Relationship Between Remotely-sensed Vegetation Indices, Canopy Attributes and Plant Physiological Processes: What Vegetation Indices Can and Cannot Tell Us About the Landscape

By Edward P. Glenn, Alfredo R. Huete, Pamela L. Nagler, S. G. Nelson. Italian National Conference on Sensors, 2008

766 citations recorded by the source corpus.

Vegetation indices (VIs) are among the oldest tools in remote sensing studies. Although many variations exist, most of them ratio the reflection of light in the red and NIR sections of the spectrum to separate the landscape into water, soil, and vegetation. Theoretical analyses and field studies have shown that VIs are near-linearly related to photosynthetically active radiation absorbed by a plant canopy, and therefore to light-dependent physiological processes, such as photosynthesis, occurring in the upper canopy. Practical studies have used time-series VIs to measure primary production and evapotranspiration, but these are limited in accuracy to that of the data used in ground truthing or calibrating the models used. VIs are also used to estimate a wide variety of other canopy attributes that are used in Soil-Vegetation-Atmosphere Transfer (SVAT), Surface Energy Balance (SEB), and Global Climate Models (GCM). These attributes include fractional vegetation cover, leaf area index, roughness lengths for turbulent transfer, emissivity and albedo. However, VIs often exhibit only moderate, non-linear relationships to these canopy attributes, compromising the accuracy of the models. We use case studies to illustrate the use and misuse of VIs, and argue for using VIs most simply as a measurement of canopy light absorption rather than as a surrogate for detailed features of canopy architecture. Used this way, VIs are compatible with “Big Leaf” SVAT and GCMs that assume that canopy carbon and moisture fluxes have the same relative response to the environment as any single leaf, simplifying the task of modeling complex landscapes.

Subfields: Ecology, Environmental Engineering, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/50faad14fc23a2340124d7b551ae52db370d7773

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

In Environmental Engineering

In Global and Planetary Change

Citations in the corpus

Spatial patterns and temporal dynamics in savanna vegetation phenology across the North Australian Tropical Transect (2013, methodology): “The Enhanced Vegetation Index (EVI) is widely used as proxy of canopy “greenness”, which is defined as an integrative composite property of green leaf area, green foliage cover, structure, and leaf chlorophyll content (Glenn et al., 2008; Huete et al., 2002).”
Optical remote sensing and the retrieval of terrestrial vegetation bio-geophysical properties - A review (2015, background): “VIs are defined to enhance spectral features sensitive to a vegetation property while reducing disturbance by combining some spectral bands into a VI (Glenn et al., 2008; Clevers, 2014).”
Unmanned Aerial Vehicles (UAVs): A Survey on Civil Applications and Key Research Challenges (2018, neutral): “In [113], [118], [136], [137], most of the VIs found in the literature have been summarized and discussed.”
Evaluation of Sentinel-2 Red-Edge Bands for Empirical Estimation of Green LAI and Chlorophyll Content (2011, methodology): “include: stepwise multiple linear regression, principal component regression, partial least square regression [41,64,70].”
Experimental Sentinel-2 LAI estimation using parametric, non-parametric and physical retrieval methods - A comparison (2015, background): “VIs are defined with the objective to enhance spectral features sensitive to a vegetation property while reducing disturbance by combining a few spectral bands into a VI (Glenn et al., 2008).”