Exploring discrepancies between in situ phenology and remotely derived phenometrics at NEON sites. Issue 1 (27th January 2022)

• Record Type: Journal Article
• Authors: Donnelly, Alison; Yu, Rong; Jones, Katherine; Belitz, Michael; Li, Bonan; Duffy, Katharyn; Zhang, Xiaoyang; Wang, Jianmin; Seyednasrollah, Bijan; Gerst, Katherine L.; Li, Daijiang; Kaddoura, Youssef; Zhu, Kai; Morisette, Jeffrey; Ramey, Colette; Smith, Kathleen
• Is Part Of: Ecosphere. Volume 13:Issue 1(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-01-27
• Subjects: in situ phenology -- moderate resolution imaging spectroradiometer -- NEON -- Phenesse estimates -- PhenoCam -- Special Feature: Harnessing the NEON Data Revolution -- visible infrared imaging radiometer suite; Ecology -- Periodicals; Ecology; Periodicals; 577.05
• DOI: 10.1002/ecs2.3912
• Languages: English
• ISSNs: 2150-8925

Abstract

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.