CN118533149B - An intelligent surveying and mapping method for architectural design - Google Patents
An intelligent surveying and mapping method for architectural design Download PDFInfo
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Abstract
The invention discloses an intelligent mapping method for building design, which relates to the technical field of building mapping and solves the problem that the optimal mapping point is not locked according to the surface characteristics of an actual building area; for convex surface region, in order to ensure that the determined mapping points can reach the optimal coverage mapping effect, three groups of convex surface regions are used as a group of region sets, a triangle determining or circle rotating mode is adopted to determine the optimal mapping points in the region sets, and then the mapping points are used for mapping treatment to ensure the specific mapping effect, meanwhile, the mapping time is shortened, and the mapping work of subsequent mapping personnel is facilitated.
Description
Technical Field
The invention relates to the technical field of building mapping, in particular to an intelligent mapping method for building design.
Background
The mapping is based on computer technology, photoelectric technology, network communication technology, space science and information science, and uses global navigation satellite positioning system (GNSS), remote Sensing (RS) and Geographic Information System (GIS) as technical cores, and selects the existing characteristic points and boundary lines of the ground and obtains the graph and position reflecting the ground current situation and the related information thereof by measuring means for engineering construction, planning design and administrative management.
The application with the bulletin number of CN116295300B relates to the technical field of mapping, in particular to an intelligent building mapping method. The intelligent building mapping method comprises the following steps of arranging a supporting mechanism at a designated measurement place of a building wall, driving a three-dimensional grating scanner to move along a set mapping track by set parameters through a swing arm assembly according to the setting of a central control host after arrangement, and then obtaining point cloud data and panoramic images of building surface contours after the three-dimensional grating scanner moves along the set mapping track, so as to construct a three-dimensional model of a mapping building, and building the three-dimensional model. The automatic surveying and mapping method has the advantages that the automatic surveying and mapping operation of the building can be completed through the arrangement of the surveying and mapping assembly, the rail frame and the supporting mechanism, and the spatial surveying and mapping position, the spatial surveying and mapping angle and the spatial surveying and mapping track of the surveying and mapping assembly can be quickly changed through the swing frame assembly and the rail frame during surveying and mapping operation.
In the specific mapping process of the related building area, the operator generally determines related mapping points, and when the mapping points are confirmed, only personal experience is needed, if a plurality of convex areas exist, a plurality of different mapping points are needed to be determined to map the area, in the actual processing process, the mapping mode wastes time and energy, meanwhile, the mapping efficiency is influenced, and the optimal mapping points are not locked according to the surface characteristics of the actual building area, so that mapping work of the mapping staff is facilitated.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides an intelligent mapping method for building design, which solves the problem that the optimal mapping point is not locked according to the surface characteristics of the actual building area.
In order to achieve the purpose, the intelligent mapping method for the building design is achieved through the following technical scheme that the intelligent mapping method for the building design comprises the following steps of:
S1), generating a terrain three-dimensional model belonging to a relevant design area through a set three-dimensional model based on the relevant image of the relevant design area of the corresponding building;
S2), determining a terrain surface of the terrain three-dimensional model from the determined terrain three-dimensional model, dividing the terrain surface into a plurality of analysis base planes, and determining an uneven area and a flat area based on different gradient data of different analysis base planes, wherein the method comprises the following steps of:
S21, determining a terrain surface from a terrain three-dimensional model, equally dividing the subsurface into a plurality of analysis base surfaces with the same area, determining gradient data of each different analysis base surface from the terrain three-dimensional model, and calibrating the gradient data as PD i, wherein i represents different analysis base surfaces, and directly determining the maximum value of the gradient data as PD i because a plurality of gradient data possibly exist in a single analysis base surface;
S22, comparing the gradient data PD i with a preset interval, wherein the end point values of the preset interval are preset values, if PD i epsilon the preset interval, calibrating the analysis base surface as a flat base surface, if Calibrating the analysis base surface as an uneven base surface;
S23, calibrating a plurality of interconnected flat base surfaces into the same flat area, calibrating interconnected uneven base surfaces into the same uneven area, and calibrating by taking the peripheral area corresponding to the analysis base surface as the relevant area of the analysis base surface if the interconnection condition does not exist;
S3), confirming the height difference of the determined uneven area, determining the relevant height difference of the uneven area by combining the uneven area with the nearest periphery, and calibrating the uneven area as a concave area or a convex area and a relative standard area, wherein the method comprises the following steps:
S31, determining a plurality of groups of intersecting lines with different heights of the uneven area and the peripheral even area, determining the highest intersecting line as a datum line, and constructing a group of transverse horizontal standard planes by using the datum line;
S32, dividing the uneven area based on the transverse horizontal standard surface, marking an area above the transverse horizontal standard surface as a height area, and marking an area below the transverse horizontal standard surface as a low area:
decomposing the height area into a plurality of point positions, taking the point positions as vertical lines of the transverse horizontal standard surface, determining the vertical distances between different point positions and the transverse horizontal standard surface, and selecting a maximum CZ1 from the plurality of vertical distances;
The highest vertical distance CZ2 between the low-level area and the transverse horizontal standard surface is identified, the low-level area is classified into a plurality of point positions, the point positions are taken as vertical lines of the transverse horizontal standard surface, the vertical distances between different point positions and the transverse horizontal standard surface are determined, and the maximum CZ2 is selected from the plurality of vertical distances;
comparing CZ1 determined by different height areas with a preset value Y1, and when CZ1 is more than or equal to Y1, calibrating the height area as a convex area;
comparing the CZ2 determined by different low-level areas with a preset value Y2, namely calibrating the low-level areas as concave areas when the CZ2 is more than or equal to Y2, wherein Y1 and Y2 are both preset values, and calibrating the high-level areas or the low-level areas as relative standard areas when the CZ1 is more than or equal to Y1 or the CZ2 is more than or equal to Y2 if the CZ1 or the CZ2 is not more than or equal to Y2;
S4) determining mapping points of the regions with different types based on the calibrated convex regions or concave regions in the local terrain three-dimensional model by adopting different processing modes, and calibrating the determined mapping points in the local terrain three-dimensional model.
Preferably, for the determined concave surface region, the specific manner of determining the mapping point is as follows:
S411, determining the lowest point of the concave surface area based on the determined horizontal standard plane, decomposing the concave surface area into a plurality of point positions, sequentially determining the vertical distances between different point positions and the horizontal standard plane, selecting the maximum vertical distance, determining the point position, and calibrating the point position as the lowest point, wherein the lowest point is the point position farthest from the horizontal standard plane, namely the point position corresponding to the maximum vertical distance;
and S412, calibrating the lowest point of the concave surface area as a mapping point of the area, and synchronously marking the mapping point in the terrain three-dimensional model.
Preferably, for the determined convex area, the specific manner of determining the mapping point is as follows:
For a convex region of no less than three groups:
S421, randomly selecting a group of convex areas from the inner edge of the local terrain three-dimensional model as a main area, taking the main area as a center, determining two groups of convex areas closest to the main convex area, generating a group of area sets, wherein three groups of convex areas in the area sets cannot be positioned on the same horizontal line, processing other convex areas as the main area in the same mode, generating a plurality of area sets, and the convex areas in each area set cannot be completely overlapped;
S422, determining relative center points of different convex areas in the area set, namely randomly selecting a group of points from the edges of the convex areas as initial points, confirming the related point with the farthest distance from the initial point from the edges of the convex areas, calibrating the related point as opposite points, determining line segments of the initial point and the opposite points, and taking the center point of the line segment as the relative center point of the convex area.
As a first embodiment of step S423, the specific manner of determining the mapping points thereof further includes:
Connecting the relative center points of different convex areas belonging to the same area set, determining a group of triangles to be analyzed, selecting the longest line segment from three groups of side lines of the triangles to be analyzed, determining the opposite triangular point of the longest line segment, starting from the triangular point, making the perpendicular line of the longest line segment, selecting the center point of the perpendicular line as the mapping point of the area set, synchronously marking the mapping point in a terrain three-dimensional model, sequentially determining the mapping points of other area sets, and marking a plurality of determined groups of mapping points in the terrain three-dimensional model.
As a second embodiment of step S423, the specific manner of determining the mapping points thereof further includes:
Taking the relative center point as a circle center, taking the line segment as a circle center, making a group of characteristic circles belonging to the convex surface area, uniformly dividing each characteristic circle into four equal parts, extending the four equal parts outwards, locking extension lines, enabling the distance between the extension lines to be not more than the terrain surface of the local terrain three-dimensional model, enabling three groups of characteristic circles to rotate, enabling the rotation speeds of each group of characteristic circles to be different, enabling the rotation speeds of the three groups of characteristic circles to be different, enabling the three groups of characteristic circles to have no common divisor, confirming the intersection areas generated by the extension lines of the three groups of characteristic circles based on the rotation process, enabling the intersection areas to be common areas generated by the extension lines corresponding to the three groups of characteristic circles, locking the maximum intersection areas based on the rotation process, directly determining the center point of the maximum intersection area, and calibrating the center point to be the mapping point of the local area set;
S5, based on the confirmed mapping points in the local terrain three-dimensional model, operators conduct preferential mapping, free mapping is conducted on the unmeasured area, and relevant points are confirmed by the operators.
The invention provides an intelligent mapping method for building design. Compared with the prior art, the device has the following
The beneficial effects are that:
According to the invention, the building areas are initially classified, then the concave surface areas and the convex surface areas are determined sequentially according to the surface characteristics of the areas, and the areas are classified according to the related characteristics of the related areas, so that the subsequent determination of related mapping points is facilitated;
Aiming at the concave surface area, the mapping point is determined by determining the lowest point of the concave surface area, so that the subsequent mapping treatment is convenient;
For convex surface region, in order to ensure that the determined mapping points can reach the optimal coverage mapping effect, three groups of convex surface regions are used as a group of region sets, a triangle determining or circle rotating mode is adopted to determine the optimal mapping points in the region sets, and then the mapping points are used for mapping treatment to ensure the specific mapping effect, meanwhile, the mapping time is shortened, and the mapping work of subsequent mapping personnel is facilitated.
Drawings
FIG. 1 is a schematic flow chart of the method of the present invention;
FIG. 2 is a schematic diagram illustrating a first mode of identifying mapping points in step S423 of the present invention;
Fig. 3 is a schematic diagram illustrating a second mode of identifying mapping points in step S423 of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
Referring to fig. 1, the application provides an intelligent mapping method for architectural design, which comprises the following steps:
S1), generating a terrain stereoscopic model belonging to a relevant design area through a set three-dimensional stereoscopic model based on the relevant image of the relevant design area, wherein the acquired relevant image can be acquired from cloud big data, can also be extracted based on the relevant image mapped by the unmanned aerial vehicle, is not described in detail herein because the mode of generating the relevant terrain stereoscopic model based on the relevant image is common knowledge, generally based on the acquired high-definition image, the relevant stereoscopic model can automatically generate the relevant stereoscopic model belonging to the area based on the high-definition image and the acquired elevation data, the part of the relevant stereoscopic model is a coarse model, the three-dimensional model is optimized through a subsequent relevant mapping process, and has a powerful three-dimensional model construction function, and the relevant contour curved surface data of the corresponding terrain can be confirmed through the relevant image to construct the relevant stereoscopic model belonging to the local terrain;
S2) determining a terrain surface of the local terrain three-dimensional model based on the determined terrain three-dimensional model, dividing the terrain surface into a plurality of analysis base planes, and determining an uneven area and a flat area based on different gradient data of different analysis base planes, wherein the specific mode for determining is as follows:
s21, determining a terrain surface (namely, the model surface of the model, because the model is three-dimensional and the related gradient of the surface area is determined in order to identify the related gradient of the surface area), dividing the subsurface into a plurality of analysis base surfaces with the same area (the divided specific areas are planned in advance by operators), determining gradient data of each different analysis base surface from the terrain three-dimensional model, and calibrating the gradient data as PD i, wherein i represents the different analysis base surfaces, and directly determining the maximum value of the gradient data as PD i because a plurality of gradient data possibly exist in a single analysis base surface;
S22, comparing the gradient data PD i with a preset interval, wherein the end point values of the preset interval are preset values, the specific values are empirically determined by an operator, if PD i epsilon the preset interval, the analysis base surface is calibrated to be a flat base surface, and if Calibrating the analysis base surface as an uneven base surface;
S23, calibrating a plurality of interconnected flat base surfaces into the same flat area, calibrating interconnected uneven base surfaces into the same uneven area, and calibrating the peripheral area corresponding to the analysis base surface as the relevant area of the analysis base surface if no interconnection condition exists (for example, if a group of flat base surfaces are positioned in the middle and the peripheral areas are all uneven base surfaces, the peripheral uneven areas cause surrounding shape to the flat area, so that the peripheral area outside can be used as the relevant area of the base surface and calibration can be synchronously completed);
S3) confirming the height difference of the determined uneven area, and determining the relevant height difference of the uneven area by combining the uneven area with the nearest periphery, and calibrating the uneven area into a concave area or a convex area and a relative standard area, wherein the specific mode for determining is as follows:
S31, determining a plurality of groups of intersecting lines with different heights of the uneven area and the peripheral even area, determining the highest intersecting line as a datum line, and constructing a group of transverse horizontal standard planes by using the datum line;
S32, dividing the uneven area based on the transverse horizontal standard surface, marking an area above the transverse horizontal standard surface as a height area, and marking an area below the transverse horizontal standard surface as a low area:
decomposing the height area into a plurality of point positions, taking the point positions as vertical lines of the transverse horizontal standard surface, determining the vertical distances between different point positions and the transverse horizontal standard surface, and selecting a maximum CZ1 from the plurality of vertical distances;
The highest vertical distance CZ2 between the low-level area and the transverse horizontal standard surface is identified, the low-level area is classified into a plurality of point positions, the point positions are taken as vertical lines of the transverse horizontal standard surface, the vertical distances between different point positions and the transverse horizontal standard surface are determined, and the maximum CZ2 is selected from the plurality of vertical distances;
Comparing CZ1 determined by different height areas with a preset value Y1, namely when CZ1 is more than or equal to Y1, calibrating the height area as a convex area, otherwise, calibrating the height area as a relative standard area;
Comparing CZ2 determined by different low-level areas with a preset value Y2, namely when CZ2 is more than or equal to Y2, calibrating the low-level areas as concave areas, otherwise, calibrating the low-level areas as relative standard areas, wherein Y1 and Y2 are both preset values, and the specific values are drawn by operators according to experience;
Specifically, when the determined uneven area is identified in the height difference, the height area or the low area to which the uneven area belongs is determined based on the level base surface of the periphery, so that in the specific mapping process, different mapping modes are needed to be adopted for mapping the area in the subsequent step, the best mode of determining the area with the height difference is the nearest plane of the periphery, the plane is taken as a reference plane to determine the relevant area with the height difference with the reference plane, and if the height difference value is overlarge, the relevant calibration of a convex area or a concave area is needed, so that the subsequent step of mapping the area with different types is facilitated;
S4) determining mapping points of regions with different types based on the calibrated convex region or concave region in the local terrain three-dimensional model by adopting different processing modes, and calibrating the determined mapping points in the local terrain three-dimensional model, wherein the specific mode for determining is as follows:
For concave areas:
S411, determining the lowest point of the concave surface area based on the determined horizontal standard plane, decomposing the concave surface area into a plurality of point positions, sequentially determining the vertical distances between different point positions and the horizontal standard plane, selecting the maximum vertical distance, determining the point position, and calibrating the point position as the lowest point, wherein the lowest point is the point position farthest from the horizontal standard plane, namely the point position corresponding to the maximum vertical distance;
s412, calibrating the lowest point of the concave surface area as a mapping point of the area and synchronously marking the mapping point in the terrain three-dimensional model, wherein, for the relevant mapping of the concave surface area, the relevant parameters of the concave surface area cannot be mapped when the external plane area is mapped, so that the lowest point of the area is required to be selected to determine the relevant mapping parameters of the concave surface area, thereby ensuring the mapping precision;
for convex region < three groups:
the mapping points are not required to be determined specifically, the confirmation mode of the mapping points is required to be the original confirmation mode, and the mapping points can be confirmed by operators or on-site confirmation by mapping staff;
For a convex region of no less than three groups:
S421, randomly selecting a group of convex areas from the inner edge of the local terrain three-dimensional model as a main area, then taking the main area as a center, determining two groups of convex areas closest to the local convex area, generating a group of area sets, wherein three groups of convex areas in the area sets cannot be positioned on the same horizontal line (namely, three groups of convex areas must generate a relative surrounding circle, namely, a group of surrounding areas exist among the three groups of convex areas), then taking other convex areas as the main area, processing in the same way, generating a plurality of area sets, and determining that the convex areas in each area set cannot completely coincide (for example, starting from the area A, selecting the area B or the area C, then A, B, C, starting from the area B, selecting the area A or the area C, determining a group of area sets, namely B, C, D areas, and then determining three areas CDE as a group of area sets based on the area C;
S422, determining relative center points of different convex areas in the area set, namely randomly selecting a group of points from the edge of the convex area as initial points, determining the related point with the farthest distance from the initial point from the edge of the convex area, calibrating the related point as opposite points, determining line segments of the initial point and the opposite points, and taking the center point of the line segment as the relative center point of the convex area;
S423, connecting the relative center points of different convex areas belonging to the same area set, determining a group of triangles to be analyzed, selecting the longest line segment from three groups of side lines of the triangles to be analyzed, determining the triangular point opposite to the longest line segment, starting from the triangular point, making the perpendicular line of the longest line segment, selecting the center point of the perpendicular line as the mapping point of the local area set, synchronously marking the mapping point in a terrain three-dimensional model, sequentially confirming the mapping points of other area sets, and marking a plurality of confirmed groups of mapping points in the terrain three-dimensional model;
For example, in connection with fig. 2, a set of regions is drawn as ABC set, three different convex regions A, B and C are subjected to line segment confirmation, the relative center points of the line segments are synchronously confirmed, the relative center points of the three regions are connected, a set of triangles to be analyzed can be determined, the longest line segment is selected from the triangles to be analyzed, and mapping points are selected based on the longest line segment and the opposite points, so that the mapping points can achieve effective mapping on all three convex regions.
Specifically, for a plurality of groups of convex surface areas that exist, the determined mapping point is the optimal mapping point, when the mapping point is mapped by the side point, the mapped convex surface area can be maximized, and a plurality of different convex surface areas can be mapped synchronously.
S5, based on the confirmed mapping points in the local terrain three-dimensional model, operators conduct preferential mapping, free mapping is conducted on the unmeasured area, and relevant points are confirmed by the operators.
Example two
In the implementation of this embodiment, there is another way to determine the mapping point for the convex region, compared to the first embodiment:
For a convex region of no less than three groups:
S421, randomly selecting a group of convex areas from the inner edge of the local terrain three-dimensional model as a main area, taking the main area as a center, determining two groups of convex areas closest to the main convex area, generating a group of area sets, wherein three groups of convex areas in the area sets cannot be positioned on the same horizontal line, processing other convex areas as the main area in the same mode, generating a plurality of area sets, and the convex areas in each area set cannot be completely overlapped;
S422, determining relative center points of different convex areas in the area set, namely randomly selecting a group of points from the edge of the convex area as initial points, determining the related point with the farthest distance from the initial point from the edge of the convex area, calibrating the related point as opposite points, determining line segments of the initial point and the opposite points, and taking the center point of the line segment as the relative center point of the convex area;
S423, referring to FIG. 3, taking the relative center point as the center, taking the line segment as the diameter, making a group of characteristic circles belonging to the convex area, dividing each characteristic circle into four equal parts, extending the four equal parts outwards, locking extension lines, enabling the distances of the extension lines not to exceed the terrain surface of the local terrain three-dimensional model, enabling the three groups of characteristic circles to rotate, enabling the rotation speeds of each group of characteristic circles to be different, enabling the three groups of rotation speeds to have no common divisor (for example, the three groups of rotation speeds are 13, 14 and 15 respectively, enabling the three groups of speeds to have no common divisor, only having common divisor), confirming the intersection areas generated by a plurality of groups of extension lines based on the rotation process, enabling the intersection areas to be common areas generated by the extension lines corresponding to the three groups of characteristic circles, locking the maximum intersection areas based on the rotation process, and directly determining the center point of the maximum intersection areas, and marking the center point as the mapping point of the set of the area;
The center point of the irregular area can be confirmed by a segmentation method, and the method for confirming the center point of the irregular area belongs to common knowledge, so that redundant description is omitted here.
Example III
This embodiment includes all of the implementations of the two sets of embodiments described above.
Some of the data in the above formulas are numerical calculated by removing their dimensionality, and the contents not described in detail in the present specification are all well known in the prior art.
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 (10)
1. An intelligent mapping method for building design is characterized by comprising the following steps:
S1), generating a terrain three-dimensional model belonging to a relevant design area through a set three-dimensional model based on the relevant image of the relevant design area of the corresponding building;
S2), determining a terrain surface of the terrain three-dimensional model based on the determined terrain three-dimensional model, dividing the terrain surface into a plurality of analysis base planes, and determining an uneven area and a smooth area based on different gradient data of different analysis base planes;
S3) confirming the height difference of the determined uneven area, determining the relevant height difference of the uneven area by combining the uneven area with the nearest periphery, and calibrating the uneven area as a concave area or a convex area and a relative standard area;
S4) determining mapping points of the regions with different types based on the calibrated convex regions or concave regions in the local terrain three-dimensional model by adopting different processing modes, and calibrating the determined mapping points in the local terrain three-dimensional model.
2. The intelligent mapping method for architectural design according to claim 1, wherein in the step S2, the specific manner of determining the uneven area and the leveling area includes:
S21, determining a terrain surface from a terrain three-dimensional model, equally dividing the subsurface into a plurality of analysis base surfaces with the same area, determining gradient data of each different analysis base surface from the terrain three-dimensional model, and calibrating the gradient data as PD i, wherein i represents different analysis base surfaces, and directly determining the maximum value of the gradient data as PD i because a plurality of gradient data possibly exist in a single analysis base surface;
S22, comparing the gradient data PD i with a preset interval, wherein the end point values of the preset interval are preset values, if PD i epsilon the preset interval, calibrating the analysis base surface as a flat base surface, if The analysis base surface is marked as an uneven base surface if a preset interval is set;
S23, calibrating a plurality of interconnected flat base surfaces into the same flat area, calibrating interconnected uneven base surfaces into the same uneven area, and calibrating by taking the peripheral area corresponding to the analysis base surface as the relevant area of the analysis base surface if the interconnection condition does not exist.
3. The intelligent mapping method for architectural design according to claim 1, wherein in the step S3, the specific way of marking the uneven area as the concave area or the convex area and the relative standard area includes:
S31, determining a plurality of groups of intersecting lines with different heights of the uneven area and the peripheral even area, determining the highest intersecting line as a datum line, and constructing a group of transverse horizontal standard planes by using the datum line;
S32, dividing the uneven area based on the transverse horizontal standard surface, marking an area above the transverse horizontal standard surface as a height area, and marking an area below the transverse horizontal standard surface as a low area:
decomposing the height area into a plurality of point positions, taking the point positions as vertical lines of the transverse horizontal standard surface, determining the vertical distances between different point positions and the transverse horizontal standard surface, and selecting a maximum CZ1 from the plurality of vertical distances;
The highest vertical distance CZ2 between the low-level area and the transverse horizontal standard surface is identified, the low-level area is classified into a plurality of point positions, the point positions are taken as vertical lines of the transverse horizontal standard surface, the vertical distances between different point positions and the transverse horizontal standard surface are determined, and the maximum CZ2 is selected from the plurality of vertical distances;
comparing CZ1 determined by different height areas with a preset value Y1, and when CZ1 is more than or equal to Y1, calibrating the height area as a convex area;
And comparing the CZ2 determined by the different low-level areas with a preset value Y2, wherein when the CZ2 is more than or equal to Y2, the low-level areas are marked as concave areas, and Y1 and Y2 are both preset values.
4. An intelligent mapping method for architectural design according to claim 3, wherein the height area or the low height area is marked as a relative standard area when CZ1 is not equal to or greater than Y1 or CZ2 is not equal to or greater than Y2.
5. The intelligent mapping method for architectural design according to claim 3, wherein in the step S4, the specific manner of determining the mapping point for the determined concave area is:
S411, determining the lowest point of the concave surface area based on the determined horizontal standard plane, decomposing the concave surface area into a plurality of point positions, sequentially determining the vertical distances between different point positions and the horizontal standard plane, selecting the maximum vertical distance, determining the point position, and calibrating the point position as the lowest point, wherein the lowest point is the point position farthest from the horizontal standard plane, namely the point position corresponding to the maximum vertical distance;
and S412, calibrating the lowest point of the concave surface area as a mapping point of the area, and synchronously marking the mapping point in the terrain three-dimensional model.
6. The intelligent mapping method for architectural design according to claim 3, wherein in the step S4, the specific manner of determining the mapping point for the determined convex area is:
For a convex region of no less than three groups:
S421, randomly selecting a group of convex areas from the inner edge of the local terrain three-dimensional model as a main area, taking the main area as a center, determining two groups of convex areas closest to the main convex area, generating a group of area sets, wherein three groups of convex areas in the area sets cannot be positioned on the same horizontal line, processing other convex areas as the main area in the same mode, generating a plurality of area sets, and the convex areas in each area set cannot be completely overlapped;
S422, determining relative center points of different convex areas in the area set, namely randomly selecting a group of points from the edges of the convex areas as initial points, confirming the related point with the farthest distance from the initial point from the edges of the convex areas, calibrating the related point as opposite points, determining line segments of the initial point and the opposite points, and taking the center point of the line segment as the relative center point of the convex area.
7. The intelligent mapping method for architectural design according to claim 6, wherein in the step S4, the specific manner of determining the mapping point for the determined convex area further comprises:
Connecting the relative center points of different convex areas belonging to the same area set, determining a group of triangles to be analyzed, selecting the longest line segment from three groups of side lines of the triangles to be analyzed, determining the opposite triangular point of the longest line segment, starting from the triangular point, making the perpendicular line of the longest line segment, selecting the center point of the perpendicular line as the mapping point of the area set, synchronously marking the mapping point in a terrain three-dimensional model, sequentially determining the mapping points of other area sets, and marking a plurality of determined groups of mapping points in the terrain three-dimensional model.
8. The intelligent mapping method for architectural design according to claim 6, wherein in the step S4, the specific manner of determining the mapping point for the determined convex area further comprises:
taking the relative center point as the center of a circle, taking the line segment as the diameter, making a group of characteristic circles belonging to the convex surface area, uniformly dividing each characteristic circle into four equal parts, outwards extending the four groups of characteristic circles, locking extension lines, enabling the distances of the extension lines not to exceed the terrain surface of the local terrain three-dimensional model, enabling the three groups of characteristic circles to rotate, enabling the rotation speeds of the characteristic circles to be different, enabling the rotation speeds of the three groups of characteristic circles to have no common divisor, confirming the intersection areas generated by the extension lines of the three groups of characteristic circles based on the rotation process, locking the maximum intersection area based on the rotation process, directly determining the center point of the maximum intersection area, and calibrating the center point as the mapping point of the local area set.
9. An intelligent mapping method for architectural design according to claim 3, wherein,
For convex region < three groups:
The mapping points are not required to be determined specifically, and the confirmation mode of the mapping points is just the original confirmation mode, and can be confirmed by operators or on-site confirmation by mapping staff.
10. The intelligent mapping method for architectural design of claim 1, further comprising the steps of:
S5, based on the confirmed mapping points in the local terrain three-dimensional model, operators conduct preferential mapping, free mapping is conducted on the unmeasured area, and relevant points are confirmed by the operators.
Priority Applications (1)
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