Urban parks support public health, but landscape architecture typically examines them through form and function. Prior equitable access research focused on park form, while functional studies relied on small-scale surveys, movement data, or broad usage metrics, missing specific activities and visit motivations. This gap limits our grasp of parks' functional diversity. We address this with a novel method refining mobile base station coverage via antenna azimuths to isolate park-specific traffic from surroundings. Using Paris as a case study, we process 492 million hourly per-app mobile records (35% market share) from 45 urban parks. We test the central-city hypothesis (multifunctional parks in dense, high-rent zones due to land constraints) and socio-spatial hypothesis (parks reflecting neighborhood routines and preferences). Results reveal parks' unique mobile traffic signatures, distinct from urban contexts and each other. Clustering by temporal and app patterns identifies three types: lunchbreak, cultural, and recreational parks, linked to health-promoting visitation motives. Central parks show diverse apps and peak usage; suburban recreational parks mirror local demographics, like income-aligned app preferences. This demonstrates mobile traffic's power as a proxy for urban green space activities, with key implications for park design, public health, and well-being strategies.

翻译：城市公园对公共健康具有支撑作用，但景观建筑学通常通过形态与功能对其进行分析。先前关于公平使用的研究侧重于公园形态，而功能性研究则依赖于小规模调查、移动数据或宽泛的使用指标，未能捕捉具体活动与访问动机。这一局限制约了我们对公园功能多样性的理解。我们提出一种新方法，通过天线方位角优化移动基站覆盖范围，从而将公园特定流量与周边环境隔离。以巴黎为案例研究，我们处理了来自45个城市公园的4.92亿条每小时每应用移动记录（市场占有率35%）。我们检验了中心城区假说（由于土地限制，密集高租金区域的多功能公园）与社会空间假说（公园反映社区日常习惯与偏好）。结果显示，公园具有独特的移动流量特征，既区别于城市背景，也彼此不同。基于时间与应用模式的聚类识别出三种类型：午休型、文化型与休闲型公园，这些类型与促进健康的访问动机相关。中心城区公园展现出多样化的应用使用和高峰流量；郊区休闲型公园则反映当地人口特征，如与收入水平相符的应用偏好。这证明了移动流量作为城市绿地活动代理指标的有效性，对公园设计、公共健康及福祉策略具有重要启示。