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

Abstract

Medium-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-resolution data,which are inadequate for characterizing the spatio-temporal 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 the PhenoCam network and Harvard Forest. Comparing with results derived from the moderate-resolution imaging spectro-radiometer (MODIS) data, our Landsat-derived phenology indicators can provide more spatial details. Also, we found the temporal trends of phenology indicators (e.g., SOS) derived from Landsat and MODIS are consistent overall, but the Landsat-derived results from 1985more » offer a longer temporal span compared to MODIS from 2001 to present. 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 3 decades. The derived phenology product in the US urban domains at the national level is of great use for urban ecology studies for its medium spatial resolution (30 m) and long temporal span (30 years).« less

Authors:
 [1];  [1];  [1]; ORCiD logo [2];  [1];  [3]
  1. Iowa State Univ., Ames, IA (United States). Dept. of Geological and Atmospheric Sciences
  2. Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Joint Global Change Research Inst.
  3. Univ. of Tennessee, Knoxville, TN (United States). Dept. of Geography
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1567251
Report Number(s):
PNNL-SA-144732
Journal ID: ISSN 1866-3516
Grant/Contract Number:  
AC05-76RL01830
Resource Type:
Accepted Manuscript
Journal Name:
Earth System Science Data (Online)
Additional Journal Information:
Journal Name: Earth System Science Data (Online); Journal Volume: 11; Journal Issue: 2; Journal ID: ISSN 1866-3516
Publisher:
Copernicus
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES

Citation Formats

Li, Xuecao, Zhou, Yuyu, Meng, Lin, Asrar, Ghassem R., Lu, Chaoqun, and Wu, Qiusheng. A dataset of 30 m annual vegetation phenology indicators (1985–2015) in urban areas of the conterminous United States. United States: N. p., 2019. Web. doi:10.5194/essd-11-881-2019.
Li, Xuecao, Zhou, Yuyu, Meng, Lin, Asrar, Ghassem R., Lu, Chaoqun, & Wu, Qiusheng. A dataset of 30 m annual vegetation phenology indicators (1985–2015) in urban areas of the conterminous United States. United States. doi:10.5194/essd-11-881-2019.
Li, Xuecao, Zhou, Yuyu, Meng, Lin, Asrar, Ghassem R., Lu, Chaoqun, and Wu, Qiusheng. Fri . "A dataset of 30 m annual vegetation phenology indicators (1985–2015) in urban areas of the conterminous United States". United States. doi:10.5194/essd-11-881-2019. https://www.osti.gov/servlets/purl/1567251.
@article{osti_1567251,
title = {A dataset of 30 m annual vegetation phenology indicators (1985–2015) in urban areas of the conterminous United States},
author = {Li, Xuecao and Zhou, Yuyu and Meng, Lin and Asrar, Ghassem R. and Lu, Chaoqun and Wu, Qiusheng},
abstractNote = {Medium-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-resolution data,which are inadequate for characterizing the spatio-temporal 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 the PhenoCam network and Harvard Forest. Comparing with results derived from the moderate-resolution imaging spectro-radiometer (MODIS) data, our Landsat-derived phenology indicators can provide more spatial details. Also, we found the temporal trends of phenology indicators (e.g., SOS) derived from Landsat and MODIS are consistent overall, but the Landsat-derived results from 1985 offer a longer temporal span compared to MODIS from 2001 to present. 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 3 decades. The derived phenology product in the US urban domains at the national level is of great use for urban ecology studies for its medium spatial resolution (30 m) and long temporal span (30 years).},
doi = {10.5194/essd-11-881-2019},
journal = {Earth System Science Data (Online)},
number = 2,
volume = 11,
place = {United States},
year = {2019},
month = {6}
}

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