基于多源数据的城市绿地生态系统识别方法和系统
By integrating multi-source data and using a hierarchical deep forest model, the problem of accurate identification and classification of urban green space ecosystems has been solved, achieving efficient and accurate multi-level green space classification and supporting the modernization of urban ecological governance systems.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- BEIJING MUNICIPAL RES INST OF ENVIRONMENT PROTECTION
- Filing Date
- 2025-12-19
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies struggle to accurately identify ecologically functional and non-ecologically dominant green spaces in urban green areas, and their precision in classifying the functional types of vegetation within green spaces is insufficient, failing to meet the needs for quantifying ecological value and refining management.
An urban green space ecosystem identification method based on multi-source data is adopted. By acquiring satellite remote sensing data, UAV remote sensing data, ground multi-sensor data and urban management data, data preprocessing and multi-dimensional ecological feature extraction are performed. A hierarchical deep forest model is used to identify ecological types, including the extraction and classification of basic ecological features, phenological ecological features and ecological resilience features.
It enables efficient, accurate, and multi-level classification of urban green spaces, precisely identifies green space systems with stable ecological service functions, removes interference from non-ecologically dominant green spaces, improves the spatial accuracy and functional differentiation of green space classification, and supports urban ecological space planning and refined resource management.
Smart Images
Figure CN121686243B_ABST