地理大数据支持下的城市功能区识别研究

Study on Urban Functional Area Identification Supported by Geographic Big Data

摘要:

准确识别城市功能区有助于精细化城市管理、合理化资源配置。传统的城市功能区识别方法在很大程度上依赖实地调研及统计年鉴数据，不可避免地存在较大的主观性，且受限于数据获取的繁琐性，导致识别过程耗时耗力且效率低下。地理大数据的广泛应用为城市研究提供了一种新的方法和途径，已被用于辅助城市规划建设与管理相关工作。为推广和普及地理大数据在城市功能区识别中的应用，以特大城市为研究对象，基于OSM（OpenStreetMap）路网与互联网位置信息等地理大数据，准确识别了研究区内多种类型的主要功能区，并将识别结果与城市实景予以比较和验证。实验结果表明，基于地理大数据结合区域活跃度指标的空间与时间尺度分析，可以较为准确地识别出符合特大城市规划现状的主要功能区，证明了地理大数据支持下的城市功能区识别的有效性，有助于为城市规划和建设管理等相关工作的高效开展提供参考。

Abstract:

Accurate identification of urban functional areas helps refine urban management and rationalize resource allocation. Traditional methods of urban functional area identification rely heavily on field research and statistical yearbook data, which are inevitably subjective and limited by the tediousness of data acquisition, resulting in a timeconsuming and inefficient identification process. The wide application of geographic big data provides a new method and approach for urban research, and has been used to assist urban planning and construction and management. In order to promote and popularize the application of geographic big data in urban functional area identification, megacities are taken as the research object and accurately identifies various types of major functional areas in the study area based on geographic big data, such as OSM (Open Street Map) road network and internet location information, and compares and verifies the identification results with the real city scenery. The experimental results show that the spatial and temporal scale analysis based on geographic big data combined with regional activity indexes can accurately identify the main functional areas in line with the current planning status of megacities, which proves the effectiveness of the identification of urban functional areas supported by geographic big data and helps to provide references for the efficient implementation of urban planning and construction management and other related work.