Chlorophyll content in eucalypt vegetation at the leaf and canopy scales as derived from high resolution spectral data

Abstract

The physiological status of forest canopy foliage is influenced by a range of factors that affect leaf pigment content and function. Recently, several indices have been developed from remotely sensed data that attempt to provide robust estimates of leaf chlorophyll content. These indices have been developed from either hand-held spectroradiometer spectra or high spectral resolution (or hyperspectral) imagery. We determined if two previously published indices (Datt 1999), which were specifically developed to predict chlorophyll content in eucalypt vegetation by remote sensing at the leaf scale, can be extrapolated accurately to the canopy. We derived the two indices from hand-held spectroradiometer data of eucalypt leaves exhibiting a range of insect damage symptoms. We also derived the indices from spectra obtained from high spectral and spatial resolution Compact Airborne Spectrographic Imager 2 (CASI-2) imagery to determine if reasonable estimates at a scale of < 1 m can be achieved. One of the indices (R 850/R 710 index, where R is reflectance) derived from hand-held spectroradiometer data showed a moderate correlation with relative leaf chlorophyll content (r = 0.59, P < 0.05) for all dominant eucalypt species in the study area. The R (850)/R (710) index derived from CASI-2 imagery yielded slightly lower correlations over the entire data set (r = 0.42, P < 0.05), but correlations for individual species were high (r = 0.77, P < 0.05). A scaling analysis indicated that the R (850)/R (710) index was strongly affected by soil and water cover types when pixels were mixed, but appeared to be invariant to changes in proportions of understory, which may limit its application.

Non-destructive determination of maize leaf and canopy chlorophyll content

“…On the contrary, it i s well known that the distribution of Chl among leaves ultimately depends on the canopy acclimation to light penetration (e.g., Kull, 2002), characteristics of each canopy species, and the environment. Further, the distribution of Chl within a canopy can vary considerably as a function of time and space, making the estimation of canopy Chi content through destructive sampling a labor-intensive and expensive process (e.g., Coops et al, 2003).…”

Crown‐scale evaluation of spectral indices for defoliated and discoloured eucalypts

“…The possibility of routine assessments of forest canopy health utilizing remote sensing technologies has increased in recent years through advances in our understanding of the spectral reflectance properties of vegetation, including eucalyptus-dominated forests (Coops et al 1997, 2003b, Datt 1998, 1999b, Stone et al 2001, Pietrzykowski et al 2006. During the growth of forest trees, a multitude of stressors (biotic or abiotic) can result in the development of stress symptoms (or strains) (Lichtenthaler 1996).…”

“…Chlorophyll content is widely regarded as a generic indicator of plant stress (Carter 1993, Lichtenthaler 1996, Gitelson et al 2003, Sampson et al 2003 and methods to quantify chlorophyll content in eucalypts with remote sensing have been developed (Datt 1998, 1999b, Coops et al 2003b. However, chlorophyll content can vary widely with leaf age in eucalypts (Choinski Jr et al 2003, Close et al 2004) and other genera (Mohammed et al 2000, Sims andGamon 2002).…”

“…through leaf-scale studies, using leaves with varying symptom levels or with varying concentrations of pigments such as chlorophyll (Carter 1993, 1994, Datt 1999a, Gamon and Surfus 1999, Mohammed et al 2000, Maccioni et al 2001, Stone et al 2001, Coops et al 2003b, Coops and Stone 2005, Pontius et al 2005, Pietrzykowski et al 2006. While diagnostic features of spectra from individual leaves contribute to assessment of tree crown health, reflectance of canopies is also influenced by whole-tree features such as foliar density, leaf shape and leaf orientation (Asner 1998) as well as non-vegetation components and background reflectance (Rondeaux et al 1996, Zarco-Tejada et al 2005.…”

Applying hyperspectral imaging to explore natural plant diversity towards improving salt stress tolerance

“…In parallel, experiments using HSI techniques for detection of fungal infections in fruits of citrus, leaves of sugar beet, wheat and maize have proven the applicability of the technique (Lorente et al, 2013, Mahlein et al, 2010Hillnhütter et al, 2011, Firrao et al, 2010Yao et al, 2010, Bauriegel and Herppich, 2014, Williams et al, 2012. Nowadays, HSI methodologies based on various indices have been mostly used for detection of photosynthetic pigments like chlorophylls, carotenoids as well as of the other major compounds in leaves and fruits, such as anthocyanins and flavonoids (Deepak et al, 2015;Matros and Mock, 2013, Hölscher et al, 2009, Zhao et al, 2005, Coops et al, 2003, Ferri et al, 2004.…”