Abstract
The Vegetation Indices (VI) used for estimation of variations in vegetation cover in past decades. The Fraction of vegetation cover was calculated from pre-computed reflectance database based on inversion of PROSAIL model. It was found that the very low and low forest vegetation cover area was dominated with an area of about 104 Km2 and 69.49 Km2 respectively. The very high forest vegetation cover area is very low of about 24 Km2 . The high and medium vegetation cover forest shows intermediate dominance of about 51.74 Km2 and 57 Km2 in area respectively. The result indicates that NDVI, RVI and PSSRA value closely related to forest vegetation cover. Also, in the regression analysis the same was observed as the high relationship is found between FCOVER AND PSSRA (R2 = 68%) followed by NDVI (R2 = 66%) and RVI (R2 = 65%). The low relationship is found in the relationship of FCOVER and MCARI (R2 = 36.7%) followed by DVI (R2 =53.7%) and IRECI (R2 = 59%).
Highlights
The fraction of vegetation cover (FCOVER) gives the information about the biophysical status of the forest
According to remote sensing techniques, FCOVER may be defined as the vegetated area which is directly visible from the sensor (Purevdor et al, 1998)
We identified that forest vegetation monitoring with FCOVER is a best suited methodology and future change detection analysis can be possible
Summary
The fraction of vegetation cover (FCOVER) gives the information about the biophysical status of the forest. The FCOVER is an imperative variable for many spatial biophysical and biogeochemical models and used for the measurement of land cover change (Zhang, 2006). According to remote sensing techniques, FCOVER may be defined as the vegetated area which is directly visible from the sensor (Purevdor et al, 1998). Quantitative information on the vegetation cover is required in many studies for observing the global and local changes in forest landscapes. With the advent of satellite imaging technology, it is much more common to use remote sensing techniques to monitor forest data, in particular, tropical deforestation. The upcoming of Sentinel 2 satellites offer new open doors for a nonstop checking of the land and vegetation with regards to the climate change and global warming (POENARU, 2017)
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