Peat swamp forest has been recognized as ecosystem capable of storing up a large amount of carbon. This paper describes a development of carbon mass estimation models using active remote sensing data. The objective of this study was to develop carbon mass volume estimation model using active remote sensing, ALOS PALSAR data. The models were basically developed on the basis of relationship between mean carbon mass and ALOS PALSAR backscatter value of HH and HV and their synthetic bands derivedfrom various pixel sizes, i.e.,(a) 1 x 1 pixel, (b) 3 x 3 pixel and (c) 5 x 5 pixel. The study found agood correlation coefficients between the backscatter value and the stock of carbon. The study also showedthat the best correlation was provided by HV, better than those obtained using HH and HH/HV. The study identified best modelas ŷ=-5,337HV 2-111,8HV-480,1;R²=0,86 and 3x3 pixel