Road area calculation method, device, computer equipment and storage medium

Abstract

Embodiments of the present application provide a road area calculation method, device, computer device, and storage medium, which relate to the technical field of geographic information processing. Based on the map data of the area to be counted, the present application obtains the original vector data of each road in the area to be counted, and the original vector data includes: the annotation point information of each road and the road surface information; according to the annotation point information and the road surface information of each road, update the original vector data of each road to obtain the updated vector data of each road; according to the annotation point information of each road, obtain the file data of each road; according to the file data of each road and the updated vector data of each road, calculate the area of each road. It can calculate the areas of various types of roads and facilities based on the vector data, and can also obtain the areas of road types that are difficult to identify through satellite map image data through the file data, improving the accuracy of road area calculation.

Description

Technical Field

[0001] The present application relates to the technical field of geographic information processing, and more particularly, to a method, device, computer device, and storage medium for calculating road area. Background Art

[0002] In urban roads, to ensure traffic order, aesthetics, etc., there are generally various types of roads and facilities, such as channelization islands, green belts, roadways, sidewalks, etc. When conducting a road census, it is necessary to classify, process, and summarize the areas of the above-mentioned various roads or facilities. However, due to the high complexity of modern urban roads and the problem of overlapping roads and facilities, it is difficult for road surveying and mapping personnel to obtain accurate statistical results.

[0003] In the prior art, generally, by identifying and extracting satellite map image data, the image of the road is obtained, and then the road area is estimated based on this.

[0004] However, this method of estimating road area cannot accurately classify and estimate the overlapping roads and facilities on the road. Moreover, it is difficult to estimate the paving area of roads paved in a special way only through satellite map image data. Summary of the Invention

[0005] The objectives of the present application include, for example, providing a method, device, computer device, and storage medium for calculating road area, which can calculate the areas of various types of roads and facilities based on vector data, and can also obtain the areas of road types that are difficult to identify through satellite map image data through archive data, improving the accuracy of road area calculation.

[0006] The embodiments of the present application can be implemented as follows:

[0007] In a first aspect, the present application provides a method for calculating road area, the method including:

[0008] Based on the map data of the area to be statistically analyzed, obtain the original vector data of each road in the area to be statistically analyzed, where the original vector data includes: the annotation point information of each road and the road surface information;

[0009] According to the annotation point information of each road and the road surface information, update the original vector data of each road to obtain the updated vector data of each road;

[0010] According to the annotation point information of each road, obtain the archive data of each road;

[0011] According to the archive data of each road and the updated vector data of each road, calculate the area of each road.

[0012] In an alternative embodiment, updating the original vector data of each road according to the annotation point information and the road surface information of each road to obtain the updated vector data of each road includes:

[0013] Classifying the annotation point information of each road according to the satellite image in the original vector data of each road to obtain the classified annotation point information, and updating the annotation point information in the original vector data of each road according to the classified annotation point information to obtain the updated annotation point information of each road;

[0014] Determining the road surface type and boundary information of each road according to the satellite image in the original vector data of each road, the road surface information of each road, and the classified annotation point information, and updating the road surface information in the original vector data of each road according to the road surface type and boundary information of each road to obtain the updated road surface information of each road.

[0015] In an alternative embodiment, classifying the annotation point information of each road according to the satellite image in the original vector data of each road to obtain the classified annotation point information includes:

[0016] Performing image recognition on the satellite image in the original vector data, and classifying the annotation point information of each road according to the image recognition result to obtain the classified annotation point information, where the classified annotation point information includes: crossroads annotation point information and non-crossroads annotation point information.

[0017] In an alternative embodiment, classifying the annotation point information of each road according to the image recognition result to obtain the classified annotation point information includes:

[0018] If the annotation point information of the first road, the second road, the third road, and the fourth road is crossroads annotation point information, then determine the marking method of the annotation point information inside the crossroads according to the widths of the roads corresponding to the annotation point information. The first road and the second road are co-planar roads in the same direction, the third road and the fourth road are co-planar roads in the same direction, and the first road and the second road respectively intersect with the third road and the fourth road at a crossroads.

[0019] In an alternative embodiment, determining the marking method of the annotation point information inside the crossroads according to the widths of the roads corresponding to the annotation point information includes:

[0020] If the width of the first road is greater than the width of the third road, or the width of the second road is greater than the width of the fourth road, then determine that the marking method of the annotation point information within the intersection is the single main road marking method;

[0021] If the width of the first road is equal to the width of the third road, and the width of the second road is equal to the width of the fourth road, then determine that the marking method of the annotation point information within the intersection is the double main road marking method.

[0022] In an alternative embodiment, the determining the road surface type and boundary information of each road according to the satellite image in the original vector data of each road, the road surface information of each road, and the classified annotation point information includes:

[0023] Identify the satellite image in the original vector data, and classify the road surface information of each road according to the image recognition result and the classified annotation point information, to obtain the road surface type and boundary information of each road, where the road surface type includes: vehicle lane, sidewalk, bicycle lane, central green belt, non - central green belt, and channelization island.

[0024] In an alternative embodiment, the calculating the area of each road according to the archive data of each road and the updated vector data of each road includes:

[0025] Determine the area of each type of road sub - item of the first road according to the road surface information in the updated vector data of the first road, where the first road is any road in the area to be counted;

[0026] Determine the area of at least one permeable pavement sub - item of the first road according to the archive data of the first road;

[0027] Overlay the area of each type of road sub - item and the area of each permeable pavement sub - item to obtain the area of the first road.

[0028] In a second aspect, the present application provides a road area calculation device, and the device includes:

[0029] An acquisition module, configured to acquire the original vector data of each road within the area to be counted based on the map data of the area to be counted, where the original vector data includes: the annotation point information and road surface information of each road;

[0030] An update module, configured to update the original vector data of each road according to the annotation point information and the road surface information of each road, to obtain the updated vector data of each road;

[0031] The obtaining module is further configured to obtain the file data of each road according to the annotation point information of each road;

[0032] A calculation module, configured to calculate the area of each road according to the file data of each road and the updated vector data of each road.

[0033] The update module is specifically further configured to classify the annotation point information of each road according to the satellite image in the original vector data of each road, obtain the classified annotation point information, and update the annotation point information in the original vector data of each road according to the classified annotation point information to obtain the updated annotation point information of each road; determine the road surface type and boundary information of each road according to the satellite image in the original vector data of each road, the road surface information of each road, and the classified annotation point information, and update the road surface information in the original vector data of each road according to the road surface type and boundary information of each road to obtain the updated road surface information of each road.

[0034] The update module is specifically further configured to perform image recognition on the satellite image in the original vector data, and classify the annotation point information of each road according to the image recognition result to obtain the classified annotation point information, where the classified annotation point information includes: crossroads annotation point information and non-crossroads annotation point information.

[0035] The update module is specifically further configured to, if the annotation point information of the first road, the second road, the third road, and the fourth road is crossroads annotation point information, determine the marking method of the annotation point information inside the crossroads according to the widths of the roads corresponding to the annotation point information, where the first road and the second road are co-planar roads in the same direction, the third road and the fourth road are co-planar roads in the same direction, and the first road and the second road respectively intersect with the third road and the fourth road at a crossroads.

[0036] The update module is specifically further configured to, if the width of the first road is greater than the width of the third road, or the width of the second road is greater than the width of the fourth road, determine that the marking method of the annotation point information inside the crossroads is a single main road marking method; if the width of the first road is equal to the width of the third road, and the width of the second road is equal to the width of the fourth road, determine that the marking method of the annotation point information inside the crossroads is a double main road marking method.

[0037] The update module is further specifically configured to identify satellite images in the original vector data, and classify the road surface information of each road according to the image recognition result and the classified annotation point information, so as to obtain the road surface type and boundary information of each road. The road surface types include: carriageway, sidewalk, bicycle lane, central green belt, non-central green belt, and channelization island.

[0038] The calculation module is further specifically configured to determine the area of each type of road sub-item of the first road according to the road surface information in the updated vector data of the first road, where the first road is any road in the area to be counted; determine the area of at least one permeable pavement sub-item of the first road according to the file data of the first road; and superimpose the areas of each type of road sub-item and the areas of each permeable pavement sub-item to obtain the area of the first road.

[0039] In a third aspect, the present application provides a computer device, which includes: a processor, a storage medium, and a bus. The storage medium stores machine-readable instructions executable by the processor. When the computer device runs, the processor communicates with the storage medium through the bus, and the processor executes the machine-readable instructions to perform the steps of the road area calculation method as described in any one of the foregoing embodiments.

[0040] In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the road area calculation method as described in any one of the foregoing embodiments are implemented.

[0041] The beneficial effects of the embodiments of the present application include:

[0042] By using the road area calculation method, device, computer device, and storage medium provided by the present application, first, the present application can obtain the corresponding file data according to the annotation point information of each road. In this way, for roads paved in a special way, the area of roads paved in a special way that is difficult to directly analyze and identify from satellite map images, such as the area of roads of the permeable pavement type, can be obtained by associating with the file data, enriching the types of road areas that can be obtained and improving the accuracy of road area calculation. Second, the present application calculates the vector data in the area to be counted, respectively identifies the boundaries of the roads on each road and then classifies and processes them, avoiding the error in calculating the area of each road caused by not further classifying and processing the overlapping area in the prior art and thus undercounting or not counting this part of the area. Description of the Drawings

[0043] To more clearly illustrate the technical solutions of the embodiments of the present application, the accompanying drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present application and should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can also be obtained based on these drawings without creative efforts.

[0044] Figure 1 Schematic diagram of the step flow of the road area calculation method provided by the embodiment of the present application;

[0045] Figure 2 Another schematic diagram of the step flow of the road area calculation method provided by the embodiment of the present application;

[0046] Figure 3 Schematic diagram of non-crossing point annotation information of the road area calculation method provided by the embodiment of the present application;

[0047] Figure 4 Schematic diagram of cross-point annotation information of the road area calculation method provided by the embodiment of the present application;

[0048] Figure 5 Another schematic diagram of the step flow of the road area calculation method provided by the embodiment of the present application;

[0049] Figure 6 Schematic diagram of the single main road marking method of the road area calculation method provided by the embodiment of the present application;

[0050] Figure 7 Schematic diagram of the double main road marking method of the road area calculation method provided by the embodiment of the present application;

[0051] Figure 8 Schematic diagram of the cross-point area classification processing of the road area calculation method provided by the embodiment of the present application;

[0052] Figure 9 Another schematic diagram of the step flow of the road area calculation method provided by the embodiment of the present application;

[0053] Figure 10 Schematic diagram of the structure of the road area calculation device provided by the embodiment of the present application;

[0054] Figure 11 Schematic diagram of the structure of the computer device provided by the embodiment of the present application.

[0055] Icons: 10 - Road area calculation device; 1001 - Acquisition module; 1002 - Update module; 1003 - Calculation module; 2001 - Processor; 2002 - Memory. Detailed implementation manners

[0056] To make the objectives, technical solutions and advantages of the embodiments of this application clearer, the following will clearly and completely describe the technical solutions in the embodiments of this application with reference to the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are some, but not all, of the embodiments of this application. Usually, the components of the embodiments of this application described and illustrated in the accompanying drawings here can be arranged and designed in various different configurations.

[0057] Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of this application claimed, but merely represents selected embodiments of this application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of this application without creative efforts fall within the scope of protection of this application.

[0058] It should be noted that similar reference numerals and letters denote similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings.

[0059] In addition, terms such as "first" and "second" are used only for descriptive distinction and cannot be construed as indicating or implying relative importance.

[0060] It should be noted that, without conflict, the features in the embodiments of this application can be combined with each other.

[0061] In urban roads, obtaining the areas of various types of roads and facilities is of great significance for understanding the current situation of the special planning and development of urban traffic and evaluating the urban development. In the prior art, generally, the urban roads are estimated by identifying and extracting satellite map images. However, this method cannot accurately classify and calculate the roads and facilities in overlapping areas. Moreover, only based on the satellite map image data, only the total area of the roads can be estimated according to the shape of the roads. For roads paved in a special way, for example, roads of the permeable paving type obtained after paving with permeable concrete, permeable asphalt, permeable bricks and other permeable paving materials, it is difficult to directly obtain them from the satellite map image data, resulting in calculation deviation of the road area.

[0062] Based on this, after research, the applicant has proposed a road area calculation method, device, computer device and storage medium, which can calculate through vector data, identify the boundaries of each road and then classify and process them, and summarize the calculation, avoiding the errors in the area of each road caused by under-calculating or not calculating the overlapping part area in the prior art. It can also obtain the corresponding archive data according to the annotation point information of each road, and obtain more types of road area data by association, improving the accuracy rate of road area calculation.

[0063] The following combines multiple specific application examples to explain a road area calculation method, device, computer device, and storage medium provided by the embodiments of the present application.

[0064] To calculate the urban road area, it is necessary to separately obtain the areas of various types of road sub-items in the city. Due to the high complexity of urban roads, accurately and quickly calculating the areas of various types of road sub-items in the city and the total construction area of each road is an important means to improve the efficiency of planning and decision-making.

[0065] In this application, first, the map data within the area to be counted is extracted and manually marked to obtain the original vector data of each road within the area to be counted. The original vector data is a data structure that describes the spatial positions and shapes of landmarks such as roads, rivers, and green spaces in the map data through annotation point information, road centerline information, and road surface information, etc., and is a vector image containing coordinates, line segments, and color blocks. Optionally, the original vector data may also include satellite images, and the satellite images have a one-to-one correspondence with the above vector images in terms of position and shape. It should be noted that the original vector data can have multiple layers, such as a bottom layer, a road layer, etc.

[0066] After obtaining the annotation point information of each road, first, the annotation point information is classified. The satellite images in the original vector data can be identified and analyzed. According to the topological relationship between the shapes of the roads where each annotation point is located and the roads where other annotation points are located, the classified annotation point information is determined. Among them, the classified annotation point information can include crossroads annotation point information or non-crossroads annotation point information. For the crossroads annotation point information, the widths of the road where it is located and the other roads that intersect can be compared, and it is determined that the annotation point information in the area within the crossroads and the annotation point information of each crossroads where a cross intersection occurs are marked in the double main road crossroads annotation point marking method or the single main road crossroads annotation point marking method. Finally, the original vector data of each road can be updated according to the classified annotation point information.

[0067] Next, the satellite images in the original vector data can be identified. According to the contour shapes and colors of each facility in the satellite images, the road surface types and boundary information included in each road surface information are determined. For the crossroads road surface, the annotation point marking method of the road surface within the crossroads can also be determined according to the classified annotation point information. Then, the original vector data of each road with the updated annotation point information can be further updated, and color blocks of different colors and sizes corresponding to the road surface types and boundaries are stored in the original vector data, updating the road surface information in the original vector data.

[0068] Optionally, after updating the annotation point information and road surface information in the original vector data of each road, it is also possible to check whether the topological relationship between the road centerline information of each road and the updated annotation point information and the updated road surface information is correct. Specifically, it can be determined by checking whether the area of the road centerline is consistent with the area of the road surface information, and whether there is a corresponding relationship between the road centerline and the annotation points. Based on this, the road centerline information in the original vector data can be updated. After the road surface information, annotation point information, and road centerline information in the original vector data are updated in sequence, the updated vector data is obtained.

[0069] Then, using the annotation point information of each road in the updated vector data as the association identifier, the archive data of each road is obtained. Specifically, the archive data can be searched according to the annotation point information of each road to extract the associated archive data whose annotation point information is the same as that of the vector data from the archive data.

[0070] Table 1 Schematic Table of Road Surface Types

[0071]

[0072]

[0073] Furthermore, the road surface information of each road in the above-mentioned updated vector data is calculated to obtain the areas of various types of road sub-items. As shown in Table 1, the area of road sub-item AreaⅢ can include the area of the carriageway, sidewalk, bicycle lane, central green belt, non-central green belt, and channelization island area, etc. According to the above-mentioned associated archive data, various types of data in the archive data, such as the area of permeable pavement, are extracted and stored in the data with the same annotation point information in the updated vector data. In this way, the areas of road surface types that are difficult to directly identify from satellite images are obtained through the archive data.

[0074] Finally, the areas of the same type among the above-mentioned various types of road sub-items can be superimposed to further obtain the area of the road aggregation item. As shown in Table 1, the area of road aggregation item AreaⅡ can include the area of the carriageway, non-motor vehicle lane, green belt, channelization island area, and permeable pavement area, etc. Further superimposing the area of road aggregation item AreaⅡ can obtain the total road area AreaⅠ.

[0075] Figure 1 The figure shows the schematic flow chart of the road area calculation method provided by the embodiment of the present application. The execution subject of this method can be a computer device with computing and processing capabilities. As Figure 1 shown, this method includes:

[0076] S101. Based on the map data of the area to be counted, obtain the original vector data of each road in the area to be counted.

[0077] Among them, the original vector data includes: the annotation point information of each road and the road surface information.

[0078] The area to be counted can be a certain area within an urban block. The map data of this area can be obtained by shooting with a high-definition camera or downloading an aerial view of the street, and then through image processing and curve vectorization, or by annotation and drawing to obtain the original vector data of each road in the area to be counted. The original vector data of each road contains various types of data such as annotation point information, road center line information, and road surface information. The vector graphics displayed on the map are all obtained through mathematical formula calculations and will not be distorted regardless of zooming in, zooming out, or rotating. Generally, the vector data of each road contains multiple data structures, which are stored separately, and each data structure uses the annotation point information as the unique identification identifier.

[0079] The annotation point information of each road can be the road name of each road, which can be used to mark the boundaries of each road to determine the scope of the area where the road is located. The road surface information of each road can be the coordinates of the boundaries of each road, the represented color, etc. Optionally, when the original vector data is three-dimensional vector data, it can also include the spatial coordinates of the road surface to identify the height of the road surface.

[0080] Optionally, the original vector data can also include road center line information. The road center line is generally located in the center of the road and is consistent with the direction of the road. The road center line information can include the coordinates describing the road center line. In this application, the original vector data can also include a satellite map, and the landmarks, roads, facilities, etc. shown in the vector map described by combining the road annotation point information, road surface information, and road center line information can have a one-to-one correspondence with the satellite map.

[0081] S102. According to the annotation point information and road surface information of each road, update the original vector data of each road to obtain the updated vector data of each road.

[0082] It is possible to further classify and process the annotation point information, road surface information, and road center line information of each road included in the original vector data to obtain the updated annotation point information and updated road surface information, and then redraw the above updated annotation point information and updated road surface information on the vector map corresponding to the original vector data to obtain the updated vector data.

[0083] Optionally, after obtaining the above-updated vector data, it is also possible to check the topological relationship between the road centerline information of each road contained in the original vector data and the road surface information and centerline information in the updated vector data, and redraw the road centerline according to the road surface color in the road surface information to further update the updated vector data. Specifically, it is possible to check whether the length of the road centerline is consistent with the penetration of the road surface, whether the plane where the road centerline is located is consistent with the road surface, and whether the road centerline has a one-to-one correspondence with a certain annotation point.

[0084] S103. Obtain the archive data of each road according to the annotation point information of each road.

[0085] The annotation point information that can uniquely identify the vector data can be used as the unique association identifier to obtain the archive data of each road. Specifically, according to the annotation point information of each road, the archive data can be searched to extract the associated archive data with the same annotation point information as the vector data from the archive data.

[0086] S104. Calculate the area of each road according to the archive data of each road and the updated vector data of each road.

[0087] The area of each road part of the classified processing type road can be obtained by analyzing, identifying, and calculating the road surface information contained in the updated vector data of each road. The area of the road surface of the type that is difficult to directly analyze from the road surface information in the vector data can also be obtained according to the associated archive data, such as the area of the permeable pavement. Summing up the areas of the road surfaces of each type can obtain the total construction area of the road.

[0088] In this embodiment, by calculating the vector data and archive data, the total construction area of the road is obtained, and more data related to the road area can be obtained. It is also possible to classify and process the boundaries of each road after identification, avoiding the problem that the overlapping parts are not calculated due to unclassified processing, and improving the accuracy of the road area calculation.

[0089] Optionally, as Figure 2 shown, in the above step S102, according to the annotation point information and road surface information of each road, updating the original vector data of each road to obtain the updated vector data of each road can be implemented by the following steps S201 to S202.

[0090] S201. Classify the annotation point information of each road according to the satellite image in the original vector data of each road to obtain the classified annotation point information, and update the annotation point information in the original vector data of each road according to the classified annotation point information to obtain the updated annotation point information of each road.

[0091] Specifically, the satellite images in the original vector data can be analyzed, and according to the intersection and penetration conditions of each road in the satellite images, the annotation point information of the corresponding roads can be classified. Exemplarily, it can be determined whether a certain road intersects with other roads at intersections and whether it is coplanar with other intersections, so as to determine the classified annotation point information, where the classified annotation point information can include intersection coplanar annotation point information, non-intersection annotation point information, etc. Of course, this is not limited thereto.

[0092] According to the classification of the annotation point information, the annotation point information in the original vector data is updated to obtain updated annotation point information. For example, for the intersection coplanar annotation point information, the area within the crossroads where each intersection occurs needs to be further classified to determine how this area corresponds to the annotation point information of the intersecting roads.

[0093] After determining that all road surfaces in the original vector information correspond to the annotation point information, according to the updated annotation point information, the annotation point information in the original vector data is updated, and the newly added classification attributes are stored in the data structure of the annotation point information of each road, obtaining the updated annotation point information of each road.

[0094] S202. According to the satellite images in the original vector data of each road, the road surface information of each road, and the classified annotation point information, determine the road surface type and boundary information of each road, and update the road surface information in the original vector data of each road according to the road surface type and boundary information of each road, obtaining the updated road surface information of each road.

[0095] Optionally, the satellite images in the original vector data can also be recognized to determine the types and boundary information of various types of roads and facilities included on the road surfaces included in the road surface information of each road. Specifically, different types of roads or facility boundaries can be represented by drawing color blocks of different colors on the road surfaces. For the attribution relationship between the road surfaces of the intersection and each road, it can be determined according to the road surface type and the corresponding boundary information belonging to each road calculated from the classified annotation point information in the above steps.

[0096] According to the road surface information and annotation point information of each road corresponding to the satellite image, the color values and boundary coordinate values used to represent different color blocks can be stored in the data structure of the belonging annotation point information, completing the update of the road surface information in the vector data.

[0097] In this embodiment, by identifying the satellite images in the original vector data and further classifying the annotation point information and road surface information in the original vector information, the attribution relationships of the annotation points and road surfaces of some overlapping and intersecting road surfaces with each road are determined, so that the areas of various types of road surfaces can be obtained more accurately.

[0098] Optionally, in the above step S201, classifying the annotation point information of each road according to the satellite images in the original vector data of each road to obtain the classified annotation point information may include:

[0099] Performing image recognition on the satellite images in the original vector data, and classifying the annotation point information of each road according to the image recognition result to obtain the classified annotation point information, where the classified annotation point information includes: intersection annotation point information and non-intersection annotation point information.

[0100] By performing image recognition on the satellite images in the original vector data, it can be determined whether the annotation point information is intersection annotation point information or non-intersection annotation point information based on whether each road intersects with other roads at a cross, that is, the shape, orientation, etc. of the road.

[0101] Specifically, Figure 3 The figure shows the case where the annotation point information is non-intersection annotation point information. Among them, both A and B are non-intersection annotation point information, and each road corresponds to the annotation point information one by one.

[0102] Figure 4 The figure shows the case where the annotation point information is intersection annotation point information. Among them, A, B, C, and D are all annotation point information corresponding to different roads. Four roads intersect, and the corresponding annotation point information is all intersection annotation point information. The annotation method for the annotation point information within the intersection area generated by the intersection will be described in detail in the following embodiments.

[0103] In this embodiment, by identifying the satellite images in the original vector information, the annotation point information is classified. Thus, the areas that need to be further annotated with annotation points are screened out, avoiding omissions when calculating the road area.

[0104] Optionally, in the above embodiment, classifying the annotation point information of each road according to the image recognition result to obtain the classified annotation point information may include:

[0105] If the annotation point information of the first road, the second road, the third road, and the fourth road is intersection annotation point information, then determine the marking method of the annotation point information within the intersection according to the widths of the roads corresponding to the annotation point information.

[0106] Among them, the first road and the second road are co-planar roads in the same direction, the third road and the fourth road are co-planar roads in the same direction, and the first road and the second road intersect the third road and the fourth road at a crossroads respectively.

[0107] Optionally, continue to refer to Figure 4 , if the first road A and the second road C are co-planar in the same direction, and the third road B and the fourth road D are co-planar in the same direction, a crossroads area is generated in the area where the first road A, the second road C, the third road B, and the fourth road D intersect. It can be understood that the widths of the first road A and the second road C are generally the same, and the widths of the third road B and the fourth road D are generally the same.

[0108] Regarding how to mark the annotation points in this crossroads area, the widths of the first road A and the second road C can be first compared with the widths of the third road B and the fourth road D, and according to the result of the road width comparison, the marking method of the annotation point information in the crossroads area can be determined. For example, if the road in a certain direction is wider, a larger area in the crossroads area can be marked with the annotation point information of the wider road.

[0109] In this embodiment, the marking method of the annotation points in the crossroads is determined by the result of the width comparison of the roads where the crossroads meet. This method of determining the annotation point marking area in the crossroads area according to the road surface width can also make a more accurate segmentation of similar intersection public areas, determine their attribution relationship with each road, and thus improve the accuracy of road area calculation.

[0110] Optionally, as Figure 5 shown, in the above embodiment, according to the widths of the roads corresponding to the annotation point information, the marking method of the annotation point information in the crossroads can be realized by the following steps S301 to S302.

[0111] S301, if the width of the first road is greater than the width of the third road, or the width of the second road is greater than the width of the fourth road, then determine that the marking method of the annotation point information in the crossroads is the single main road marking method.

[0112] By comparing the road widths of the four roads in two directions of the crossroads where the intersection occurs in the satellite map of the original vector data, as Figure 6 shown, if the width of the first road A is greater than the width of the third road B, or the width of the second road C is greater than the width of the fourth road D, then it is considered that the roads in the direction where the first road A and the second road C are located are the main roads. At this time, determine that the marking method of the annotation point information in the crossroads is the single main road marking method.

[0113] Specifically, as Figure 6As shown in the figure, the single main road marking method is as follows: at the middle position within the intersection area, the direction perpendicular to the roads in the directions where the first road A and the second road C are located is denoted as the boundary line between the first road A and the second road C. This boundary line can be marked as the annotation point of the first road A, or can be marked as the annotation point of the second road C at the same time.

[0114] If the annotation point marking method is the single main road marking method, then in the road surface within the intersection area, the area of the cross-grid part is included in the carriageway area of the first road A, and the area of the diagonal part is included in the carriageway area of the second road C.

[0115] S302, if the width of the first road is equal to the width of the third road, and the width of the second road is equal to the width of the fourth road, then determine that the marking method of the annotation point information within the intersection is the double main road marking method.

[0116] If after comparing the road widths of the four roads in two directions of the intersection where the satellite maps in the original vector data meet, as Figure 7 shown, if the width of the first road A is equal to the width of the third road B, and moreover, the width of the second road C is equal to the width of the fourth road D, then it is considered that the roads where the first road A and the second road C are located and the roads where the third road B and the fourth road D are located are all main roads. At this time, determine that the marking method of the annotation point information within the intersection is the double main road marking method.

[0117] As Figure 7 shown, when the marking method of the annotation point information is the double main road marking method, the intersection area is evenly divided into four equal parts by two horizontal and vertical lines. The annotation points of each road are respectively marked on the line perpendicular to the through direction of each road, which is used to delimit the subordination relationship between the two equal parts areas connected to each road and each road. Exemplarily, the annotation point information of the first road A can be the area delimited by the line A0 perpendicular to the through direction of the first road A and the area connected to this line along the through direction of the first road A, that is, the areas represented by A0B0 and A0D0, which are the areas of the road area within the intersection area belonging to the first road A. Among them, A0B0 is the common carriageway area that belongs to both the first road A and the third road B, and A0D0 is the common carriageway area that belongs to both the first road A and the fourth road D.

[0118] In this embodiment, by comparing the widths of the roads where the cross intersections occur, determining that the marking method of the annotation point information within the intersection is the single main road marking method or the double main road marking method, and further determining the attribution relationship between the public area within the intersection area and each road, the accuracy of road area calculation is improved.

[0119] Optionally, in the above step S202, determining the road surface type and boundary information of each road based on the satellite images in the original vector data of each road, the road surface information of each road, and the classified annotation point information may include:

[0120] Identify the satellite images in the original vector data, and classify the road surface information of each road according to the image recognition results and the classified annotation point information, to obtain the road surface type and boundary information of each road. The road surface types include: carriageway, sidewalk, bicycle lane, central green belt, non - central green belt, and channelization island.

[0121] The satellite images in the original vector data can be identified. According to the shapes, colors and other features of each road and facility in the satellite images, the types of roads and boundary information in the satellite images can be determined, and are shown by drawing color blocks of different colors and sizes on the road surface.

[0122] Exemplarily, as Figure 8 shown, through the image recognition results of identifying the satellite images, the triangular area represents the channelization island at the intersection. The area A1B1 where the triangle overlaps with the public carriageway represents the public channelization island. This area is included in the channelization island area of the first road A and also included in the channelization island area of the third road B. And the area of the part where the channelization island overlaps with the first road is included in the channelization island area of the first road A, and the area of the part where the channelization island overlaps with the third road B is included in the channelization island area of the third road C.

[0123] In this embodiment, by identifying the satellite images in the original vector data, the road surface type and boundary information of each road are determined, so as to further determine the areas of various types of roads, and further combined with the range corresponding to the annotation point information, the attribution relationship between the area of the public area and each intersecting road is determined, improving the accuracy of area calculation.

[0124] Optionally, as Figure 9 shown, in the above step S104, calculating the area of each road according to the file data of each road and the updated vector data of each road can be implemented by the following steps 401 to S403.

[0125] S401, determine the area of each type of road sub - item of the first road according to the road surface information in the updated vector data of the first road, where the first road is any road in the area to be counted.

[0126] Optionally, according to the road surface information and boundary information of each type determined above, and according to the scale information, the actual areas of each type of road sub-item can be calculated respectively. As shown in Table 1, the area of road sub-item AreaⅢ can include: carriageway area, sidewalk area, bicycle lane area, central green belt area, non-central green belt area, and channelization island area. Of course, it is not limited thereto.

[0127] S402. Determine the area of at least one permeable pavement sub-item of the first road according to the archive data of the first road.

[0128] Furthermore, through the associated archive data in the above steps, the areas of road sub-items that are difficult to directly identify and calculate by satellite images can be obtained. For example, in the sidewalk or carriageway, the area of the permeable pavement sub-item paved in the permeable pavement method.

[0129] It can be understood that other information that is difficult to directly obtain from vector data can also be obtained through archive data, such as information on road construction units, construction times, maintenance responsible persons, etc. This application does not make limitations here.

[0130] S403. Superimpose the areas of each type of road sub-item and the areas of each permeable pavement sub-item to obtain the area of the first road.

[0131] After obtaining the areas of each road sub-item AreaⅢ, the areas of the same type of road sub-items can be superimposed, and the area of the road aggregation item AreaⅡ can be obtained by establishing a homogeneous aggregate in the data structure of the annotation point information of each road. Exemplarily, the carriageway area and the bicycle lane area of the same road are superimposed to obtain the non-motor vehicle area of the road; the central green belt area and the non-central green belt area of the same road are superimposed to obtain the green belt area of the road.

[0132] Furthermore, the road total area AreaⅠ can be obtained by accumulating the areas of the road aggregation items AreaⅡ.

[0133] The above calculation process can be represented by the formula AreaⅠ = ∑AreaⅡ = ∑AreaⅢ. The calculated areas of each road sub-item AreaⅢ, road aggregation item AreaⅡ, and road total area AreaⅠ can be stored as the attributes of the road center lines of each road and represented by the attributes of the road center lines. The annotation point information of each road can also be used as a unique identifier, and the road area corresponding to each road can be stored as a piece of data in the database.

[0134] In this embodiment, the areas of each type of road sub-item and the areas of the permeable pavement sub-items are calculated through vector data and archive data, and the road total area is further superimposed. In this way, accurate results of the areas of each subclass and major class of the road can be obtained.

[0135] An embodiment of the present application further provides a road area calculation device 10, as Figure 10 shown. The device includes:

[0136] An acquisition module 1001, configured to obtain the original vector data of each road in the area to be counted based on the map data of the area to be counted. The original vector data includes: the annotation point information and the road surface information of each road;

[0137] An update module 1002, configured to update the original vector data of each road according to the annotation point information and the road surface information of each road to obtain the updated vector data of each road;

[0138] The acquisition module 1001 is further configured to obtain the file data of each road according to the annotation point information of each road;

[0139] A calculation module 1003, configured to calculate the area of each road according to the file data of each road and the updated vector data of each road.

[0140] Specifically, the update module 1002 is further configured to classify the annotation point information of each road according to the satellite image in the original vector data of each road to obtain the classified annotation point information, and update the annotation point information in the original vector data of each road according to the classified annotation point information to obtain the updated annotation point information of each road; determine the road surface type and boundary information of each road according to the satellite image, the road surface information of each road, and the classified annotation point information in the original vector data of each road, and update the road surface information in the original vector data of each road according to the road surface type and boundary information of each road to obtain the updated road surface information of each road.

[0141] Specifically, the update module 1002 is further configured to perform image recognition on the satellite image in the original vector data, and classify the annotation point information of each road according to the image recognition result to obtain the classified annotation point information. The classified annotation point information includes: crossroads annotation point information and non-crossroads annotation point information.

[0142] Specifically, the update module 1002 is further configured to, if the annotation point information of the first road, the second road, the third road, and the fourth road is crossroads annotation point information, determine the marking method of the annotation point information in the crossroads according to the widths of the roads corresponding to the annotation point information. The first road and the second road are co-planar roads in the same direction, the third road and the fourth road are co-planar roads in the same direction, and the first road and the second road respectively intersect with the third road and the fourth road at a crossroads.

[0143] The update module 1002 is also specifically used to determine that the marking method of the annotation point information in the intersection is a single main road marking method if the width of the first road is greater than the width of the third road, or the width of the second road is greater than the width of the fourth road; if the width of the first road is equal to the width of the third road, and the width of the second road is equal to the width of the fourth road, then determine that the marking method of the annotation point information in the intersection is a double main road marking method.

[0144] The update module 1002 is also specifically used to identify the satellite images in the original vector data, and classify the road surface information of each road according to the image recognition results and the annotation point information after classification processing, so as to obtain the road surface type and boundary information of each road. The road surface types include: carriageway, sidewalk, bicycle lane, central green belt, non-central green belt and channelized island.

[0145] The calculation module 1003 is also specifically used to determine the area of ​​each type of road sub-item of the first road according to the road surface information in the updated vector data of the first road, wherein the first road is any road in the area to be counted; determine the area of ​​at least one permeable pavement sub-item of the first road according to the archive data of the first road; and superimpose the area of ​​each type of road sub-item and the area of ​​each permeable pavement sub-item to obtain the area of ​​the first road.

[0146] See also Figure 11 This embodiment also provides a computer device, which includes: a processor 2001, a memory 2002 and a bus, the memory 2002 stores machine-readable instructions executable by the processor 2001, and when the computer device is running, the above machine-readable instructions are executed. The processor 2001 communicates with the memory 2002 through the bus, and the processor 2001 is used to execute the steps of the road area calculation method in the above embodiment.

[0147] The memory 2002, the processor 2001 and the bus components are electrically connected to each other directly or indirectly to realize data transmission or interaction. For example, these components can be electrically connected to each other through one or more communication buses or signal lines. The data processing device of the road area calculation system includes at least one software function module that can be stored in the memory 2002 in the form of software or firmware or fixed in the operating system (OS) of the computer device. The processor 2001 is used to execute the executable modules stored in the memory 2002, such as the software function modules and computer programs included in the data processing device of the road area calculation system.

[0148] Among them, the memory 2002 may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), an Electric Erasable Programmable Read-Only Memory (EEPROM), etc.

[0149] Optionally, the present application further provides a storage medium, on which a computer program is stored. When the computer program is run by a processor, it executes the steps of the method embodiment described above. The specific implementation manners and technical effects are similar and will not be elaborated here.

[0150] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems and devices described above can refer to the corresponding processes in the method embodiments, which will not be elaborated in the present application. In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of the modules is only a logical function division, and there may be other division manners in actual implementation. For another example, multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some communication interfaces. The indirect couplings or communication connections of the devices or modules can be in electrical, mechanical, or other forms.

[0151] In addition, in each embodiment of the present application, the functional units can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: various media such as a USB flash drive, a mobile hard disk, a ROM, a RAM, a magnetic disk, or an optical disc that can store program codes.

[0152] As described above, it is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present application should be covered within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claimed rights.

Claims

1. A method for calculating road area, characterized in that, the method includes: Based on the map data of the area to be counted, obtain the original vector data of each road in the area to be counted, and the original vector data includes: the annotation point information of each road and the road surface information; According to the satellite images in the original vector data of each road, classify the annotation point information of each road to obtain the classified annotation point information, and update the annotation point information in the original vector data of each road according to the classified annotation point information to obtain the updated annotation point information of each road; According to the satellite images in the original vector data of each road, the road surface information of each road, and the classified annotation point information, determine the road surface type and boundary information of each road, and update the road surface information in the original vector data of each road according to the road surface type and boundary information of each road to obtain the updated road surface information of each road; According to the annotation point information of each road, obtain the file data of each road, and the file data includes the area data of each road type; According to the road surface information in the updated vector data of the first road, determine the area of each type of road sub-item of the first road, where the first road is any road in the area to be counted; According to the file data of the first road, determine the area of at least one permeable pavement sub-item of the first road; Overlay the areas of each type of road sub-item and the areas of each permeable pavement sub-item to obtain the area of the first road.

2. The road area calculation method according to claim 1, characterized in that, the classifying and processing the annotation point information of each road according to the satellite images in the original vector data of each road to obtain the classified annotation point information includes: Performing image recognition on the satellite images in the original vector data, and classifying and processing the annotation point information of each road according to the image recognition result to obtain the classified annotation point information, and the classified annotation point information includes: crossroads annotation point information and non-crossroads annotation point information.

3. The road area calculation method according to claim 2, characterized in that, the classifying and processing the annotation point information of each road according to the image recognition result to obtain the classified annotation point information includes: If the annotation point information of the first road, the second road, the third road, and the fourth road is crossroads annotation point information, then determine the marking method of the annotation point information inside the crossroads according to the widths of the roads corresponding to the annotation point information. The first road and the second road are co-planar roads in the same direction, the third road and the fourth road are co-planar roads in the same direction, and the first road and the second road respectively intersect with the third road and the fourth road at a crossroads.

4. The road area calculation method according to claim 3, characterized in that, the determining the marking method of the annotation point information inside the crossroads according to the widths of the roads corresponding to the annotation point information includes: If the width of the first road is greater than the width of the third road, or the width of the second road is greater than the width of the fourth road, then determine that the marking method of the annotation point information within the intersection is the single main road marking method; If the width of the first road is equal to the width of the third road, and the width of the second road is equal to the width of the fourth road, then determine that the marking method of the annotation point information within the intersection is the double main road marking method.

5. The road area calculation method according to any one of claims 1-4, characterized in that, determining the road surface type and boundary information of each road according to the satellite image in the original vector data of each road, the road surface information of each road, and the classified annotation point information, including: Identifying the satellite image in the original vector data, and classifying the road surface information of each road according to the image recognition result and the classified annotation point information to obtain the road surface type and boundary information of each road, and the road surface type includes: carriageway, sidewalk, bicycle lane, central green belt, non-central green belt, and channelization island.

6. A road area calculation device, characterized in that, the device includes: An acquisition module, configured to acquire the original vector data of each road within the area to be counted based on the map data of the area to be counted, and the original vector data includes: the annotation point information and road surface information of each road; An update module, configured to update the original vector data of each road according to the annotation point information and the road surface information of each road to obtain the updated vector data of each road; The acquisition module is further configured to acquire the file data of each road according to the annotation point information of each road, and the file data includes the area data of each road type; A calculation module, configured to calculate the area of each road according to the file data of each road and the updated vector data of each road; The update module is specifically configured to: Classify the annotation point information of each road according to the satellite image in the original vector data of each road to obtain the classified annotation point information, and update the annotation point information in the original vector data of each road according to the classified annotation point information to obtain the updated annotation point information of each road; Determine the road surface type and boundary information of each road according to the satellite image in the original vector data of each road, the road surface information of each road, and the classified annotation point information, and update the road surface information in the original vector data of each road according to the road surface type and boundary information of each road to obtain the updated road surface information of each road; The calculation module is specifically configured to: Determine the area of each type of road sub-item of the first road according to the road surface information in the updated vector data of the first road, where the first road is any road in the area to be counted; Determine the area of at least one permeable pavement sub-item of the first road according to the file data of the first road; Overlay the areas of each type of road sub-item and the areas of each permeable pavement sub-item to obtain the area of the first road.

7. A computer device, characterized in that the computer device includes: a processor, a storage medium, and a bus. The storage medium stores machine-readable instructions executable by the processor. When the computer device runs, the processor communicates with the storage medium through the bus, and the processor executes the machine-readable instructions to perform the steps of the road area calculation method according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium. When the computer program is executed by a processor, the steps of the road area calculation method according to any one of claims 1-5 are implemented.

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