Journal
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
Volume 10, Issue 2, Pages 211-219Publisher
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DOI: 10.1016/j.jag.2007.11.004
Keywords
deciduous forest; leaf area index; IRS LISS-IV; above-ground biomass
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This study demonstrates the potentials of IRS P6 LISS-IV high-resolution multispectral sensor (IGFOV similar to 6 m)-based estimation of biomass in the deciduous forests in the Western Ghats of Karnataka, India. Regression equations describing the relationship between IRS P6 LISS-IV data-based vegetation index (NDVI) and field measured leaf area index (ELAI) and estimated above-ground biomass (EAGB) were derived. Remote sensing (RS) data-based leaf area index (PLAI) image is generated using regression equation based on NDVI and ELAI (r(2) = 0.68, p <= 0.05). RS-based above-ground biomass (PAGB) image was generated based on regression equation developed between PLAI and EAGB (r(2) = 0.63, p <= 0.05). The mean value of estimated above-ground biomass and RS-based above-ground biomass in the study area are 280(+/- 72.5) and 297.6(+/- 55.2) Mg ha(-1), respectively. The regression models generated in the study between NDVI and LAI; LAI and biomass can also help in generating spatial biomass map using RS data alone. LISS-IV-based estimation of biophysical parameters can also be used for the validation of various coarse resolution satellite products derived from the ground-based measurements alone. (c) 2007 Elsevier B.V. All rights reserved.
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