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© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 20 May 2019

Submitted as: research article | 20 May 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Biogeosciences (BG).

Using Remote Sensing to Monitor the Spring Phenology of Acadia National Park across Elevational Gradients

Yan Liu1,2, Caitlin McDonough MacKenzie3,4, Richard B. Primack4, Michael J. Hill5,6, Xiaoyang Zhang7, Zhuosen Wang8,9, and Crystal B. Schaaf1 Yan Liu et al.
  • 1School for the Environment, University of Massachusetts Boston, Boston, 02125, USA
  • 2Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
  • 3Climate Change Institute, University of Maine, Orono, 04469, USA
  • 4Department of Biology, Boston University, Boston, 02215, USA
  • 5College of Science and Engineering, Flinders University, Adelaide, 5042, Australia
  • 6Department of Earth System Science and Policy, University of North Dakota, Grand Forks, 58202, USA
  • 7Geospatial Sciences Center of Excellence, South Dakota State University, Brookings, 57007, USA
  • 8Earth System Science Interdisciplinary Center, University of Maryland, College Park, 20742, USA
  • 9Terrestrial Information Systems Laboratory, NASA Goddard Space Flight Center, Greenbelt, 20771, USA

Abstract. Greenup dates of the mountainous Acadia National Park, were monitored using remote sensing data (including Landsat 8 surface reflectances (at a 30 m spatial resolution) and VIIRS reflectances adjusted to a nadir view (gridded at a 500 m spatial resolution)) during the 2013–2016 growing seasons. Ground-level leaf-out monitoring in the areas alongside the north-south-oriented hiking trails on three of the park's tallest mountains (466 m, 418 m, and 380 m) was used to evaluate satellite derived greenup dates in this study. While the 30 m resolution would be expected to provide a better scale for phenology detection in this mountainous region than the 500 m resolution, the daily temporal resolution of the 500 m data would be expected to offer vastly superior monitoring of the rapid variations experienced during vegetation greenup along elevational gradients. Therefore, the greenup dates derived from the Landsat 8 Enhanced Vegetation Index (EVI) data, augmented with Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) simulated EVI values, does provide more spatial details than VIIRS data alone and agree well with field monitored leaf out dates. Satellite derived greenup dates from the 30 m of Acadia National Park vary among different elevational zones, although the date of greenup is not always the most advanced at the lowest elevation. This indicates that the spring phenology is not only determined by microclimates associated with different elevations in this mountainous area, but is also possibly affected by the species mixture, localized temperatures, and other factors in Acadia.

Yan Liu et al.
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Status: final response (author comments only)
Status: final response (author comments only)
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Yan Liu et al.
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