Batch Road Attribute Extraction via Topology Correction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Manual processing of extracting attributes for starting and ending points of roads in urban regional road networks is labor-intensive, prone to errors, and inefficient, especially in complex networks with large amounts of data.
Innovation Solution
A method involving topology inspection and correction of line layer Shape files, assigning IDs, processing data in ArcGIS, intersecting point and line elements, and exporting results to extract attributes of starting and ending points in batches, reducing manual errors and increasing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual matching of road attributes is performed, then accuracy can be maintained through human judgment, but the workload is heavy and error-prone
Solution Approach 1:
The system performs automatic attribute extraction and matching through computerized algorithms, allowing the system to serve itself without manual intervention. The automated process extracts road names, starting points, and ending points from geographic data, eliminating the need for manual matching while maintaining consistency and accuracy through standardized procedures.
Solution Approach 2:
The patent replaces the manual mechanical process of attribute matching with an automated computational system. Geographic information systems and algorithms automatically extract and match road attributes, substituting human manual operations with computer-based processing that handles large datasets efficiently and accurately.
2Productivity
If computer batch operation is used for attribute matching, then productivity is improved, but matching accuracy may deteriorate due to automated processing errors
Solution Approach 1:
The system incorporates validation mechanisms that verify the accuracy of automatically extracted attributes. The feedback loop checks whether extracted road names, starting points, and ending points match the expected formats and cross-references existing geographic data to confirm accuracy, allowing correction of any automated processing errors.
Solution Approach 2:
The system performs preliminary data cleaning and standardization before attribute extraction and matching. By preprocessing the geographic data to ensure consistent formats and complete information, the system prepares the data in advance to minimize potential errors during automated processing and matching operations.
3Manufacturing precision
If manual processing of road network data is performed, then data quality can be controlled, but time consumption increases significantly
Solution Approach 1:
The patent replaces manual data processing operations with automated computational methods. Geographic information systems automatically extract road attributes, validate data quality, and process large volumes of road network data through standardized algorithms, eliminating the time-consuming manual processing while maintaining quality control through systematic validation procedures.
Solution Approach 2:
The automated system processes road network data continuously without interruption, handling large datasets in batch operations. The continuous processing capability allows the system to maintain data quality standards throughout the entire workflow, from extraction to validation, without the breaks and rework associated with manual processing.
Data Source
AI summary
A method for extracting attributes of starting and ending points of roads in batches from an urban regional road network: obtaining a line layer Shape file of the urban regional traffic road network, performing topology inspection and correction on the line layer Shape file to be stored as a line layer Shape2 file; processing the line layer Shape2 file to obtain data of a starting point, a turning point, and an ending point of each road to be exported as a point-line layer Shape3 file; intersecting point layer elements and line layer elements of the point-line layer Shape3 file and the line layer Shape2 file to be exported as a point-line layer Shape4 file; processing the point-line layer Shape4 file, exporting a .Csv file; and connecting the line layer Shape2 file with the Csv file to extract the attributes of the starting and ending points of the roads in batches.