城市公园可达性影响心理健康、身体健康及社区凝聚力，因此其测量是城市与景观规划的核心环节。尽管研究者已就不同可达性测度对分析结果的影响展开讨论，但鲜有关注数据源选择带来的变异性。基于不同数据集定义公园位置与属性时，可达性分析结果是否存在差异？本文通过验证数据并在两个城市中测量公园可达性，比较了四种广泛使用的地理空间数据源：OpenStreetMap、Esri、SafeGraph 和 The Trust for Public Land。尽管这些数据集声称覆盖相同的空间要素，但研究发现，由于各数据源在完整性、覆盖范围和准确性方面存在差异，导致可达性结果出现显著偏差。本文为可达性分析中的数据选择与严格验证提供指导准则，因为这些决策直接影响后续城市公园规划与决策的准确性和公平性。

Urban park accessibility shapes mental health, physical well-being, and community cohesion. Measuring it is thus central to urban and landscape planning. Although researchers have debated the impacts of different accessibility measures on analysis results, scant attention has been paid to variability from data source selection. Do the results of accessibility analyses vary depending on the dataset used to define park locations and attributes? We compare four widely used geospatial data sources - OpenStreetMap, Esri, SafeGraph, and The Trust for Public Land - by validating their data and measuring park access across two cities. These datasets purport to cover the same spatial features, but our findings reveal wide discrepancies in accessibility results, driven by differences in dataset completeness, coverage, and accuracy between the sources. We provide guidelines for selecting and carefully validating data for accessibility analyses, as these decisions directly impact the accuracy and equity of downstream urban park planning and decision-making.