RyuVerfaillieMacfarlaneEtAl2012
Référence
Ryu, Y., Verfaillie, J., Macfarlane, C., Kobayashi, H., Sonnentag, O., Vargas, R., Ma, S., Baldocchi, D.D. (2012) Continuous observation of tree leaf area index at ecosystem scale using upward-pointing digital cameras. Remote Sensing of Environment, 126:116-125. (Scopus 
)
Résumé
Understanding the dynamics of leaf area index (LAI) at ecosystem scale is critical for evaluating and modeling the response of vegetation to environmental variability and change. We present an approach for quantifying daily ecosystem LAI that integrates automatic acquisition of a small number of reference photos, viewed towards the zenith, and a larger number of photos covering a spatially extensive area that were manually acquired during periodic field trips. We present an image archive spanning three years for an oak-savanna ecosystem in California to identify the timing of phenological and disturbance events, and to quantify the seasonal to interannual variability of tree LAI at ecosystem scale. The digital camera-derived LAI, corrected for clumping effects, agreed well (r 2=0.94, root mean square error=0.05) with independent estimates of LAI from litterfall traps and the LAI-2000 Plant Canopy Analyzer. Using the Moderate Resolution Imaging Spectroradiometer (MODIS) LAI product, which combined grass and tree LAI, we obtained realistic seasonal patterns of ecosystem LAI that corresponded with tree LAI from the digital cameras for the period when grass was dead. The digital camera method is an easy and inexpensive way to monitor LAI at ecosystem scale. This method can be used for testing and improving phenology models, evaluating remote-sensing-derived LAI products, and quantifying forest structures in rapidly changing environments. © 2012 Elsevier Inc.
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@ARTICLE { RyuVerfaillieMacfarlaneEtAl2012,
AUTHOR = { Ryu, Y. and Verfaillie, J. and Macfarlane, C. and Kobayashi, H. and Sonnentag, O. and Vargas, R. and Ma, S. and Baldocchi, D.D. },
TITLE = { Continuous observation of tree leaf area index at ecosystem scale using upward-pointing digital cameras },
JOURNAL = { Remote Sensing of Environment },
YEAR = { 2012 },
VOLUME = { 126 },
PAGES = { 116-125 },
NOTE = { cited By 63 },
ABSTRACT = { Understanding the dynamics of leaf area index (LAI) at ecosystem scale is critical for evaluating and modeling the response of vegetation to environmental variability and change. We present an approach for quantifying daily ecosystem LAI that integrates automatic acquisition of a small number of reference photos, viewed towards the zenith, and a larger number of photos covering a spatially extensive area that were manually acquired during periodic field trips. We present an image archive spanning three years for an oak-savanna ecosystem in California to identify the timing of phenological and disturbance events, and to quantify the seasonal to interannual variability of tree LAI at ecosystem scale. The digital camera-derived LAI, corrected for clumping effects, agreed well (r 2=0.94, root mean square error=0.05) with independent estimates of LAI from litterfall traps and the LAI-2000 Plant Canopy Analyzer. Using the Moderate Resolution Imaging Spectroradiometer (MODIS) LAI product, which combined grass and tree LAI, we obtained realistic seasonal patterns of ecosystem LAI that corresponded with tree LAI from the digital cameras for the period when grass was dead. The digital camera method is an easy and inexpensive way to monitor LAI at ecosystem scale. This method can be used for testing and improving phenology models, evaluating remote-sensing-derived LAI products, and quantifying forest structures in rapidly changing environments. © 2012 Elsevier Inc. },
AFFILIATION = { Department of Landscape Architecture and Rural Systems Engineering, Seoul National University, Seoul, South Korea; Department of Environmental Science, Policy and Management, UC Berkeley, Berkeley, United States; CSIRO, Private Bag No. 5, Wembley, WA 6913, Australia; Research Institute for Global Change, Japan Agency for Marine-Earth Science and Technology, Japan; Département de géographie, Université de Montréal, Montréal, Canada; Department of Plant and Soil Sciences, Delaware Environmental Institute, University of Delaware, Newark, DE 19717, United States },
AUTHOR_KEYWORDS = { Clumping index; Digital camera; Digital cover photography; Disturbance; Gap fraction; Leaf area index; MODIS; Remote sensing },
DOCUMENT_TYPE = { Article },
DOI = { 10.1016/j.rse.2012.08.027 },
SOURCE = { Scopus },
URL = { https://www.scopus.com/inward/record.uri?eid=2-s2.0-84865829516&doi=10.1016%2fj.rse.2012.08.027&partnerID=40&md5=18aaa4bb1253f03b2f834f82fb77c947 },
}
