-axis;
In the wide interval of described X-axis, extracting apart from the some spatial point cloud data recently, farthest of the first dot matrix corresponding to the wide interval of described X-axis is first reconnaissance;
Divide wide interval along Y-axis, make the point of the first dot matrix in described Y-axis and the wide interval one_to_one corresponding of described Y-axis;
In the wide interval of described Y-axis, extracting apart from the point first reconnaissance recently, farthest of the first dot matrix corresponding to the wide interval of described Y-axis is impact point.
3., as claimed in claim 1 based on the tree crown measuring method of three-dimensional laser scanning system, it is characterized in that, the described millet cake of connection table clockwise or counterclockwise also comprises after constructing polygonal step:
Clockwise or counterclockwise, extract continuous print four surface points, described four surface points are followed successively by starting point, the first reference point, the second reference point, the 3rd reference point;
Distance between starting point described in comparison and described first reference point, the second reference point, the 3rd reference point, is connected surface point nearest for starting point described in described first reference point, the second reference point, the 3rd reference point middle distance with described starting point;
Be new starting point with the surface point that starting point described in described first reference point, the second reference point, the 3rd reference point middle distance is nearest, again extract the first reference point, the second reference point, the 3rd reference point, until all surface points all complete comparison.
4., as claimed in claim 3 based on the tree crown measuring method of three-dimensional laser scanning system, it is characterized in that, also comprise:
Utilize mathematical model
calculate the area of a polygon in described differentiation section, wherein, S is area of a polygon, and m is polygon vertex number, and x is the X-coordinate of polygon vertex, and y is the Y-coordinate of polygon vertex.
5., as claimed in claim 4 based on the tree crown measuring method of three-dimensional laser scanning system, it is characterized in that, also comprise:
Utilize mathematical model
calculate Tree Crown Volume, wherein V is Tree Crown Volume, and n is the polygon number in tree crown three-dimensional model, and H is the height distinguishing section.
6., as claimed in claim 5 based on the tree crown measuring method of three-dimensional laser scanning system, it is characterized in that, also comprise:
Utilize mathematical model
calculate the Crown surface area of target trees, wherein, S
tablefor Crown surface area, C
kfor every layer of polygonal girth.
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| CN103940368A (en) * | 2014-04-16 | 2014-07-23 | 南京航空航天大学 | Method for generating three-dimensional model of corrugation structure of dragonfly wing |
| CN104729464B (en) * | 2014-05-05 | 2017-02-01 | 河南理工大学 | Flattish form subarea scanning method based on three-dimensional laser scanner |
| CN105277143B (en) * | 2014-06-13 | 2019-04-12 | 中兴通讯股份有限公司 | A kind of device and method of measurement area |
| CN106033616B (en) * | 2015-03-17 | 2020-01-31 | 联想(北京)有限公司 | Electronic device and image processing method |
| CN106447767B (en) * | 2016-09-30 | 2019-01-15 | 信阳师范学院 | A kind of trunk parameter extracting method of the three-dimensional dry axial curve building of the trunk based on point cloud data |
| CN107063114B (en) * | 2016-11-16 | 2019-10-01 | 信阳师范学院 | A kind of trunk data reduction method based on tangent plane segmentation |
| CN106846486A (en) * | 2017-01-25 | 2017-06-13 | 广州市城市规划勘测设计研究院 | Ancient and well-known trees mapping method and device based on a cloud |
| CN106839987B (en) * | 2017-03-30 | 2019-03-15 | 信阳师范学院 | A kind of stem volume acquisition methods based on trunk surface model |
| CN108763730B (en) * | 2018-05-24 | 2022-08-12 | 浙江农林大学 | Method, system, terminal and medium for screening street trees based on thermal comfort indexes |
| CN109444937B (en) * | 2018-08-08 | 2021-04-02 | 北京木业邦科技有限公司 | Tree modeling and tending method and device, electronic equipment and storage medium |
| CN109470137B (en) * | 2018-10-19 | 2020-08-18 | 南京林业大学 | Forest information measuring system based on two-dimensional laser scanner and data processing method |
| CN111156922A (en) * | 2019-12-23 | 2020-05-15 | 苏州迭慧智能科技有限公司 | Method for measuring by using contour |
| CN111127312B (en) * | 2019-12-25 | 2023-08-22 | 武汉理工大学 | Method for extracting circles from point clouds of complex objects and scanning device |
| CN111814666B (en) * | 2020-07-07 | 2021-09-24 | 华中农业大学 | Single tree parameter extraction method, system, medium and equipment under complex forest stand |
| CN111984915B (en) * | 2020-08-20 | 2021-06-08 | 黑龙江工程学院 | Biomass extraction method based on different-speed growth relation combined with laser radar equation |
| CN114459378A (en) * | 2022-02-16 | 2022-05-10 | 河南城建学院 | Tunnel engineering three-dimensional laser scanning sectional measurement method and measurement system |
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| JP2010097419A (en) * | 2008-10-16 | 2010-04-30 | Toshiba Plant Systems & Services Corp | Apparatus, program and method for processing three-dimensional data |
| US8537337B2 (en) * | 2009-12-22 | 2013-09-17 | Weyerhaeuser Nr Company | Method and apparatus for analyzing tree canopies with LiDAR data |
| CN102252612B (en) * | 2011-06-14 | 2013-06-12 | 北京林业大学 | Method for measuring crown volume based on elevation isoline method |
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