Exploring discrepancies between in situ phenology and remotely derived phenometrics at NEON sites
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Author
Donnelly, A.Yu, R.
Jones, K.
Belitz, M.
Li, B.
Duffy, K.
Zhang, X.
Wang, J.
Seyednasrollah, B.
Gerst, K.L.
Li, D.
Kaddoura, Y.
Zhu, K.
Morisette, J.
Ramey, C.
Smith, K.
Affiliation
School of Natural Resources and the Environment, University of ArizonaIssue Date
2022
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John Wiley and Sons IncCitation
Donnelly, A., Yu, R., Jones, K., Belitz, M., Li, B., Duffy, K., Zhang, X., Wang, J., Seyednasrollah, B., Gerst, K. L., Li, D., Kaddoura, Y., Zhu, K., Morisette, J., Ramey, C., & Smith, K. (2022). Exploring discrepancies between in situ phenology and remotely derived phenometrics at NEON sites. Ecosphere.Journal
EcosphereRights
Copyright © 2022 The Author(s). Ecosphere published by Wiley Periodicals LLC on behalf of The Ecological Society of America. This is an open access article under the terms of the Creative Commons Attribution License.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
In recent decades, the use of satellite sensors, near-surface cameras, and other remote methods for monitoring vegetation phenology at landscape and higher scales has become increasingly common. These technologies provide a means to determine the timing of phenophases and growing season length at different spatial resolutions; coverage that is not attainable by human observers. However, in situ ground observations are required to validate remotely derived phenometrics. Despite increased knowledge and expertise there still remains the persistent challenge of reconciling ground observations at the individual plant level with remotely sensed (RS) phenometrics at landscape or larger scales. We compared the timing of in situ phenophase estimates (spring and autumn) with a range of corresponding remote sensing (moderate resolution imaging spectroradiometer [MODIS], visible infrared imaging radiometer suite [VIIRS], PhenoCam) phenometrics across five terrestrial sites in the United States' NEON (Harvard Forest [MA] [HARV], Onaqui [UT] [ONAQ], Abby Road [WA] [ABBY], Disney Wilderness Preserve [FL] [DSNY], and Ordway-Swisher Biological Station [FL] [OSBS]) focusing on the 3-year period from 2017 to 2019. Our main objective was to explore potential reasons for the observed discrepancies between in situ and RS phenometrics and to determine which technologies were better able to capture ground observations. Statistically significant relationships were strongest (p < 0.001) for spring phenophases, while the only RS phenometrics significantly correlated with in situ estimates of autumn phenophases were leaf fall (p < 0.01) and leaves (p < 0.000). In particular, root mean square error (RMSE) (mean bias error [MBE]) for MODIS-Enhanced Vegetation Index-2 band (EVI2), VIIRS-EVI2, and PhenoCam-green chromatic coordinate (GCC) derived early spring transition dates indicated overall differences of 21.7 days (−4.6 days), 28.4 days (−1.2 days), and 24.1 days (11.9 days) from in situ estimates of early leaf-out dates. In autumn, RMSE/MBE was smallest (10.9 days/−2.2 days) between phenesse estimates (95th percentile date) of the latest date of in situ leaf fall and VIIRS derived end of senescence, compared to the equivalent phenometric derived from MODIS (13.5 days/7.7 days) and PhenoCam (GCC greenness-falling) (13.8 days/−5.1 days). Overall, discrepancies between in situ and RS phenology related to scale, species availability, and the short duration of the time series (3 years). However, as the NEON project progresses these challenges are expected to be reduced as more data become available. © 2022 The Author(s). Ecosphere published by Wiley Periodicals LLC on behalf of The Ecological Society of America.Note
Open access journalISSN
2150-8925Version
Final published versionae974a485f413a2113503eed53cd6c53
10.1002/ecs2.3912
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Except where otherwise noted, this item's license is described as Copyright © 2022 The Author(s). Ecosphere published by Wiley Periodicals LLC on behalf of The Ecological Society of America. This is an open access article under the terms of the Creative Commons Attribution License.