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Near‐surface remote sensing of spatial and temporal variation in canopy phenology
Author(s) -
Richardson Andrew D.,
Braswell Bobby H.,
Hollinger David Y.,
Jenkins Julian P.,
Ollinger Scott V.
Publication year - 2009
Publication title -
ecological applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.864
H-Index - 213
eISSN - 1939-5582
pISSN - 1051-0761
DOI - 10.1890/08-2022.1
Subject(s) - phenology , deciduous , environmental science , canopy , taiga , context (archaeology) , spatial variability , remote sensing , temperate deciduous forest , physical geography , ecology , geography , biology , statistics , mathematics , archaeology
There is a need to document how plant phenology is responding to global change factors, particularly warming trends. “Near‐surface” remote sensing, using radiometric instruments or imaging sensors, has great potential to improve phenological monitoring because automated observations can be made at high temporal frequency. Here we build on previous work and show how inexpensive, networked digital cameras (“webcams”) can be used to document spatial and temporal variation in the spring and autumn phenology of forest canopies. We use two years of imagery from a deciduous, northern hardwood site, and one year of imagery from a coniferous, boreal transition site. A quantitative signal is obtained by splitting images into separate red, green, and blue color channels and calculating the relative brightness of each channel for “regions of interest” within each image. We put the observed phenological signal in context by relating it to seasonal patterns of gross primary productivity, inferred from eddy covariance measurements of surface–atmosphere CO 2 exchange. We show that spring increases, and autumn decreases, in canopy greenness can be detected in both deciduous and coniferous stands. In deciduous stands, an autumn red peak is also observed. The timing and rate of spring development and autumn senescence varies across the canopy, with greater variability in autumn than spring. Interannual variation in phenology can be detected both visually and quantitatively; delayed spring onset in 2007 compared to 2006 is related to a prolonged cold spell from day 85 to day 110. This work lays the foundation for regional‐ to continental‐scale camera‐based monitoring of phenology at network observatory sites, e.g., National Ecological Observatory Network (NEON) or AmeriFlux.