Urban land utilization identification method based on BERT model text classification algorithm
By using a text classification algorithm based on the BERT model and a POI data cleaning strategy, the problems of accuracy and cross-city adaptability in urban land use identification in existing technologies are solved, and high-precision, adaptive urban land use identification is achieved.
Patent Information
- Application Number
- CN202512038877.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-31
- Publication Date
- 2026-05-12
AI Technical Summary
Existing technologies for identifying urban land use using POI data suffer from problems such as inappropriate data selection principles, inaccurate identification unit division, lack of context sensitivity in model algorithms, inaccurate translation of identification results, and inability to adapt to mixed land use, resulting in low identification accuracy and a lack of cross-city adaptability.
A text classification algorithm based on the BERT model was adopted. Urban land use identification units were divided into 50×50 meter grids. Combined with POI data cleaning strategy and data augmentation technology, an urban land use identification model was established. The context capture capability and multi-layer semantic understanding of the BERT model were used to achieve high-precision identification.
It significantly improves the accuracy and precision of urban land use identification, can adapt to urban spatial structure, support land use compatibility and mixed policies, has adaptive optimization capabilities, and achieves efficient and accurate urban land use identification.