Literature DB >> 19769091

Near-surface remote sensing of spatial and temporal variation in canopy phenology.

Andrew D Richardson1, Bobby H Braswell, David Y Hollinger, Julian P Jenkins, Scott V Ollinger.   

Abstract

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 CO2 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.

Entities:  

Mesh:

Year:  2009        PMID: 19769091     DOI: 10.1890/08-2022.1

Source DB:  PubMed          Journal:  Ecol Appl        ISSN: 1051-0761            Impact factor:   4.657


  37 in total

1.  Key canopy traits drive forest productivity.

Authors:  Peter B Reich
Journal:  Proc Biol Sci       Date:  2012-01-25       Impact factor: 5.349

2.  The effects of phenological mismatches on demography.

Authors:  Abraham J Miller-Rushing; Toke Thomas Høye; David W Inouye; Eric Post
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2010-10-12       Impact factor: 6.237

3.  Influence of spring and autumn phenological transitions on forest ecosystem productivity.

Authors:  Andrew D Richardson; T Andy Black; Philippe Ciais; Nicolas Delbart; Mark A Friedl; Nadine Gobron; David Y Hollinger; Werner L Kutsch; Bernard Longdoz; Sebastiaan Luyssaert; Mirco Migliavacca; Leonardo Montagnani; J William Munger; Eddy Moors; Shilong Piao; Corinna Rebmann; Markus Reichstein; Nobuko Saigusa; Enrico Tomelleri; Rodrigo Vargas; Andrej Varlagin
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2010-10-12       Impact factor: 6.237

4.  Comparing land surface phenology derived from satellite and GPS network microwave remote sensing.

Authors:  Matthew O Jones; John S Kimball; Eric E Small; Kristine M Larson
Journal:  Int J Biometeorol       Date:  2013-09-05       Impact factor: 3.787

5.  Photographic assessment of temperate forest understory phenology in relation to springtime meteorological drivers.

Authors:  Liang Liang; Mark D Schwartz; Songlin Fei
Journal:  Int J Biometeorol       Date:  2011-05-10       Impact factor: 3.787

6.  Five years of phenological monitoring in a mountain grassland: inter-annual patterns and evaluation of the sampling protocol.

Authors:  Gianluca Filippa; Edoardo Cremonese; Marta Galvagno; Mirco Migliavacca; Umberto Morra di Cella; Martina Petey; Consolata Siniscalco
Journal:  Int J Biometeorol       Date:  2015-05-03       Impact factor: 3.787

7.  Changes in autumn senescence in northern hemisphere deciduous trees: a meta-analysis of autumn phenology studies.

Authors:  Allison L Gill; Amanda S Gallinat; Rebecca Sanders-DeMott; Angela J Rigden; Daniel J Short Gianotti; Joshua A Mantooth; Pamela H Templer
Journal:  Ann Bot       Date:  2015-05-11       Impact factor: 4.357

8.  Later springs green-up faster: the relation between onset and completion of green-up in deciduous forests of North America.

Authors:  Stephen Klosterman; Koen Hufkens; Andrew D Richardson
Journal:  Int J Biometeorol       Date:  2018-05-31       Impact factor: 3.787

9.  Interannual variations and trends in global land surface phenology derived from enhanced vegetation index during 1982-2010.

Authors:  Xiaoyang Zhang; Bin Tan; Yunyue Yu
Journal:  Int J Biometeorol       Date:  2014-03-18       Impact factor: 3.787

10.  Using digital time-lapse cameras to monitor species-specific understorey and overstorey phenology in support of wildlife habitat assessment.

Authors:  Christopher W Bater; Nicholas C Coops; Michael A Wulder; Thomas Hilker; Scott E Nielsen; Greg McDermid; Gordon B Stenhouse
Journal:  Environ Monit Assess       Date:  2010-11-18       Impact factor: 2.513

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