Use of digital webcam images to track spring green-up in a deciduous broadleaf forest

By Andrew D. Richardson, J. Jenkins, B. Braswell, David Y. Hollinger, Scott V. Ollinger, Marie-Louise Smith. Oecologia, 2007

621 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/ae674eb605d0a48b7d79abe9d00670e35819b985

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Citations in the corpus

Tracking the structural and functional development of a perennial pepperweed (Lepidium latifolium L.) infestation using a multi-year archive of webcam imagery and eddy covariance measurements (2011, methodology): “A popular way to synthesize RGB color space information obtained from digital camera photographs is through color indices, i.e. algebraic combinations of RGB brightness levels such as excess green (Richardson et al., 2007; Woebbecke et al., 1995).”
Digital repeat photography for phenological research in forest ecosystems (2012, methodology): “All sites are part of the PhenoCam network (http://phenocam.unh.edu), a recent initiative to continuously monitor phenology at ecosystem scale with image archives of digital landscape images across the US and adjacent Canada (Richardson et al., 2007, 2009a).”
Budburst and leaf area expansion measured with a novel mobile camera system and simple color thresholding (2009, positive): “For comparison, using entire images and the algebraic sum of %R+2G‐B as a measure of increasing green in images ( Richardson et al., 2007 ) resulted in a mean RMS error of 99.3cm 2 with a maximum error of 221.7cm 2 and anr 2 for a linear best fit regression”
Tracking the rhythm of the seasons in the face of global change: phenological research in the 21st century. (2009, methodology): “Increasing spatial extent often implies consideration of more than one species and, for both remote and proximate sensors, understanding how discrete life events among different species will impact various measurements remains an active area of research (Chuine et al. 2000; Schwartz et al. 2002; Gra”
Latitudinal patterns of magnitude and interannual variability in net ecosystem exchange regulated by biological and environmental variables (2009, result): “For example, one modeling analysis (Richardson et al., 2007a) suggested that, at the annual time step, about 40% of the variance in modeled NEE could be attributed to variation in environmental drivers, and 55% to variation in the biotic response to this forcing (i.e., basal rates and environmental…”