Advances in remote sensing, 2013; 2 : 1-9A study was conducted to estimate the forest cover change, quantify and map tree above-ground carbon stock using Re- mote sensing and GIS techniques together with forest inventory. Landsat images of 1980, 1995 and 2010 acquired dur- ing dry season were used in the estimation of cover changes. Supervised image classification using Maximum Likeli- hood Classifier was performed in ERDAS Imagine software to analyze the images and further analysis was performed in Arc GIS 9.3 software. Stratified sampling procedure was used to select concentric inventory plots in Pugu Forest Re- serve (PFR) and Kazimzumbwi Forest Reserve (KFR). Plots were laid according to NAFORMA, and the tree parame- ters in each sampling plot were collected. A Microsoft Excel spreadsheet was used to compute the above-ground bio- mass for each plot using an empirical equation relating wood basic density and tree height. The above-ground carbon was calculated using a conversion factor of 0.49. Geostatistical method in ArcGIS was used to analyze and map carbon. Results revealed that for the periods 1980-1995 and 1995-2010, Closed Forest in PFR decreased by 4.5% and 25.3% respectively, while for KFR, Closed Forest decreased by 11.9% and 31.3% respectively. The mean carbon density for PFR and KFR were respectively 5.72 tC/ha and 0.98 tC/ha while carbon stocks were 14 730.41 tC and 7 206.46 tC re- spectively. The revealed low carbon densities were attributable to decline in area under Closed Forest in the two Forest Reserves. The study recommends concerted efforts to enhance proper management of the forests so that the two forest reserves may contribute to REDD initiatives.