Comparing time-lapse PhenoCams with satellite observations across the boreal forest of Quebec, Canada

Please always quote using this URN: urn:nbn:de:bvb:20-opus-252213
  • 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) andIntercomparison 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 (R\(^2\) from 0.66 to 0.85) than NDVI (R\(^2\) 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.show moreshow less

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Metadaten
Author: Siddhartha Khare, Annie Deslauriers, Hubert Morin, Hooman Latifi, Sergio Rossi
URN:urn:nbn:de:bvb:20-opus-252213
Document Type:Journal article
Faculties:Philosophische Fakultät (Histor., philolog., Kultur- und geograph. Wissensch.) / Institut für Geographie und Geologie
Language:English
Parent Title (English):Remote Sensing
ISSN:2072-4292
Year of Completion:2021
Volume:14
Issue:1
Article Number:100
Source:Remote Sensing (2022) 14:1, 100. https://doi.org/10.3390/rs14010100
DOI:https://doi.org/10.3390/rs14010100
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 52 Astronomie / 526 Mathematische Geografie
5 Naturwissenschaften und Mathematik / 58 Pflanzen (Botanik) / 580 Pflanzen (Botanik)
Tag:EVI; GCC; Google Earth Engine; NDVI; PhenoCam; Picea mariana; coniferous species
Release Date:2023/05/26
Date of first Publication:2021/12/26
Licence (German):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International