Inference of vegetation distribution and
characteristics from remote sensing has usually been
based on the difference between vegetation reflectance
in the red and near-infrared channels (which yields the
Normalized Difference Vegetation Index, NDVI [69].
Some other channels such as the shortwave infrared
and thermal infrared have been also used, yielding
other indices of vegetation status. For example, the
Normalized Difference Infrared Index (NDII) is a
widely employed measure of vegetation water status
based on near and shortwave infrared channels.
Compared with VIS/IR remote sensing, microwave
remote sensing has the advantage of not requiring
cloud-free conditions and also has unique applications
such as the ability to directly sense soil moisture.
While the relatively coarse spatial resolution (several
km) of satellite passive microwave instruments makes
them most useful for regional and global studies,
active microwave instruments such as synthetic
aperture radar (SAR) offer spatial resolution similar to
that of high-resolution visible and infrared satellite
imaging (tens of m) and are suitable for field-scale
monitoring and precision agriculture applications.
Combining information from different microwave bands and from microwave and visible/infrared bands
offers particularly promising avenues for maximizing
the usefulness of available and upcoming remote
sensing modalities.