广州作为珠三角的核心城市之一，一直在经济建设与交通运输方面扮演着重要的角色。然而，随着大规模工程建设的推进和人类活动强度的增加，地质灾害问题也日益凸显。因此，高精度的形变监测和归因分析对于保障城市社会经济发展和公共安全显得尤为重要。本文收集了覆盖广州市2017年5月至2020年5月期间的85景Sentinel-1A数据，利用IPTA时序InSAR技术获取了广州市的地表形变时间序列，并结合GIS空间分析技术和皮尔逊相关性统计定量分析了形变背后的影响因素。同时，本文还引入实地调查数据，分析了地铁沿线缓冲区距离选择对各影响因素与地表形变之间相关性的影响。结果表明：1）广州市地表形变分布较为分散，主要表现为地铁沿线和居民区的局部形变、垃圾填埋场大量级形变以及大面积农田区形变。最大形变位于李坑垃圾填埋场，形变速率达到-54.5 mm/yr；2）地铁沿线的显著形变（<-20mm/yr）主要集中在地铁4号线、9号线、14号线、6号线和18号线，其中6号线柯木塱站最大形变速率可达-39.5mm/yr；3）地铁沿线沉降与运营时间呈现一定的负相关（r=-0.53）;4）地铁沿线沉降与距离成负相关，与路网密度和建筑荷载成正相关，相关性多小于0.2；5）广州市地铁沿线缓冲区选择的最佳距离为1000米，而路网密度与建筑荷载对缓冲区的选择不敏感。

As one of the core cities of the Pearl River Delta, Guangzhou plays an important role in economic development and transportation. However, with the advancement of large-scale engineering construction and the increase in human activities, geologic hazards have become more prominent. Therefore, high-precision deformation monitoring and cause analysis are essential to safeguard the city"s socio-economic development and public safety. This study collected 85 scenes of Sentinel-1A data covering Guangzhou from May 2017 to May 2020 and utilized IPTA time-series InSAR technology to obtain the surface deformation sequence of Guangzhou. By combining GIS spatial analysis techniques and Pearson correlation statistics, the influencing factors behind the deformation were quantitatively analyzed. Additionally, field survey data were introduced to examine the impact of buffer zone distance selection along subway lines on the correlation between various influencing factors and surface deformation. Results: 1) Surface deformation within Guangzhou exhibits a decentralized distribution, characterized by localized deformation along metro lines and residential areas, large-scale deformation in landfill sites, and widespread deformation in the farmland areas. The largest deformation is observed at LiKeng landfill, with a deformation rate of -54.5 mm/yr. 2) Obvious deformations (<-20 mm/yr) along the metro primarily concentrated on lines 14, 9, 4, 6, and 18, with the largest deformation rate recorded at KeMuLang station on line 6, reaching -39.5 mm/yr. 3) Settlement along the metro line demonstrates a moderate negative correlation with operation time (r=-0.53), suggesting that as metro lines operate for longer durations, settlement magnitudes decrease; 4) Settlement along the metro line shows a negative correlation with distance, yet displays a positive correlation with road network density and building loads, the correlation is mostly less than 0.2; 5) The optimal buffer zone distance along Guangzhou’s metro lines is determined to be 1000 meters, while road network density and building loads exhibit insensitivity to buffer zone selection.