Terrestrial vegetation exhibits strong seasonal and inter-annual fluctuations, which are associated with changes in the
environmental variables. The understanding of the vegetation dynamics on a long-term basis requires repetitive
observations over many years at temporal and spatial scale compatible with the regional processes. Space-borne
scatterometer though primarily designed for ocean study, have proved advantageous in studying vegetation dynamics at
regional scale. This could be possible due to availability of high repeat cycle data in addition to availability of processed
scatterometer data by SIR algorithm. In the present study, the temporal behavior of Indian tropical-moist-deciduous
forests has been studied using QuikScat (Ku-band) scatterometer data of year 2000. The impact of vegetation growth and
senescence was investigated by comparing σ0 time-series to NDVI and rainfall observations. It was observed that σ0 varies with different scale than the NDVI. The low correlation coefficients also indicate that, the direct relationship
between σ0 and NDVI is either very week or absent. Therefore, inferring that NDVI, which is a measure of the
vegetation greenness or vigor rather than plant water-content or height, is not important for the explanation of the
backscattering behavior. Further, σ0 was minimum during the deciduous period with prevailing high temperature and no
rainfall condition. The temporal changes in backscattering coefficient were modeled for understanding the vegetation
dynamics. The study suggests the suitability of Ku-band space-borne scatterometer data for understanding the seasonal
dynamics of different forest types.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.