Abstract
Intercomparison of satellite-derived vegetation phenology is scarce in remote locations because of the limited coverage area and low temporal resolution of field observations. By their reliable near-ground observations and high-frequency data collection, PhenoCams can be a robust tool for intercomparison of land surface phenology derived from satellites. This study aims to investigate the transition dates of black spruce (Picea mariana (Mill.) B.S.P.) phenology by comparing fortnightly the MODIS normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI) extracted using the Google Earth Engine (GEE) platform with the daily PhenoCam-based green chromatic coordinate (GCC) index. Data were collected from 2016 to 2019 by PhenoCams installed in six mature stands along a latitudinal gradient of the boreal forests of Quebec, Canada. All time series were fitted by double-logistic functions, and the estimated parameters were compared between NDVI, EVI, and GCC. The onset of GCC occurred in the second week of May, whereas the ending of GCC occurred in the last week of September. We demonstrated that GCC was more correlated with EVI (R2 from 0.66 to 0.85) than NDVI (R2 from 0.52 to 0.68). In addition, the onset and ending of phenology were shown to differ by 3.5 and 5.4 days between EVI and GCC, respectively. Larger differences were detected between NDVI and GCC, 17.05 and 26.89 days for the onset and ending, respectively. EVI showed better estimations of the phenological dates than NDVI. This better performance is explained by the higher spectral sensitivity of EVI for multiple canopy leaf layers due to the presence of an additional blue band and an optimized soil factor value. Our study demonstrates that the phenological observations derived from PhenoCam are comparable with the EVI index. We conclude that EVI is more suitable than NDVI to assess phenology in evergreen species of the northern boreal region, where PhenoCam data are not available. The EVI index could be used as a reliable proxy of GCC for monitoring evergreen species phenology in areas with reduced access, or where repeated data collection from remote areas are logistically difficult due to the extreme weather.
Highlights
Vegetation phenology is an important indicator to study the timings of the seasonal progression of plant activities through stages of dormancy, active growth, senescence, and back to dormancy [1,2]
green chromatic coordinate (GCC), enhanced vegetation index (EVI), and normalized difference vegetation index (NDVI) showed a bell-shaped pattern, with a slow increase in spring, a rapid increase culminating with a plateau in July, and a decrease in autumn until reaching a minimum value in winter (Figures 2–4)
Our results showed that EVI performs better than NDVI when compared with PhenoCam (GCC)
Summary
Vegetation phenology is an important indicator to study the timings of the seasonal progression of plant activities through stages of dormancy, active growth, senescence, and back to dormancy [1,2]. Validation of satellite-derived phenology metrics remains uncertain and challenging due to the limited availability of field observations at high temporal and spatial resolutions, mainly for remote locations or areas with difficult accessibility. PhenoCam provides several clear advantages over human observations of phenology because of the ability to collect automatically repeated images at high temporal resolution (daily or hour scale) and across wide spatial scales (from the individual to the landscape). These cameras become useful for remote areas or where the accessibility of sites is prevented by harsh climatic conditions [21,22]. PhenoCam can be considered as a robust tool to evaluate and compare phenological metrics derived from satellite data [14,25,27,28]
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