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Discussion papers
https://doi.org/10.5194/essd-2019-9
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-2019-9
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 14 Feb 2019

Research article | 14 Feb 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Earth System Science Data (ESSD).

A dataset of 30-meter annual vegetation phenology indicators (1985–2015) in urban areas of the conterminous United States

Xuecao Li1, Yuyu Zhou1, Lin Meng1, Ghassem R. Asrar2, Chaoqun Lu3, and Qiusheng Wu4 Xuecao Li et al.
  • 1Department of Geological and Atmospheric Sciences, Iowa State University, Ames, IA, 50011, USA
  • 2Joint Global Change Research Institute, Pacific Northwest National Lab, College Park, MD, 20740, USA
  • 3Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA, 50011, USA
  • 4Department of Geography, Binghamton University, SUNY, Binghamton, NY, 13902, USA

Abstract. 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 resolution data, which are inadequate for characterizing the spatiotemporal dynamics of vegetation phenology in urban domains. In this study, we produced an annual vegetation phenology dataset in urban ecosystems for the conterminous United States (US), using all 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), using a double logistic model. Then, we identified the annual variability of these two phenology indicators by 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 and Harvard Forest. Comparing with results derived from the moderate resolution imaging spectroradiometer (MODIS) data, our Landsat derived phenology indicators can provide more spatial details. Also, temporal trends of phenology indicators (e.g., SOS) derived from Landsat and MODIS are consistent overall, but the Landsat derived results from 1985 have a longer temporal span compared to MODIS from 2001. In general, there is a spatially explicit pattern of phenology indicators from the North to the South in cities in the conterminous US, with an overall advanced SOS in the past three decades. 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). The data are available at https://doi.org/10.6084/m9.figshare.7685645.v2.

Xuecao Li et al.
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Short summary
We generated a long-term (1985-2015) and fine-resolution (30m) product of vegetation phenology indicators in urban domains in the conterminous United States, using Landsat satellite observations. The derived phenology indicators agree well with in-situ observations and show more spatial details in complex urban areas compared to the existing moderate resolution phenology product. The published data are of great use for urban phenology studies (e.g., pollen-induced respiratory allergies).
We generated a long-term (1985-2015) and fine-resolution (30m) product of vegetation phenology...
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