Authors: Xuecao Li*, , Yuyu Zhou, Iowa State University, Lin Meng, Iowa State University, Ghassem R Asrar, Pacific Northwest National Lab, Chaoqun Lu, Iowa State University, Qiusheng Wu, State University of New York
Topics: Environmental Science, Sustainability Science, Remote Sensing
Keywords: Landsat; double logistic; urban; deciduous forest; start of season; Google Earth Engine
Session Type: Paper
Start / End Time: 8:00 AM / 9:40 AM
Room: Senate Room, Omni, West
Presentation File: No File Uploaded
Fine-resolution satellite observations show great potential for characterizing seasonal and annual dynamics of vegetation phenology in urban domains, from local to regional and global scales. However, most previous studies were conducted using coarse or moderate resolutions, which are inadequate for characterizing the spatiotemporal dynamics of vegetation phenology in urban domains. In this study, we investigated the dynamics (1985-2015) of vegetation phenology in urban ecosystems for the conterminous United States (US), using all the available Landsat images on the Google Earth Engine (GEE) platform. First, we characterized the long-term mean seasonal pattern of phenology indicators of the start of season (SOS) and the end of season (EOS), from Landsat observations, using a double logistic function. Then, we identified the annual variability of these two phenology indicators through measuring the difference of dates when the vegetation index in a specific year reaches the same magnitude as its long-term mean. The derived phenology indicators agree well with in-situ observations from PhenoCam network, Harvard Forest, and the moderate resolution imaging spectroradiometer (MODIS) product. Our results indicate the SOS advanced to earlier dates during the past three decades in most US climate zones. In addition, the phenology response to urbanization is more pronounced in the northern US, where temperature is a predominant limiting factor for the plant growth. The derived phenology product in the US urban domains at the national level is of great use for urban ecology studies for its fine spatial resolution (30 m) and long temporal span (30 years).