Real estate surveying and mapping project regional surveying and mapping method and system based on unmanned aerial vehicle

Abstract

The invention relates to the technical field of real estate surveying and mapping, and particularly discloses a real estate surveying and mapping project regional surveying and mapping method and system based on an unmanned aerial vehicle, and the method comprises the steps: 1, obtaining basic topographic data, local policies and airspace limitation of a surveying and mapping region, and organizing team personnel to carry out on-site survey; 2, dividing a surveying and mapping area into a plurality of areas by using a GIS tool, formulating a flight height, a flight route and an overlapping rate, and meanwhile, arranging a GCP; step 3, according to the planned flight task, performing unmanned aerial vehicle flight in different regions, and collecting region images and point cloud data in real time; according to the method, the unmanned aerial vehicle is used for carrying the laser measurement system and the camera to collect the point cloud data and the image data of the project surveying and mapping area under the regional condition, and then the point cloud data and the influence data are integrated for drawing to obtain the final surveying and mapping result, so that the field workload can be reduced on the premise of ensuring the result precision; object boundaries are presented in the form of laser points, which is convenient for operators to judge.

Description

Technical Field

[0001] The present invention belongs to the technical field of real estate surveying and mapping, and in particular relates to a method and system for regional surveying and mapping of real estate surveying and mapping projects based on unmanned aerial vehicles. Background Art

[0002] According to the existing laws and regulations, the content of real estate registration includes many aspects, such as the ownership of land, sea areas, and the buildings, structures, forests, trees and other fixed objects thereon. Natural conditions are one of the main contents of real estate registration. The data of location, boundary, spatial boundary, area and other natural conditions are all obtained through surveying and mapping. Therefore, surveying and mapping plays a vital role in real estate investigation and registration.

[0003] In the real estate surveying and mapping work when conducting field investigations, title confirmation, and registration of real estate, real estate surveying and mapping geographical maps are essential basic maps. They are the positioning basis for real estate surveying and mapping, and are also the carrier platform for real estate thematic content. In the updating and deletion of real estate surveying and mapping data, the use of algorithms to complete real-time data updates can not only improve work efficiency, but also enable reasonable information management. Solve the problem of real-time updating of data information and queries, and achieve digital and intelligent surveying and mapping goals. At this stage, the amount of data collected by drones is huge, and the data processing speed is slow. At the same time, it is necessary to complete the storage and management of the large amount of collected data, otherwise it is easy to cause data loss or confusion.

[0004] Therefore, it is necessary to propose a regional surveying method and system for real estate surveying and mapping projects based on drones to solve the problem of large data volume and difficulty in processing in the existing technology.

[0005] The above information disclosed in this background technology is only used to increase the understanding of the background technology of the present invention and therefore, it may include information that does not constitute the prior art known to ordinary technicians in this field. Summary of the invention

[0006] The purpose of the present invention is to provide a method and system for regional surveying of real estate surveying projects based on drones to solve the problems raised in the above-mentioned background technology.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] A method for regional surveying of real estate surveying projects based on drones, comprising the following steps:

[0009] Step 1: Obtain basic terrain data, local policies and airspace restrictions in the survey area, and organize team members to conduct on-site surveys;

[0010] Step 2: Use GIS tools to divide the survey area into several areas, determine the flight altitude, route, overlap rate, and lay out GCPs;

[0011] Step 3: According to the planned flight mission, UAVs are flown in different areas to collect regional images and point cloud data in real time;

[0012] Step 4: Use professional software to process the UAV flight data and point cloud data respectively, and perform image stitching to generate orthophoto images;

[0013] Step 5: Use decision tree algorithm to classify the data in the database, and use weighted multi-source data fusion method to fuse real estate basic data and image data;

[0014] Step 6: After integrating and associating the orthophoto with the processed point cloud data, the vector features are drawn using cadastral map editing software to obtain the final surveying and mapping results.

[0015] Preferably, in step one, a surveying and mapping area is delineated based on the project objectives, and the delineated surveying and mapping area is adjusted according to local policies and airspace restrictions, a safety assessment is conducted on the area of ​​field survey to identify potential risks, and an emergency plan is formulated.

[0016] Preferably, in step 2, a Voronoi diagram is constructed based on a single area to help plan the route to cover the entire area, and a genetic algorithm is used to optimize the route design to minimize flight time and resource consumption. At the same time, the number of GCPs to be deployed is determined according to the size and complexity of the single area, and the positions of the GCPs are accurately measured and calibrated and field verification is performed.

[0017] Preferably, before collecting in step three, check the equipment status (battery, propeller, sensor calibration, etc.) and conduct a simulated flight test; during collection, monitor the drone status and sensor working conditions in real time; after collection, download the collected images and point cloud data to the ground control station for data backup.

[0018] Preferably, in step four, Inertial Explore software is used to parse the UAV flight data to generate flight trajectory data, and point cloud fusion, coordinate conversion, and point cloud precision processing operations are sequentially performed to analyze and process the obtained point cloud data, and the flight trajectory data is introduced during the coordinate conversion to generate point cloud data with real three-dimensional coordinates. For the processing of the image data, the flight trajectory data and the collected image data are loaded into Pix4dmapper software for processing to produce an orthophoto map.

[0019] Preferably, in step five, timestamp is used as the basis for the order of data storage, and the selected data sets are grouped according to attribute characteristics through a ternary decision tree, so that the sum of the differences in the categorical variable values ​​in the subsets of the data set is minimized, and the categorical variable values ​​covered by all data in the left and right subsets are the same, and the spatial data and non-spatial data of the real estate are integrated through data fusion.

[0020] Suppose the selected sample data set is b, the sample set of candidate attributes is m, k different attributes are selected, and the attribute value contained in them is i. When the decision tree classification of the ternary decision tree is selected, the classification index in the classification and regression tree is the boundary value. The calculation formula for the value of each sample category variable in the selected training sample data set is:

[0021]

[0022] Where q represents the processed data set that has not been grouped, and p represents the probability that data set b exists in the selected data.

[0023] Preferably, in step six, the cadastral map compiling software introduces point cloud data through a three-dimensional window and orthophoto data through a two-dimensional window, uses the point cloud data and image data as data sources to draw a vector map, and performs statistics on the accuracy of the results through high-precision statistical methods.

[0024] A regional surveying and mapping system for real estate surveying and mapping projects based on drones, comprising: a data acquisition module, a data processing module, a data management module, a project management module, a user management module, and a result verification module;

[0025] The data acquisition module is used to collect real estate data in different regions by using a drone equipped with a laser measurement system and a camera;

[0026] The data processing module is used to analyze and process the collected raw data to generate usable surveying and mapping results;

[0027] The data management module is used to store, manage and share surveying and mapping data in attribute data tables;

[0028] The project management module is used to manage the overall progress and resource scheduling of the project;

[0029] The user management module is used to manage the permissions and access control of participants;

[0030] The results verification module is used to evaluate the accuracy of surveying and mapping results through statistical methods.

[0031] Preferably, the data acquisition module is used to process requests that do not require immediate response through an asynchronous task queue, so that the main thread remains responsive, the data management module is used to use a suitable B-tree index to query data in the database, the project management module is used to use a multi-core processor to execute tasks in parallel, decompose large tasks into multiple small tasks and assign them to participants for processing, and the data processing module uses GraphQL instead of RESTful API to request specific data as needed, thereby reducing the amount of data transmission.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] The present invention uses an unmanned aerial vehicle equipped with a laser measurement system and a camera to collect point cloud data and image data of the project surveying area in a zoned manner, processes the point cloud data and image data respectively through professional software, and then integrates the point cloud data and the impact data to draw the final surveying and mapping results. The field workload can be reduced while ensuring the accuracy of the results. The boundaries of objects are presented in the form of laser points, which is convenient for operators to judge and gives users a better user experience.

[0034] The present invention associates the spatial data and attribute data of real estate, and uses timestamps and B-tree indexes to complete classified queries for integrated surveying and mapping, helping users to better manage multi-source data and avoid large errors in surveying and mapping results caused by data loss, thereby failing to achieve expected goals.

[0035] The above summary is for illustrative purposes only and is not intended to be limiting in any way. In addition to the illustrative aspects, embodiments and features described above, further aspects, embodiments and features of the present invention will be readily apparent by reference to the accompanying drawings and the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 This is a flow chart of the regional surveying method for real estate surveying and mapping projects based on drones of the present invention;

[0037] Figure 2 This is a framework diagram of the regional surveying and mapping system for real estate surveying and mapping projects based on drones of the present invention. DETAILED DESCRIPTION

[0038] 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.

[0039] It should be further understood that the term “and / or” used in the specification of this application and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0040] Embodiment 1:

[0041] See also Figure 1 As shown, a method for regional surveying of real estate surveying projects based on drones includes the following steps:

[0042] Step 1: Obtain basic terrain data, local policies and airspace restrictions for the survey area, and organize team members to conduct field surveys: Delineate the survey area based on project objectives, and adjust the designated survey area according to local policies and airspace restrictions, conduct safety assessments on the field survey area to identify potential risks, and develop emergency plans;

[0043] Step 2: Use GIS tools to divide the survey area into several areas, determine the flight altitude, route, overlap rate, and lay out GCPs: Construct a Voronoi diagram based on a single area to help plan routes to cover the entire area, use genetic algorithms to optimize route design to minimize flight time and resource consumption, and determine the number of GCPs to be laid out based on the size and complexity of a single area, accurately measure and calibrate the location of the GCPs, and conduct on-site verification;

[0044] Step 3: According to the planned flight mission, the drone is flown in different areas to collect regional images and point cloud data in real time: before collecting, the equipment status is checked and a simulated flight test is conducted; during collection, the drone status and sensor working conditions are monitored in real time; after collection, the collected images and point cloud data are downloaded to the ground control station for data backup;

[0045] Step 4: Use professional software to process the UAV flight data and point cloud data respectively, and perform image stitching to generate orthophotos: Use Inertial Explore software to analyze the UAV flight data to generate flight trajectory data, and perform point cloud fusion, coordinate conversion, and point cloud precision processing operations to analyze and process the obtained point cloud data. In addition, the flight trajectory data is introduced during the coordinate conversion to generate point cloud data with real three-dimensional coordinates.

[0046] First, create a new project in the Inertial Explore software, load the IMU data (IMU system carried by the drone) and GCP data collected in the field into the project, and obtain the flight trajectory data through combined navigation solution. After the flight trajectory data solution is completed, check the solution results, including IMU processing attitude, attitude and position accuracy, processing accuracy report, etc. After the solution results are correct, output the flight trajectory file.

[0047] First, the point cloud fusion is completed in the HGO software, and then the flight trajectory data and point cloud rxp data are loaded in the Ztpointprocess software. The rxp data is converted into point cloud data with real three-dimensional coordinates by setting the system inspection parameters. The point cloud format is the universal LAS format. Finally, the LAS format point cloud data is loaded into the TerraSolid software for point cloud filtering, noise point removal and other fine processing. The filtering is performed at a scanning angle of 120°, and the quality of the processed point cloud is checked. The main inspection items are:

[0048] (1) Whether the point cloud data covers the entire survey area completely;

[0049] (2) Whether the flight strip splicing error meets the data processing requirements (the flight strip splicing error must be less than 0.5m, and recalculation is required if it is greater than 0.5m);

[0050] (3) Whether there are gaps between flight strips and whether the overlap rate meets the requirements (not less than 50%).

[0051] Step 5: Use the decision tree algorithm to classify the data in the database, and use the weighted multi-source data fusion method to fuse the real estate basic data and image data: use the timestamp as the order basis for data storage, and use the ternary decision tree to group the selected data sets according to the attribute characteristics, so that the sum of the differences in the category variable values ​​in the subsets of the data set is minimized, and the category variable values ​​covered by all the data in the left and right subsets are the same. The spatial data and non-spatial data of the real estate are integrated through data fusion;

[0052] Step 6. After integrating and associating the orthophoto image with the processed point cloud data, the cadastral map compilation software is used to draw vector features to obtain the final surveying and mapping results: the cadastral map compilation software introduces point cloud data through a three-dimensional window and orthophoto data through a two-dimensional window, and uses point cloud data and image data as data sources to draw vector maps, and uses high-precision statistical methods to calculate the accuracy of the results.

[0053] From the above, it can be seen that the present invention uses an unmanned aerial vehicle equipped with a laser measurement system and a camera to collect point cloud data and image data of the project surveying area in a zoned manner, processes the point cloud data and image data respectively through professional software, and then integrates the point cloud data and the impact data to draw the final surveying and mapping results. The field workload can be reduced while ensuring the accuracy of the results. The boundaries of objects are presented in the form of laser points, which is convenient for operators to judge and gives users a better user experience.

[0054] Embodiment 2:

[0055] See also Figure 2As shown, based on Example 1, the present invention provides a regional surveying and mapping system for real estate surveying and mapping projects based on drones, including: a data acquisition module, a data processing module, a data management module, a project management module, a user management module, and a result verification module;

[0056] The data acquisition module is used to collect real estate data in different regions using a drone equipped with a laser measurement system and a camera, and to process requests that do not require an immediate response through an asynchronous task queue, so that the main thread remains responsive;

[0057] The data processing module is used to analyze and process the collected raw data, generate usable surveying and mapping results, use GraphQL instead of RESTful API, request specific data as needed, and reduce the amount of data transmission;

[0058] The data management module is used to store, manage and share surveying and mapping data in attribute data tables, and to perform data queries in the database using appropriate B-tree indexes;

[0059] The project management module is used to manage the overall progress and resource scheduling of the project, using multi-core processors to execute tasks in parallel and breaking down large tasks into multiple small tasks to be assigned to participants for processing;

[0060] The user management module is used to manage the permissions and access control of participants; the results verification module is used to evaluate the accuracy of surveying and mapping results through statistical methods.

[0061] From the above, it can be seen that the present invention associates the spatial data and attribute data of real estate, uses timestamps and B-tree indexes to complete classified queries for integrated surveying and mapping, helps users better manage multi-source data, avoids data loss that leads to large errors in surveying and mapping results, and fails to achieve expected goals.

[0062] Embodiment 3:

[0063] The embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, each process of the above-mentioned embodiment of the real estate surveying and mapping project sub-regional surveying and mapping system is implemented, and the same technical effect can be achieved. To avoid repetition, it is not repeated here. Among them, the computer-readable storage medium, such as a read-only memory (Read-Only Memory, referred to as ROM), a random access memory (Random Access Memory, referred to as RAM), a magnetic disk or an optical disk, etc.

[0064] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples" or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine different embodiments or examples described in this specification and the features of different embodiments or examples, unless they are contradictory.

[0065] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a program, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A way to specify functions in one or more boxes.

[0066] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0067] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0068] In the drawings of the embodiments disclosed in the present invention, only the structures involved in the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other.

[0069] The flowcharts shown in the accompanying drawings are only examples and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may also be decomposed, combined or partially merged, so the actual execution order may change according to actual conditions.

[0070] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for regional surveying of real estate surveying projects based on drones, characterized in that: include: Step 1: Obtain basic terrain data, local policies and airspace restrictions in the survey area, and organize team members to conduct on-site surveys; Step 2: Use GIS tools to divide the survey area into several areas, determine the flight altitude, route, overlap rate, and lay out GCPs; Step 3: According to the planned flight mission, UAVs are flown in different areas to collect regional images and point cloud data in real time; Step 4: Use professional software to process the UAV flight data and point cloud data respectively, and perform image stitching to generate orthophoto images; Step 5: Use decision tree algorithm to classify the data in the database, and use weighted multi-source data fusion method to fuse real estate basic data and image data; Step 6: After integrating and associating the orthophoto with the processed point cloud data, the vector features are drawn using cadastral map editing software to obtain the final surveying and mapping results.

2. The method for regional surveying of real estate surveying and mapping projects based on drones according to claim 1 is characterized by: In step one, the survey area is delineated based on the project objectives, and the delineated survey area is adjusted according to local policies and airspace restrictions. A safety assessment is conducted on the field survey area to identify potential risks and develop an emergency plan.

3. The method for regional surveying of real estate surveying and mapping projects based on drones according to claim 2 is characterized by: In step 2, a Voronoi diagram is constructed based on a single area to help plan the route, and a genetic algorithm is used to optimize the route design. At the same time, the number of GCPs that need to be deployed is determined based on the size and complexity of the single area, and the location of the GCPs is accurately measured and calibrated, and field verification is performed.

4. The method for regional surveying of real estate surveying and mapping projects based on drones according to claim 3 is characterized by: Before collecting in step 3, check the equipment status and conduct a simulated flight test; during collection, monitor the drone status and sensor working conditions in real time; after collection, download the collected images and point cloud data to the ground control station for data backup.

5. The method for regional surveying of real estate surveying and mapping projects based on drones according to claim 4 is characterized by: In step 4, the Inertial Explore software is used to analyze the UAV flight data to generate flight trajectory data. Point cloud fusion, coordinate transformation, and point cloud precision processing operations are performed in sequence to analyze and process the obtained point cloud data. The flight trajectory data is introduced during the coordinate transformation to generate point cloud data with real three-dimensional coordinates.

6. The method for regional surveying of real estate surveying and mapping projects based on drones according to claim 5 is characterized by: In step five, the timestamp is used as the order basis for data storage, the selected data sets are grouped according to attribute characteristics through a ternary decision tree, and the spatial data and non-spatial data of real estate are integrated through data fusion.

7. The method for regional surveying of real estate surveying and mapping projects based on drones according to claim 6 is characterized by: In step six, the cadastral map compilation software introduces point cloud data through a three-dimensional window and orthophoto data through a two-dimensional window, uses point cloud data and image data as data sources to draw vector maps, and uses high-precision statistical methods to calculate the accuracy of the results.

8. A regional surveying and mapping system for real estate surveying and mapping projects based on drones, characterized in that: include: Data acquisition module, data processing module, data management module, project management module, user management module, and achievement verification module; The data acquisition module is used to collect real estate data in different regions by using a drone equipped with a laser measurement system and a camera; The data processing module is used to analyze and process the collected raw data to generate usable surveying and mapping results; The data management module is used to store, manage and share surveying and mapping data in attribute data tables; The project management module is used to manage the overall progress and resource scheduling of the project; The user management module is used to manage the permissions and access control of participants; The results verification module is used to evaluate the accuracy of surveying and mapping results through statistical methods.

9. The regional mapping system for real estate mapping projects based on drones according to claim 8 is characterized by: The data acquisition module is used to process requests that do not require immediate response through an asynchronous task queue, and the data management module is used to perform data query in the database using a suitable B-tree index.

10. The regional surveying and mapping system for real estate surveying and mapping projects based on drones according to claim 8, characterized in that: The project management module is used to utilize a multi-core processor to execute tasks in parallel, decompose a large task into multiple small tasks and assign them to participants for processing. The data processing module uses GraphQL instead of RESTful API to request specific data as needed.

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