3.6. The use of vegetation indices as NDVI concept to
assess forest degradation
Vegetation indices are the quantitative measure of measuring
biomass or vegetation vigour, usually formed by a combination of several
spectral bands; whose values are added, divided or multiplied in order to yield
a single value that indicates the amount or vigour of vegetation. A variety of
vegetation indices have been developed, with most commonly using red and near
infrared regions of the spectrum to emphasize the difference between strong
absorption of red
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electromagnetic radiation and the strong scatter of near infrared
radiation. The simplest form of vegetation index is a ratio between near
infrared and red reflectance and it is high for healthy living vegetation.
Literature survey revealed wide disagreement regarding the biomass and
vegetation indices relationship. Many studies report a significant positive
relationship ( Boyad et al., 1999 ) while some results showed poor relationship
( Foody et al.,2003,schlerf et al.,2005).
The normalized difference index is one of the most commonly
used vegetation indices in many applications relevant to analysis of
biophysical parameter of forests. Over past two decades its utility has been
well demonstrated in satellite assessment and monitoring of global vegetation
cover (Huete and Liu,1994,leprieur et al 2000). The strength of NDVI is in its
rationing concept which reduces many form of multiplicative noise present in
multiple bands. However, conclusions about its value vary depending on the use
of specific biophysical parameters and characteristics of the study area. (Deo,
2008).It is computed by the product of the ratio of two electro-magnetic
wavelengths (near infrared- red )/(near infrared+red). Vegetation has a high
near chlorophyll pigments and the value of NDVI tends to one. In contrast of
this, clouds, water, snow etc. have a high red reflectance than near-infrared
and these features yield negatives NDVI value. Rocks and bare soil also have
similar reflectance and usually zero value of NDVI;
The saturation of the relationship between biomass and NDVI is
also a well known problem. This can be explained by the fact that as canopy
increases, the amount of red light that can be absorbed by leaves reaches a
peak while near-infrared (NIR) reflectance increases because of multiples
scattering with leaves. The imbalance between a slight decrease in the red and
high NIR reflectance results in a slight change in the NDVI ratio and thus,
yield poor relationship with biomass (Tenkabail et al., 2000). Further, Rauste
(2005) observed that saturation level is also dependent on the tree species,
forest types as well as the ground surface types. Therefore, a suitable
relationship of vegetation indices and biomass is crucial in assessment of
biomass in different circumstances and a matter of more research work. The
usefulness of remote sensing in such work depends on the strength of the
relationships developed with respect to a particular type of forests and its
geographical location.
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