摘要:Medium-resolution satellite observations show greatpotential for characterizing seasonal and annual dynamics of vegetationphenology in urban domains from local to regional and global scales.However, most previous studies were conducted using coarse-resolution data,which are inadequate for characterizing the spatiotemporal dynamics ofvegetation phenology in urban domains. In this study, we produced an annualvegetation phenology dataset in urban ecosystems for the conterminous UnitedStates (US), using all available Landsat images on the Google Earth Engine(GEE) platform. First, we characterized the long-term mean seasonal patternof phenology indicators of the start of season (SOS) and the end of season(EOS), using a double logistic model. Then, we identified the annualvariability of these two phenology indicators by measuring the difference ofdates when the vegetation index in a specific year reaches the samemagnitude as its long-term mean. The derived phenology indicators agree wellwith in situ observations from the PhenoCam network and Harvard Forest. Comparing withresults derived from the moderate-resolution imaging spectroradiometer(MODIS) data, our Landsat-derived phenology indicators can provide morespatial details. Also, we found the temporal trends of phenology indicators(e.g., SOS) derived from Landsat and MODIS are consistent overall, but theLandsat-derived results from 1985 offer a longer temporal span compared toMODIS from 2001 to present. In general, there is a spatially explicitpattern of phenology indicators from the north to the south in cities in theconterminous US, with an overall advanced SOS in the past 3 decades. Thederived phenology product in the US urban domains at the national level isof great use for urban ecology studies for its medium spatial resolution (30m) and long temporal span (30 years). The data are available athttps://doi.org/10.6084/m9.figshare.7685645.v5.