A method and system for spatial identification of urban decline

By analyzing the long-term trends of urban population and building area, and combining spatial autocorrelation analysis and an eight-corner clustering model, the problem of time dimension and spatial type in the identification of urban decay spaces was solved, realizing the dynamic and accurate identification and classification of urban decay spaces, and supporting multi-scale analysis and differentiated planning.

CN121526102BActive Publication Date: 2026-05-05XIHUA UNIV
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Patent Information

Application Number
CN202610059204.5
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2026-01-16
Publication Date
2026-05-05
Estimated Expiration
2046-01-16

AI Technical Summary

Technical Problem

Existing technologies for identifying urban decay spaces suffer from problems such as missing time dimension, single data source, simple identification logic, and indiscriminate spatial type differentiation, resulting in poor identification accuracy and insufficient spatial clustering, making it difficult to accurately identify and classify urban decay spaces.

Method used

By analyzing the trends of population and building area changes over several consecutive years, and combining spatial autocorrelation analysis and an eight-corner clustering model, the automatic identification and classification of urban decay spaces are achieved. Multi-source data fusion and deep learning models are used for data processing and identification.

Benefits of technology

It enables dynamic and accurate identification and classification of urban decay spaces, improves the reliability and applicability of identification results, and supports multi-scale analysis and differentiated planning.

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Abstract

This invention discloses a method and system for identifying urban decline spaces, belonging to the field of urban planning technology. The method includes: S1. Acquiring population grid data and building area grid data of a target area for multiple consecutive years within a time interval; S2. Performing spatial alignment and standardization processing on the population grid data and building area grid data to form a standardized annual spatial database; S3. Removing grid units in the annual spatial database that do not possess effective urban activity characteristics to obtain a set of effective urban spatial grids; S4. Performing time series analysis on the effective urban spatial grid set to determine urban decline space grids; S5. Using a spatial clustering algorithm to cluster the determined urban decline space grids, dividing the urban decline space into continuous urban decline space and scattered urban decline space. This invention achieves automatic identification and classification of continuous and scattered urban decline spaces by analyzing the population and building area change trends over multiple consecutive years.
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