Abstract
Vegetation phenology plays a pivotal role in regulating several ecological processes and has profound impacts on global carbon exchange. Large-scale vegetation phenology monitoring mostly relies on Low-Earth-Orbit satellite observations with low temporal resolutions, leaving gaps in data that are important for monitoring seasonal vegetation phenology. High temporal resolution satellite observations have the potential to fill this gap by frequently collecting observations on a global scale, making it easier to study change over time. This study explored the potential of using the Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) satellite, which captures images of the entire sunlit face of the Earth at a temporal resolution of once every 1–2 h, to observe vegetation phenology cycles in North America. We assessed the strengths and shortcomings of EPIC-based phenology information in comparison with the Moderate-resolution Imaging Spectroradiometer (MODIS), Enhanced Thematic Mapper (ETM+) onboard Landsat 7, and PhenoCam ground-based observations across six different plant functional types. Our results indicated that EPIC could capture and characterize seasonal changes of vegetation across different plant functional types and is particularly consistent in the estimated growing season length. Our results also provided new insights into the complementary features and benefits of the four datasets, which is valuable for improving our understanding of the complex response of vegetation to global climate variability and other disturbances and the impact of phenology changes on ecosystem productivity and global carbon exchange.
Highlights
The capability to accurately observe vegetation phenology cycles allows us to understand how these cycles are changing in time and space due to climate, urbanization, and other natural and anthropogenic influences [1–4]
Our results indicated that Earth Polychromatic Imaging Camera (EPIC) observations, despite coarse spatial resolution of 10 km, could depict phenology cycles forobservations, a range of vegetation examined this study.of
We examined the potential of using observations from the EPIC sensor on Deep Space Climate Observatory (DSCOVR)
Summary
The capability to accurately observe vegetation phenology (i.e., seasonal greening and browning) cycles allows us to understand how these cycles are changing in time and space due to climate, urbanization, and other natural and anthropogenic influences [1–4]. Despite being more comprehensive than in-situ observations, the current satellites/sensors that are widely used for this purpose (e.g., the Moderate-resolution Imaging Spectroradiometer (MODIS) onboard Terra and Aqua, Enhanced Thematic Mapper (ETM+) onboard Landsat) have low temporal resolutions (i.e., once every 8 days or longer due to cloud contamination), which is a shortcoming, leaving major voids in required data. This lack of observations is worse for some regions and ecosystems during key phenological stages. More advanced geostationary satellites with the high temporal resolution, such as Himawari-8 and Meteosat Second Generation (MSG), have been found to have the potential to fill this temporal gap and improve monitoring of vegetation phenology [14,15]
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