Similarly, the normalized difference water index (NDWI) and land surface
water index (LSWI) are normalized versions of NIR and water absorption band
ratios (Gao 1996; Xiao et al. 2004),
NDWI ¼ q NIR À q 1240nm
ð
Þ = q NIR þ q 1240nm
ð
Þ
ð 1:4Þ
LSWI ¼ q NIR À q 1600nm
ð
Þ = q NIR þ q 1600nm
ð
Þ ;
ð1:5Þ
The global vegetation moisture index (GVMI) has also been used for retrieval
of equivalent water thickness (EWT) in a canopy (Ceccato et al. 2002a, b),
GVMI ¼ q NIR þ 0:1
ð
ÞÀ q SWIR þ 0:02
ð
Þ
½
= q NIR þ 0:1
ð
Þþ q SWIR þ 0:02
ð
Þ
½
ð1:6Þ
In combination, VIs and WIs are important in analyzing canopy ecophysiological functioning, and some model-based studies have suggested that they can
independently estimate canopy chlorophyll and water contents (Zarco-Tejada et al.
2003). Vegetation water indices are further deemed useful in assessing canopy
drying and fire vulnerability (Caccamo et al. 2011). However, there are several
studies showing little if any evidence that SWIR-based indices can sense water
stress (Bates and Hall 1981). For example, Waring et al. (1979) found very small
changes in leaf water content in needle-leaf evergreen conifers subjected to
drought stress.
The ratio- and normalized difference-based VIs have the advantage of minimizing noise and influences attributed to variations in irradiance, clouds and cloud
shadows. Their main disadvantage involve inherent non-linearities associated with
Fig. 1.2 Satellite-derived spectral signatures of various forest canopy types as measured from
MODIS. The corresponding NDVI and EVI values for each forest canopy are shown in the inset.
Sites include Siberian Yakutsk Larch, Hubbard Brook Deciduous Broadleaf Forest, Chamela
Tropical Dry Evergreen Broadleaf Forest, Black Spruce Evergreen Needle-Leaf Forest, H.J.
Andrews Pacific Northwest Evergreen Needle-Leaf Forest, and MaeKlong Tropical Evergreen
Broadleaf Forest
4
A. Huete et al.
water index (LSWI) are normalized versions of NIR and water absorption band
ratios (Gao 1996; Xiao et al. 2004),
NDWI ¼ q NIR À q 1240nm
ð
Þ = q NIR þ q 1240nm
ð
Þ
ð 1:4Þ
LSWI ¼ q NIR À q 1600nm
ð
Þ = q NIR þ q 1600nm
ð
Þ ;
ð1:5Þ
The global vegetation moisture index (GVMI) has also been used for retrieval
of equivalent water thickness (EWT) in a canopy (Ceccato et al. 2002a, b),
GVMI ¼ q NIR þ 0:1
ð
ÞÀ q SWIR þ 0:02
ð
Þ
½
= q NIR þ 0:1
ð
Þþ q SWIR þ 0:02
ð
Þ
½
ð1:6Þ
In combination, VIs and WIs are important in analyzing canopy ecophysiological functioning, and some model-based studies have suggested that they can
independently estimate canopy chlorophyll and water contents (Zarco-Tejada et al.
2003). Vegetation water indices are further deemed useful in assessing canopy
drying and fire vulnerability (Caccamo et al. 2011). However, there are several
studies showing little if any evidence that SWIR-based indices can sense water
stress (Bates and Hall 1981). For example, Waring et al. (1979) found very small
changes in leaf water content in needle-leaf evergreen conifers subjected to
drought stress.
The ratio- and normalized difference-based VIs have the advantage of minimizing noise and influences attributed to variations in irradiance, clouds and cloud
shadows. Their main disadvantage involve inherent non-linearities associated with
Fig. 1.2 Satellite-derived spectral signatures of various forest canopy types as measured from
MODIS. The corresponding NDVI and EVI values for each forest canopy are shown in the inset.
Sites include Siberian Yakutsk Larch, Hubbard Brook Deciduous Broadleaf Forest, Chamela
Tropical Dry Evergreen Broadleaf Forest, Black Spruce Evergreen Needle-Leaf Forest, H.J.
Andrews Pacific Northwest Evergreen Needle-Leaf Forest, and MaeKlong Tropical Evergreen
Broadleaf Forest
4
A. Huete et al.