An intelligent surveying and mapping method for architectural design

Abstract

The present invention discloses an intelligent surveying and mapping method for architectural design, which relates to the technical field of architectural surveying and mapping, and solves the problem of not locking the best surveying and mapping point according to the actual surface features of the building area. The present invention determines the surveying and mapping point of the concave area by determining its lowest point, which is convenient for subsequent surveying and mapping processing; for the convex area, in order to ensure that the determined surveying and mapping points can achieve the best coverage surveying and mapping effect, three groups of convex areas are taken as a group of area sets, and then the best surveying and mapping points in the area sets are determined by determining triangles or rotating circles. Subsequently, these surveying and mapping points are used for surveying and mapping processing to ensure specific surveying and mapping effects, while reducing surveying and mapping time, which is convenient for subsequent surveying and mapping personnel.

Description

Technical Field

[0001] The present invention relates to the technical field of architectural surveying and mapping, and in particular to an intelligent surveying and mapping method for architectural design. Background Art

[0002] Surveying and mapping is based on computer technology, optoelectronic technology, network communication technology, space science, and information science, with the Global Navigation Satellite System (GNSS), remote sensing (RS), and geographic information system (GIS) as its core technologies. It selects existing feature points and boundaries on the ground and uses measurement methods to obtain graphics and locations that reflect the current status of the ground and related information for use in engineering construction, planning and design, and administrative management.

[0003] The application with announcement number CN116295300B relates to the field of surveying and mapping technology, specifically an intelligent building surveying and mapping method. An intelligent building surveying and mapping method, comprising the following steps; SS001, the support mechanism is arranged at the designated measurement location of the building wall. After the arrangement, the swing arm assembly drives the three-dimensional grating scanner to move along the set surveying and mapping trajectory according to the setting of the central control host with the set parameters. After the three-dimensional grating scanner moves along the set trajectory, the point cloud data and panoramic image of the surface contour of the building are obtained, thereby constructing a three-dimensional model of the surveyed building. After the three-dimensional model of the building is established. The beneficial effect of the present invention is that the surveying and mapping method can complete the automatic surveying and mapping operation of the building through the setting of the surveying and mapping assembly, the rail frame and the support mechanism, and the spatial surveying and mapping position, spatial surveying angle and spatial surveying and mapping trajectory of the surveying and mapping assembly can be quickly changed through the swing arm assembly and the rail frame during the surveying and mapping operation.

[0004] During the specific surveying and mapping process of the relevant building area, the relevant surveying and mapping points are generally determined by the operator. The surveying and mapping points are confirmed based on personal experience. If there are multiple convex areas, multiple different surveying and mapping points need to be determined to survey the area. In the actual processing process, this surveying and mapping method is a waste of time and energy, and it will affect the surveying and mapping efficiency. The best surveying and mapping points are not locked according to the actual surface characteristics of the building area to facilitate the surveying and mapping work of the surveying and mapping personnel. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides an intelligent surveying and mapping method for architectural design, which solves the problem of not locking the best surveying and mapping points according to the actual surface features of the building area.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: an intelligent surveying and mapping method for architectural design, comprising the following steps:

[0007] S1), based on the relevant images of the corresponding building related design area, generate a terrain stereo model belonging to the related design area through the set three-dimensional stereo model;

[0008] S2), based on the determined terrain stereo model, determine the terrain surface from the local terrain stereo model, divide the terrain surface into a plurality of analysis base surfaces, and determine the uneven area and the flat area based on different slope data of different analysis base surfaces, including:

[0009] S21. Determine the terrain surface from the terrain stereo model, divide the ground surface into a number of analysis base surfaces of equal area, determine the slope data of each different analysis base surface from the terrain stereo model, and calibrate it as PD i , where i represents different analysis bases. Since there may be multiple slope data in a single analysis base, its maximum value can be directly determined and calibrated as PD i ;

[0010] S22, the slope data PD i Compare with the preset interval, where the endpoint values ​​of the preset interval are all preset values. If PD i ∈ preset interval, then the analysis base surface is marked as a flat base surface. Then the analysis base surface is marked as an uneven base surface;

[0011] S23, calibrating a plurality of interconnected flat base surfaces as the same flat region, calibrating an interconnected uneven base surface as the same uneven region, and if there is no interconnection, calibrating the peripheral region of the corresponding analysis base surface as the relevant region of the current analysis base surface;

[0012] S3) confirming the height difference of the determined uneven area, determining the relevant height difference of the uneven area by combining it with the nearest flat area around it, and marking the uneven area as a concave area or a convex area and a relative standard area, including:

[0013] S31, determining a plurality of groups of intersection lines of different heights between the uneven area and the surrounding flat areas, determining the highest intersection line as a reference line, and constructing a group of horizontal standard surfaces based on the reference line;

[0014] S32, segmenting the uneven area based on the horizontal standard surface, marking the area above the horizontal standard surface as a high area, and marking the area below the horizontal standard surface as a low area:

[0015] Identify the highest vertical distance CZ1 between the height area and the horizontal standard surface: decompose the height area into several points, use these points as perpendicular lines to the horizontal standard surface, determine the vertical distances between different points and the horizontal standard surface, and select the maximum value CZ1 from several vertical distances;

[0016] Re-identify the highest vertical distance CZ2 between the low-degree area and the horizontal standard surface: divide the low-degree area into several points, use these points as perpendicular lines to the horizontal standard surface, determine the vertical distances between different points and the horizontal standard surface, and select the maximum value CZ2 from several vertical distances;

[0017] Compare CZ1 determined by different height regions with the preset value Y1: when CZ1 ≥ Y1, mark this height region as a convex region;

[0018] Compare CZ2 determined by different low-degree areas with the preset value Y2: when CZ2≥Y2, mark this low-degree area as a concave area, where Y1 and Y2 are both preset values; if CZ1 or CZ2 does not meet: CZ1≥Y1 or CZ2≥Y2, mark this high-degree area or low-degree area as a relative standard area;

[0019] S4), based on the convex area or concave area marked in the local topographic stereoscopic model, different processing methods are used to determine the surveying and mapping points for different types of areas, and the determined surveying and mapping points are marked in the local topographic stereoscopic model.

[0020] Preferably, for the determined concave area, the specific method of determining its mapping points is:

[0021] S411, based on the determined transverse horizontal standard surface, determine the lowest point of the concave area, decompose the concave area into a number of points, and confirm the vertical distances between different points and the transverse horizontal standard surface in turn, select the point with the maximum vertical distance and determine its position, and mark it as the lowest point, the lowest point is the point farthest from the transverse horizontal standard surface, that is, the point corresponding to the maximum vertical distance;

[0022] S412, marking the lowest point of the concave area as the surveying point of the area, and synchronously marking it in the terrain three-dimensional model.

[0023] Preferably, for the determined convex area, the specific method of determining its mapping points is:

[0024] For convex areas ≥ three groups:

[0025] S421, randomly selecting a group of convex areas from the inner edge of the local topographic stereoscopic model as the main area, and then taking the main area as the center, determining two groups of convex areas that are closest to the convex area to generate a group of area sets, and the three groups of convex areas in the area set cannot be located on the same horizontal line, and then taking other convex areas as the main area, using the same method to process, to generate a number of area sets, and the convex areas in each area set cannot completely overlap;

[0026] S422, determining the relative center points of different convex areas in the area set: randomly selecting a group of points from the edge of the convex area as initial points, then confirming the related points on the edge of the convex area that are farthest from the initial points, marking them as opposite points, determining the line segment between the initial point and the opposite point, and then taking the center point of the line segment as the relative center point of the convex area.

[0027] As a first implementation of step S423, the specific method of determining the surveying and mapping points also includes:

[0028] Connect the relative center points of different convex areas belonging to the same area set to determine a group of triangles to be analyzed, select the longest line segment from the three groups of side lines of the triangles to be analyzed, and determine the triangle point opposite to the longest line segment. Starting from the triangle point, draw a perpendicular line to the longest line segment, select the center point of the perpendicular line as the surveying point of this area set, and mark this surveying point synchronously in the terrain stereo model, then confirm the surveying points of other area sets in turn, and mark the confirmed groups of surveying points in the terrain stereo model.

[0029] As a second implementation of step S423, the specific method of determining the surveying and mapping points also includes:

[0030] With this relative center point as the center of the circle and this line segment as the diameter, a set of characteristic circles belonging to this convex area is made, and each characteristic circle is divided into four equal parts, and the four groups of equal division lines are extended outward and the extension lines are locked, and the distance of the extension lines does not exceed the topographic surface of the local three-dimensional model, so that the three groups of characteristic circles are rotated, and the rotation speed of each group of characteristic circles is different, and there is no common divisor for the three groups of rotation speeds. Based on the rotation process, the intersection area generated by several groups of extension lines is confirmed, and the intersection area is the common area generated by the extension lines corresponding to the three groups of characteristic circles, and based on the rotation process, the maximum intersection area is locked, and the center point of this maximum intersection area is directly determined, and this center point is marked as the surveying and mapping point of this area set;

[0031] S5. Based on several surveying points confirmed in the local topographic stereo model, the operator conducts priority surveying and then conducts free surveying of the unsurveyed areas, and the relevant points are confirmed by the operator himself.

[0032] The present invention provides an intelligent surveying and mapping method for architectural design. Compared with the prior art, it has the following advantages:

[0033] Beneficial effects:

[0034] The present invention classifies the building area initially, and then determines the concave area and the convex area according to the surface characteristics of the area, and classifies the area according to the relevant characteristics of the relevant area, so as to facilitate the determination of the subsequent relevant surveying and mapping points;

[0035] For concave areas, the surveying and mapping points are determined by determining their lowest points, which facilitates subsequent surveying and mapping processing;

[0036] For convex areas, in order to ensure that the determined surveying and mapping points can achieve the best coverage surveying and mapping effect, the three groups of convex areas are taken as a group of area sets, and then the method of determining triangles or rotating circles is adopted to determine the best surveying and mapping points in the area set. Subsequently, this surveying and mapping point is used for surveying and mapping processing to ensure the specific surveying and mapping effect, while reducing the surveying and mapping time and facilitating the surveying and mapping work of subsequent surveying and mapping personnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a schematic diagram of the process of the present invention;

[0038] Figure 2 This is a schematic diagram of a first method for confirming a surveying point in step S423 of the present invention;

[0039] Figure 3 This is a schematic diagram of a second method for confirming surveying points in step S423 of the present invention. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] Embodiment 1

[0042] See also Figure 1 , the present application provides an intelligent surveying and mapping method for architectural design, comprising the following steps:

[0043] S1), based on the relevant images of the corresponding building-related design area, a terrain stereo model belonging to the relevant design area is generated through a set three-dimensional model, wherein the acquired relevant images can be obtained from cloud big data, or can be extracted based on the relevant images surveyed and mapped by drones. Since the method of generating the relevant terrain stereo model based on the relevant images is common knowledge, it will not be described in detail here. Generally, based on the acquired high-definition images, the relevant three-dimensional model can generate the relevant stereo model of this area based on the high-definition images and the collected elevation data. This part of the relevant stereo model is a rough model, and it is still necessary to go through the subsequent relevant surveying and mapping process to optimize such stereo model. The three-dimensional model has a powerful three-dimensional model construction function, and can also confirm the relevant contour surface data of the corresponding terrain through the relevant images to construct the relevant stereo model of the local terrain;

[0044] S2), based on the determined terrain stereo model, determine the terrain surface from the local terrain stereo model, divide the terrain surface into a plurality of analysis base surfaces, and determine the uneven area and the flat area based on different slope data of different analysis base surfaces, wherein the specific method of determining is:

[0045] S21. Determine the terrain surface from the terrain stereo model (that is, the model surface of this model. Since the model is three-dimensional, its surface is determined in order to identify the relevant slope of its surface area). Divide the ground surface into a number of analysis base surfaces with the same area (the specific area of ​​the division is prepared in advance by the operator). Determine the slope data of each different analysis base surface from the terrain stereo model and calibrate it as PD. i , where i represents different analysis bases. Since there may be multiple slope data in a single analysis base, its maximum value can be directly determined and calibrated as PD i ;

[0046] S22, the slope data PD i Compare with the preset interval, where the endpoint values ​​of the preset interval are preset values, and the specific values ​​are determined by the operator based on experience. i ∈ preset interval, then the analysis base surface is marked as a flat base surface. Then the analysis base surface is marked as an uneven base surface;

[0047] S23, calibrating several interconnected flat base surfaces as the same flat area, calibrating interconnected uneven base surfaces as the same uneven area, if there is no interconnection, then taking the peripheral area of ​​the corresponding analysis base surface as the relevant area of ​​the current analysis base surface for calibration (for example: if there is a group of flat base surfaces in the middle, and the surrounding areas are all uneven base surfaces, the surrounding uneven areas surround the current flat area, so the external peripheral area can be taken as the relevant area of ​​the current base surface, and the calibration is completed simultaneously);

[0048] S3), confirming the height difference of the determined uneven area, determining the relevant height difference of the uneven area by combining it with the nearest flat area around it, and marking the uneven area as a concave area or a convex area and a relative standard area, wherein the specific method of determination is:

[0049] S31, determining a plurality of groups of intersection lines of different heights between the uneven area and the surrounding flat areas, determining the highest intersection line as a reference line, and constructing a group of horizontal standard surfaces based on the reference line;

[0050] S32, segmenting the uneven area based on the horizontal standard surface, marking the area above the horizontal standard surface as a high area, and marking the area below the horizontal standard surface as a low area:

[0051] Identify the highest vertical distance CZ1 between the height area and the horizontal standard surface: decompose the height area into several points, use these points as perpendicular lines to the horizontal standard surface, determine the vertical distances between different points and the horizontal standard surface, and select the maximum value CZ1 from several vertical distances;

[0052] Re-identify the highest vertical distance CZ2 between the low-degree area and the horizontal standard surface: divide the low-degree area into several points, use these points as perpendicular lines to the horizontal standard surface, determine the vertical distances between different points and the horizontal standard surface, and select the maximum value CZ2 from several vertical distances;

[0053] Compare CZ1 determined by different height areas with the preset value Y1: when CZ1 ≥ Y1, mark this height area as a convex area, otherwise, mark this height area as a relative standard area;

[0054] Compare CZ2 determined by different low-degree areas with the preset value Y2: when CZ2 ≥ Y2, the low-degree area is marked as a concave area, otherwise, the low-degree area is marked as a relatively standard area, where Y1 and Y2 are both preset values, and their specific values ​​are determined by the operator based on experience;

[0055] Specifically, when the uneven area is identified, it is necessary to determine whether it belongs to a high area or a low area based on the surrounding flat base surface. In the subsequent specific surveying and mapping process, different surveying and mapping methods are required for different areas. The best way to determine the high and low difference area is to use the nearest plane in the surrounding area as the reference plane to determine the relevant area with a height difference from the reference plane. If the height difference value is too large, it is necessary to calibrate the convex area or the concave area, so as to facilitate the subsequent surveying and mapping of different types of areas.

[0056] S4), based on the convex area or concave area marked in the local topographic stereo model, for different types of areas, different processing methods are used to determine the surveying and mapping points, and the determined surveying and mapping points are marked in the local topographic stereo model, wherein the specific method for determining is:

[0057] For concave areas:

[0058] S411, based on the determined transverse horizontal standard surface, determine the lowest point of the concave area, decompose the concave area into a number of points, and confirm the vertical distances between different points and the transverse horizontal standard surface in turn, select the point with the maximum vertical distance and determine its position, and mark it as the lowest point, the lowest point is the point farthest from the transverse horizontal standard surface, that is, the point corresponding to the maximum vertical distance;

[0059] S412, marking the lowest point of the concave area as the surveying and mapping point of the area, and synchronously marking it in the terrain stereo model; specifically, for the relevant surveying and mapping of the concave area, when surveying the external plane area, it is impossible to survey and map the relevant parameters of the concave area, so it is necessary to select the lowest point of the area to determine the relevant surveying and mapping parameters of the concave area, so as to ensure its surveying and mapping accuracy;

[0060] For convex area < three groups:

[0061] There is no need to determine the surveying and mapping points specifically. The confirmation method of the surveying and mapping points can be the same as the original confirmation method, which can be confirmed by the operator or by the surveying and mapping personnel on site.

[0062] For convex areas ≥ three groups:

[0063] S421. A group of convex areas are randomly selected from the inner edge of the local topographic stereoscopic model as the main area, and then the two groups of convex areas closest to the convex area are determined with the main area as the center to generate a group of area sets, and the three groups of convex areas in the area set cannot be located on the same horizontal line (that is, the three groups of convex areas must generate a relative encirclement, that is, there is a group of encircling areas between the three groups of convex areas), and then other convex areas are taken as the main areas and processed in the same way to generate several area sets, and the convex areas in each area set cannot completely overlap (for example: Figure 2 As shown, starting from area A, area B or area C is selected, then the three groups of areas A, B, and C are a group of area sets. Then, when starting from B, area A or area C will also be selected. Because this area set has been selected, it is necessary to determine a group of D areas to determine a group of area sets. Areas B, C, and D are a group of area sets. Later, based on area C, areas CDE can be determined as a group of area sets);

[0064] S422, determining the relative center points of different convex areas in the area set: randomly selecting a group of points from the edge of the convex area as initial points, then confirming the related points on the edge of the convex area that are farthest from the initial points, marking them as opposite points, determining the line segment between the initial point and the opposite point, and then taking the center point of the line segment as the relative center point of the convex area;

[0065] S423, connecting the relative center points of different convex areas belonging to the same area set to determine a group of triangles to be analyzed, selecting the longest line segment from the three groups of side lines of the triangles to be analyzed, and determining the triangle point opposite to the longest line segment, starting from the triangle point, drawing a perpendicular line of the longest line segment, selecting the center point of the perpendicular line as the surveying and mapping point of the area set, and synchronously marking the surveying and mapping point in the terrain stereo model, and then confirming the surveying and mapping points of other area sets in turn, and marking the confirmed groups of surveying and mapping points in the terrain stereo model;

[0066] Example: Combination Figure 2 , a set of regions is proposed as the ABC set, and the line segments of three different convex regions A, B and C are confirmed, and the relative center points of their line segments are confirmed simultaneously, and then the relative center points of the three regions are connected to determine a set of triangles to be analyzed. From the triangles to be analyzed, the longest line segment is selected, and then the surveying point is selected based on the longest line segment and the opposite point. This surveying point can achieve effective surveying of the three sets of convex regions.

[0067] Specifically, for several groups of convex areas that exist, the determined surveying points are the best surveying points. When the surveying points are surveyed at the side positions, the surveyed convex areas can be maximized. Multiple different convex areas can be surveyed simultaneously. Compared with the method in which operators select surveying points by themselves, the surveying speed is faster, the effect is better, and better surveying effects can be achieved.

[0068] S5. Based on several surveying points confirmed in the local topographic stereo model, the operator conducts priority surveying and then conducts free surveying of the unsurveyed areas, and the relevant points are confirmed by the operator himself.

[0069] Embodiment 2

[0070] In the specific implementation process of this embodiment, compared with the first embodiment, there is another method for determining the surveying and mapping points of the convex area:

[0071] For convex areas ≥ three groups:

[0072] S421, randomly selecting a group of convex areas from the inner edge of the local topographic stereoscopic model as the main area, and then taking the main area as the center, determining two groups of convex areas that are closest to the convex area to generate a group of area sets, and the three groups of convex areas in the area set cannot be located on the same horizontal line, and then taking other convex areas as the main area, using the same method to process, to generate a number of area sets, and the convex areas in each area set cannot completely overlap;

[0073] S422, determining the relative center points of different convex areas in the area set: randomly selecting a group of points from the edge of the convex area as initial points, then confirming the related points on the edge of the convex area that are farthest from the initial points, marking them as opposite points, determining the line segment between the initial point and the opposite point, and then taking the center point of the line segment as the relative center point of the convex area;

[0074] S423, Combination Figure 3 , using this relative center point as the center of the circle and this line segment as the diameter, make a set of characteristic circles belonging to this convex area, and divide each characteristic circle into four equal parts, extend the four groups of equal division lines outward and lock the extension lines, the distance of the extension lines does not exceed the topographic surface of the local three-dimensional model, so that the three groups of characteristic circles rotate, and the rotation speed of each group of characteristic circles is different, and there is no common divisor for the three groups of rotation speeds (such as: the three groups of rotation speeds are 13, 14 and 15 respectively, then there is no common divisor for these three groups of speeds, only a common multiple), based on the rotation process, confirm the intersection area generated by several groups of extension lines, and the intersection area is the common area generated by the extension lines corresponding to the three groups of characteristic circles, and based on the rotation process, lock the maximum intersection area, directly determine the center point of this maximum intersection area, and mark this center point as the surveying and mapping point of this area set;

[0075] The center point of the irregular region can be confirmed by using a segmentation method. Since the method of confirming the center point of the irregular region is common knowledge, it will not be described in detail here.

[0076] Embodiment 3

[0077] The specific implementation process of this embodiment includes the entire implementation process of the above two groups of embodiments.

[0078] Some of the data in the above formulas are dimensionless and numerically calculated. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0079] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An intelligent surveying and mapping method for architectural design, characterized in that: The following steps are involved: S1), based on the relevant images of the corresponding building related design area, generate a terrain stereo model belonging to the related design area through the set three-dimensional stereo model; S2), based on the determined terrain stereo model, determine the terrain surface from the local terrain stereo model, divide the terrain surface into a plurality of analysis base surfaces, and determine the uneven area and the flat area based on different slope data of different analysis base surfaces; S3), confirming the height difference of the determined uneven area, determining the relevant height difference of the uneven area by combining it with the nearest flat area around it, and marking the uneven area as a concave area or a convex area and a relative standard area; S4), based on the convex area or concave area marked in the local topographic stereoscopic model, different processing methods are used to determine the surveying and mapping points for different types of areas, and the determined surveying and mapping points are marked in the local topographic stereoscopic model.

2. The intelligent surveying and mapping method for architectural design according to claim 1, characterized in that: In step S2, the specific method of determining the uneven area and the flat area includes: S21. Determine the terrain surface from the terrain stereo model, divide the ground surface into a number of analysis base surfaces of equal area, determine the slope data of each different analysis base surface from the terrain stereo model, and calibrate it as PD i , where i represents different analysis bases. Since there may be multiple slope data in a single analysis base, its maximum value can be directly determined and calibrated as PD i ; S22, the slope data PD i Compare with the preset interval, where the endpoint values ​​of the preset interval are all preset values. If PD i ∈ preset interval, then the analysis base surface is marked as a flat base surface. If the interval is preset, the analysis base surface is marked as an uneven base surface; S23, calibrating several interconnected flat base surfaces as the same flat area, calibrating interconnected uneven base surfaces as the same uneven area, and if there is no interconnection, calibrating the outer area of ​​the corresponding analysis base surface as the relevant area of ​​the current analysis base surface.

3. The intelligent surveying and mapping method for architectural design according to claim 1, characterized in that: In step S3, the specific method of marking the uneven area as a concave area or a convex area and a relative standard area includes: S31, determining a plurality of groups of intersection lines of different heights between the uneven area and the surrounding flat areas, determining the highest intersection line as a reference line, and constructing a set of horizontal standard surfaces based on the reference line; S32, segmenting the uneven area based on the horizontal standard surface, marking the area above the horizontal standard surface as a high area, and marking the area below the horizontal standard surface as a low area: Identify the highest vertical distance CZ1 between the height area and the horizontal standard surface: decompose the height area into several points, use these points as perpendicular lines to the horizontal standard surface, determine the vertical distances between different points and the horizontal standard surface, and select the maximum value CZ1 from several vertical distances; Re-identify the highest vertical distance CZ2 between the low-degree area and the horizontal standard surface: divide the low-degree area into several points, use these points as perpendicular lines to the horizontal standard surface, determine the vertical distances between different points and the horizontal standard surface, and select the maximum value CZ2 from several vertical distances; Compare CZ1 determined by different height regions with the preset value Y1: when CZ1 ≥ Y1, mark this height region as a convex region; The CZ2 determined for different low-degree areas is compared with the preset value Y2: when CZ2 ≥ Y2, the low-degree area is marked as a concave area, wherein Y1 and Y2 are both preset values.

4. The intelligent surveying and mapping method for architectural design according to claim 3, characterized in that: When CZ1 or CZ2 does not satisfy: CZ1≥Y1 or CZ2≥Y2, this high-altitude area or low-altitude area is calibrated as a relative standard area.

5. The intelligent surveying and mapping method for architectural design according to claim 3, characterized in that: In step S4, for the determined concave area, the specific method of determining its mapping points is: S411, based on the determined transverse horizontal standard surface, determine the lowest point of the concave area, decompose the concave area into a number of points, and confirm the vertical distances between different points and the transverse horizontal standard surface in turn, select the point with the maximum vertical distance and determine its position, and mark it as the lowest point, the lowest point is the point farthest from the transverse horizontal standard surface, that is, the point corresponding to the maximum vertical distance; S412, marking the lowest point of the concave area as the surveying point of the area, and synchronously marking it in the terrain three-dimensional model.

6. The intelligent surveying and mapping method for architectural design according to claim 3, characterized in that: In step S4, for the determined convex area, the specific method of determining its mapping points is: For convex areas ≥ three groups: S421, randomly selecting a group of convex areas from the inner edge of the local topographic stereoscopic model as the main area, and then taking the main area as the center, determining two groups of convex areas that are closest to the convex area to generate a group of area sets, and the three groups of convex areas in the area set cannot be located on the same horizontal line, and then taking other convex areas as the main area, using the same method to process, to generate a number of area sets, and the convex areas in each area set cannot completely overlap; S422, determining the relative center points of different convex areas in the area set: randomly selecting a group of points from the edge of the convex area as initial points, then confirming the related points on the edge of the convex area that are farthest from the initial points, marking them as opposite points, determining the line segment between the initial point and the opposite point, and then taking the center point of the line segment as the relative center point of the convex area.

7. The intelligent surveying and mapping method for architectural design according to claim 6, characterized in that: In step S4, for the determined convex area, the specific method of determining the surveying and mapping points thereof also includes: Connect the relative center points of different convex areas belonging to the same area set to determine a group of triangles to be analyzed, select the longest line segment from the three groups of side lines of the triangles to be analyzed, and determine the triangle point opposite to the longest line segment. Starting from the triangle point, draw a perpendicular line to the longest line segment, select the center point of the perpendicular line as the surveying point of this area set, and mark this surveying point synchronously in the terrain stereo model, then confirm the surveying points of other area sets in turn, and mark the confirmed groups of surveying points in the terrain stereo model.

8. The intelligent surveying and mapping method for architectural design according to claim 6, characterized in that: In step S4, for the determined convex area, the specific method of determining the surveying and mapping points thereof also includes: With this relative center point as the center of the circle and this line segment as the diameter, make a set of characteristic circles belonging to this convex area, and divide each characteristic circle into four equal parts, extend the four sets of equal division lines outward and lock the extension lines, and the distance of the extension lines does not exceed the terrain surface of the local three-dimensional model, so that the three sets of characteristic circles are rotated, and the rotation speed of each set of characteristic circles is different, and there is no common divisor for the three sets of rotation speeds. Based on the rotation process, the intersection areas generated by several sets of extension lines are confirmed, and the intersection areas are the common areas generated by the extension lines corresponding to the three sets of characteristic circles, and based on the rotation process, the maximum intersection area is locked, and the center point of the maximum intersection area is directly determined, and this center point is marked as the surveying and mapping point of this area set.

9. The intelligent surveying and mapping method for architectural design according to claim 3, characterized in that: For convex area < three groups: There is no need to determine specific surveying and mapping points. The surveying and mapping points can be confirmed in the original way, either by operators or on-site by surveying and mapping personnel.

10. The intelligent surveying and mapping method for architectural design according to claim 1, characterized in that: The following steps are also included: S5. Based on several surveying points confirmed in the local topographic stereo model, the operator conducts priority surveying and then conducts free surveying of the unsurveyed areas, and the relevant points are confirmed by the operator himself.

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