Abstract:
Water content plays an important role in the process
of plant photosynthesis and
biomass accumulation. Many methods have been develo
ped to retrieve canopy leaf water
content from remote sensing data. However, the vali
dity of these methods has not been
verified, which limits their applications. This stu
dy estimates the Leaf Water Content
(LWC) of winter wheat with three most widely used i
ndexes: Normalized Difference
Water Index (NDWI), Simple Ratio (SR), and Shortwave
Infrared Perpendicular Water
Stress Index (SPSI), as well as MODIS short wave an
d near infrared data, and then
compares remote sensing estimates of vegetation wat
er content with field-measured
values measured in concurrent dates. The results in
dicate that the three indexes are
significantly correlated with the LWC of winter whe
at at the 0.01 significance level. They
all have good accuracy with higher than 90%. The in
dexes derived from MODIS bands 6
and 2 were better than those from bands 7 and 2 for
measuring wheat leaf water content,
and the correlations of the former two (NDWI and SR
) were stronger than that of
SPSI
.
Keywords
: Near infrared band, Remote sensing, Short wave in
frared band. Spectral
characteristic index, Validation.
