Name: Bijaya Maharjan
Title: Sensitivity Analysis Between Radar Vegetation Index (RVI) and NDVI for Estimating Net Primary Production and Carbon Stock of Mangrove Forest
The Carnegie Ames Stanford Approach (CASA) model is applicable to estimate NetPrimary Production (NPP) of mangrove forest. The study was focused on mangroveforest NPP and carbon stock estimation, located at coastal zone of Chanthaburiprovince of eastern Thailand. The annual NPP estimation from CASA model seemedlow in mature age comparison with annual NPP estimated from observed carbonstock from field data. This may be the effect of early NDVI saturation beforeNPP stable/decrease. NDVI derived from optical imagery is major parameter todefine NPP of forest. The Radar vegetation index (RVI) measures volumescattering caused by structural elements of canopies derived from dual/fullpolarized PALSAR data along with growth of trees. The strong positivecorrelation was observed between RVI with field based carbon stock estimationover age of plantation. The sensitivity analysis between RVI and NDVI overforest growth had shown that RVI was more sensitivity to medium and high levelof plantation growth than NDVI. So NDVI adjustment using RVI was introduced toestimate further retrieve parameters such as NPP and hence of carbon stock inbetter way with breaking early NDVI saturation point in mature mangrove forest.The annual NPP estimation from conventional CASA model for 15, 17 and 19 yearswere as 28.953, 29.171 and 28.387 gmC/m2 whereas the values were refined as34.701, 35.741 and 36.476 gmC/m2 respectively after implementation ofadjustment approach. Similarly, the RVI generated from PALSAR data had positivecorrelation (R2 = 0.8716) with increment of field carbon stock of mangrovetrees over age of plantation. The amount of carbon stock of mangrove forest atend of 21 years, estimated from CASA model (Landsat) and CASA model afteradjustment of NDVI by RVI were as 0.602 KgC/m2 and 0.668 KgC/m2 respectivelywhereas 0.757 KgC/m2 as field based estimation. Hence the NDVI adjustmentapproach by RVI decreased the error in carbon stock estimation of mature forestsignificantly.