Ground-based measurements of leaf area index: a review of methods, instruments and current controversies.

By Nathalie Bréda. Journal of Experimental Botany, 2003

1,460 citations recorded by the source corpus.

Subfields: Ecology, Global and Planetary Change, Plant Science

View Paper: https://www.semanticscholar.org/paper/17d6171106a2aa60ddbbcbb1036b1b0923fd6d18

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Citations in the corpus

Seasonal patterns of tropical forest leaf area index and CO2 exchange (2008, methodology): “, 1984; Pierce and Running, 1988; Welles and Cohen, 1996], and especially well suited for determining the relative LAI changes over a year [Breda, 2003; Wang et al., 2004].”
Estimating seasonal variations of leaf area index using litterfall collection and optical methods in four mixed evergreen–deciduous forests (2015, methodology): “Moreover, the seasonality of LAI in a forest is almost impossible to monitor using the first two methods (Bréda, 2003; Macfarlane et al., 2007a).”
Generalizing predictive models of forest inventory attributes using an area-based approach with airborne LiDAR data (2015, methodology): “LAI can be retrieved using light interception-based techniques (Bréda, 2003; Vose, Clinton, Sullivan, & Bolstad, 1995) and, as the LiDAR signal behaves in a manner similar to direct sunlight, some authors have developed approaches to assess LAI from LiDAR data (Hopkinson et al.”
Modeling the flow resistance of woody vegetation using physically based properties of the foliage and stem (2014, background): “…values as high as AL/AS 5 30–70 [V€astil€a et al., 2013; this study] while AL/AS 5 6–19 has been measured for saplings [V€astil€a and J€arvel€a, 2011; Dittrich et al., 2012; Jalonen and J€arvel€a, 2013] and AL/AS 1–13 for mature trees [Cutini et al., 1998; Br eda, 2003; Barclay et al., 2000].”
Extracting leaf area index using viewing geometry effects—A new perspective on high-resolution unmanned aerial system photography (2018, methodology): “Cal-52 ibrated passive transmission measurements combined with gap fraction theory allow to estimate LAI53 (Monsi and Saeki 1953, 2005), and are implemented in commercially available products, for example54 the LAI-2200 from LI-COR Biosciences (Welles and Norman, 1991) or the DEMON instrument from55”
Comparative analysis of three chemometric techniques for the spectroradiometric assessment of canopy chlorophyll content in winter wheat (2010, background): “This implies that the erm LAI should, in the context of this study, be understood as plant rea index (PAI) (Breda, 2003).”
Quantifying the impact of woody material on leaf area index estimation from hemispherical photography using 3D canopy simulations (2016, methodology): “Total 69 woody area and thus WAI can be calculated through querying total (known) woody area of 70 reconstructed trees.”
Modeling approaches to estimate effective leaf area index from aerial discrete-return LIDAR (2009, background): “(2) (Breda, 2003; Solberg et al., 2006): L ¼ 1 k lnðI=I0Þ (2) Since the Eq.”
Comparison of different vegetation indices for the remote assessment of green leaf area index of crops (2011, background): “The ratio of leaf surface area to unit ground surface area, called leaf area index (LAI) (Breda, 2003), describes the potential surface area available for leaf gas exchange between the atmosphere and the terrestrial biosphere (Cowling and Field, 2003).”