Monitoring Drought Using Coarse-Resolution Polar-Orbiting Satellite Data - Monitoring and Predicting Agricultural Drought: A Global Study - page 64

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NIR against red band measurements for a sample of bare soil pixels. Pixels
falling near the soil line are assumed to be sparsely vegetated, whereas those
farther away, in the direction of increasing NIR and decreasing red, repre-
sent increasing amounts of vegetation. Soil lines may be specific to one soil
type or more general to a variety of soils within an image or satellite data
set. The complexity of the derivation of these distance-based indices has
resulted in inconsistencies in their formulation for assessing vegetation sta-
tus and condition, limiting their applications to regional studies where soil-
vegetation characteristics can be clearly segregated. Improvements to the
PVI have yielded three other PVIs suggested by Perry and Lautenschlager
(1984), and Qi et al. (1994) and referred to as PVI1, PVI2, and PVI3.

Vegetation Indices Based on Orthogonal Transformation Vegetation in-
dices based on orthogonal transformation include the difference vegeta-
tion index (DVI) also suggested by Richardson and Wiegand (1977), the
green vegetation index (GVI) of the tasseled cap transformation (Kauth
and Thomas, 1976), Misra's green vegetation index (MGVI) based on the
Wheeler-Misra transformation (Wheeler et al., 1976; Misra et al., 1977),
and Principal Components Analysis (PCA) (Singh and Harrison, 1985;
Fung and LeDrew, 1988). These indices involve decorrelation of the origi-
nal bands to extract a new set of components that separate vegetation from
other surface materials.

[64],

Line
——
1.5
——
Norm
PgEn

Optimized Indices There is a class of VIs based on semiempirical radiative
transfer theory that use both slope- and distance-based properties of spec-
tral data in red and NIR plots. These indices are referred to as optimized
indices and include the soil-adjusted vegetation index (SAVI) proposed by
Huete (1988). The SAVI aims to minimize the effects of soil background
on the vegetation signal by incorporating a soil adjustment factor into the
denominator of the NDVI equation:

[64],

NIR − RED

SAVI =

L ) · ( 1

+ L ) [5.2]

( NIR + RED +

where L is the soil adjustment factor that takes into account first-order,
differential penetration of red and NIR energy through a canopy in ac-
cordance with Beer's law . There are modified forms of the SAVI that in-
clude the transformed soil-adjusted vegetation index (TSAVI) by Baret and
Guyot (1991), and the modified soil-adjusted vegetation index (MSAVI)
suggested by Qi et al. (1994), based on a modification of the L factor of the
SAVI. All of these modifications are intended to improve correction to the
soil background brightness for different conditions of surface vegetation
cover.
Optimized indices also include the atmosphere resistant vegetation index
(ARVI) by Kaufman and Tanré (1992), the enhanced vegetation index
(EVI) by Huete et al. (1994), and the aerosol-free vegetation index (AFRI)
by Karnieli et al. (2001). These indices incorporate atmosphere and canopy