Abstract: To address the limitations of satellite remote sensing in monitoring vegetation phenology across heterogeneous urban and suburban landscapes, with Platanus acerifolia as research object, we proposed a novel pixel-based method for extracting target vegetation within region of interest (ROI) based on images from phenology camera observation sites in urban and suburban Nanjing during the year of 2020. By calculating the green chromatic coordinate (GCC) index, we employed Klosterman curve fitting alongside the Gu phenological parameter extraction method to derive four key phenological phases, i.e., greenup, maturity, senescence, and dormancy, and analyzed urban and suburban phenology feature of P. acerifolia. We analyzed the impact of meteorological factors on phenological phase of urban and suburban P. acerifolia at the daily scale. The results showed that the pixel-based target vegetation extraction method within ROI proposed here significantly reduced interference from buildings and understory vegetation. The identified phenological phase showed strong consistency with satellite remote sensing results, being more robust and reasonable than traditional pixel-averaged ROI method. There was a significant difference of phenological phases of P. acerifolia between urban and suburban sites. In 2020, the greenup of urban P. acerifolia occurred 5.5 days earlier than that of suburban areas, while senescence was delayed by 9.1 days. Temperature and shortwave radiation were the main factors affecting the phenological changes of P. acerifolia in the urban and suburban areas, while the impact of precipitation was not significant. The pixel-based target vegetation extraction technique developed in this study could enhance the accuracy of urban landscape phenological observation and provide methodological support for research on the impact of urbanization on vegetation phenology.

Key words: urban phenology, phenology camera, pixel, meteorological factor, Platanus acerifolia