Estimating and Mapping of Carbon Stocks based on Remote Sensing, GIS and Ground Survey in the Menagesha Suba State Forest, Ethiopia

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Addis Ababa Universty


As carbon dioxide increases in the Earth’s atmosphere, the rise in average temperature may provoke changes in the environment. As a result, the need to sequester carbon becomes urgent, and one of the options we have is to use the potential of forests to do it by enhancing assimilation of CO2 through photosynthesis. Menagesha Suba forest is one of the oldest conserved forests in Ethiopia which is located about 45 km southwest of Addis Ababa. This research aimed to develop a model for estimating carbon stock at landscape level based on statistical correlation between stock carbon measured at plot level and the associated spectral characteristics. Estimation of carbon stocks in the field was conducted in February at 63 randomly located sample plots each with an area of 250 m2. Remote sensing data were used to develop a model with Landsat TM and ETM+ images acquired in January 1984 and 2005 respectively. The following steps were used: 1) All of the data were referenced to the same projection. 2) The carbon stock of the forest fixed samples was calculated. 3) The Landsat images were processed and indices were created from the Landsat images. 4) The model of carbon stock estimation was formulated with the biomass of the forest fixed samples, corresponding to the Landsat TM images. This study concludes that neither spectral bands nor vegetation indices and the texture measures alone are sufficient to establish an effective model for carbon estimation in the study areas. But multiple regression models that consist of spectral and textural signatures improve carbon stock estimation performance. Using these models, the total estimated forest carbon stock of Menagesha forest in 1984 and 2005 were approximately 1,019,704 tons and 1,153,471 tons with the average 265 and 300 tons per ha respectively. During 1984 – 2005, plantation in Menagesha Suba State forest has resulted in increase in forest carbon stocks of about 113,766 tons. From view of forest management and periodic carbon stocking estimation, the study provides substantial evidence for application of GIS and Remote sensing techniques combined with field inventory data sets to produce periodic forest inventory data to develop forest management guide lines for the country at large, and forest enterprises in particular. Key words: Carbon density, Carbon stock, GIS, Menagesha Suba, Regression analysis, Remote Sensing, Texture measures, Vegetation Indices



Carbon density, Carbon stock, GIS, Menagesha Suba, Regression analysis, Remote Sensing, Texture measures, Vegetation Indices