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Estimation of above ground biomass in Horton Plains National Park, Sri Lanka using Optical, thermal and RADAR remote sensing data


A.R. Gunawardena ,

University of Peradeniya, LK
About A.R.
Postgraduate Institute of Agriculture
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S.P. Nissanka,

University of Peradeniya, LK
About S.P.
Department of Crop Science, Faculty of Agriculture
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N.D.K. Dayawansa,

University of Peradeniya, LK
About N.D.K.
Department of Agricultural Engineering , Faculty of Agriculture
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T.T. Fernando

Central Environmental Authority, LK
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A variety of approaches have been developed to estimate the aboveground biomass. However, methods differ in procedure, complexity and time requirement depending on the specific aim of these estimations. Remote Sensing (RS) is popular as a nondestructive method of biomass estimation since it can reduce the measurements and monitoring in the field to a considerable extent. This study focused to estimate above ground biomass of Horton Plains national park of Sri Lanka using ALOS PALSAR, IRS LISS III and Thermal bands of Landsat OLI images. There were 55 field sampling plots used and diameter at breast height, total tree height, and canopy cover percentage of all trees (dbh >10 cm), and slope and GPS locations of each sampling plots were collected. Previously developed relevant allometric equations were used to estimate biomass using DBH and height in each plot. The relationship between backscatter coefficient of the ALOS PALSAR image, Normalized Difference Vegetation Index derived from IRS LISS III image and surface temperature generated form Landsat OLI thermal images were correlated with field estimated biomass to observe there correlation. It was not possible to obtain very strong correlations between these variables and AGB. However, a positive linear correlation between AGB and NDVI was relatively high compared to other vegetation indices. The amount of biomass calculated for three different correlations obtained for NDVI, Backscatter HH, Backscatter HV and land surface temperature are 41.76 t/ha, 38.9 t/ha, 32.5 t/ha and 62.72 t/ha respectively.


Tropical Agricultural Research Vol. 26 (4): 608– 623 (2015)

How to Cite:
Published on 20 Nov 2015.
Peer Reviewed


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