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Inter- and intra-annual variations of clumping index derived from the MODIS BRDF product

Cited 45 time in Web of Science Cited 48 time in Scopus
Authors

He, Liming; Liu, Jane; Chen, Jing M.; Croft, Holly; Wang, Rong; Sprintsin, Michael; Zheng, Ting; Ryu, Youngryel; Piseke, Jan; Gonsamo, Alemu; Deng, Feng; Zhang, Yongqin

Issue Date
2016-02
Publisher
Elsevier
Citation
International Journal of Applied Earth Observation and Geoinformation, Vol.44, pp.53-60
Abstract
Clumping index quantifies the level of foliage aggregation, relative to a random distribution, and is a key structural parameter of plant canopies and is widely used in ecological and meteorological models. In this study, the inter- and intra-annual variations in clumping index values, derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) BRDF product, are investigated at six forest sites, including conifer forests, a mixed deciduous forest and an oak-savanna system. We find that the clumping index displays large seasonal variation, particularly for the deciduous sites, with the magnitude in clumping index values at each site comparable on an intra-annual basis, and the seasonality of clumping index well captured after noise removal. For broadleaved and mixed forest sites, minimum clumping index values are usually found during the season when leaf area index is at its maximum. The magnitude of MODIS clumping index is validated by ground data collected from 17 sites. Validation shows that the MODIS clumping index can explain 75% of variance in measured values (bias = 0.03 and rmse = 0.08), although with a narrower amplitude in variation. This study suggests that the MODIS BRDF product has the potential to produce good seasonal trajectories of clumping index values, but with an improved estimation of background reflectance. (C) 2015 Elsevier B.V. All rights reserved.
ISSN
1569-8432
URI
https://hdl.handle.net/10371/199197
DOI
https://doi.org/10.1016/j.jag.2015.07.007
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  • College of Agriculture and Life Sciences
  • Department of Landscape Architecture and Rural System Engineering
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