To reveal the complex relationship between the built environment and walking activity among older adults, a gradient boosting regression tree (GBRT) model was adopted, combined with multi-source data such as mobile signaling data, remote sensing image data, and point of interest (POI), to deeply explore the non-linear impact of the built environment on elderly walking activities and its threshold characteristics. The findings indicate that the built environment has a significant nonlinear impact on older adults'walking activity, with land use factors being the most influential. Specifically, land use mix, the proportion of commercial service facilities, and the proportion of residential land are identified as key factors affecting older adults' walking activity. Additionally, the proximity of facilities also plays an important role. Finally, suggestions have been put forward for the adaptive transformation of land use and facilities to improve the level of elderly walking activities and promote healthy aging.