Estimating above Ground Biomass and Carbon Stock in the Lake Hawassa Watershed, Ethiopia by Integrating Remote Sensing and Allometric Equations
- *Corresponding Author:
- Nigatu Wondrade
Norwegian University of Life Ssciences (NMBU)
Department of Mathematical Sciences and Technology (IMT)
P. O. Box 5003, As, N-1432 Norway
E-mail: [email protected], [email protected]
Received date: June 29, 2015 Accepted date: August 07, 2015 Published date: August 10, 2015
Citation: Wondrade N, Dick OB, Tveite H (2015) Estimating above Ground Biomass and Carbon Stock in the Lake Hawassa Watershed, Ethiopia by Integrating Remote Sensing and Allometric Equations. Forest Res 4:151. doi:10.4172/2168-9776.1000151
Copyright: © 2015 Wondrade N, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
With the increasing concentration of carbon dioxide in the Earth’s atmosphere as the result of deforestation, there is a pressing need to estimate biomass and carbon pools in tropical forests. This is, particularly, essential in Africa where reliable biomass data is lacking. The present study was aimed at classifying land use land cover, estimating above ground biomass using remote sensing data and allometric equations, and determining the importance value of species in Lake Hawassa Watershed. Pantropic allometric equations were used that relate tree variables obtained by non-destructive measurements to the oven dry biomass. Local species specific biomass equations were also used to compare the results. The results indicated that the natural forest had lower mean above ground biomass (200.9 Mg/ha) than the plantation forest (223.6 Mg/ha). The pantropic allometric equations overestimated the above ground biomass by about 13.0% and 20.5% for natural and plantation forests, respectively, compared to the local equations. This variation is likely to be the main source of uncertainty for biomass computed using generalized equations. The species sampled ranged from 1 to 22 per plot and the overall mean stand density was 785 stems/ha. Cupressus lucitanica (60.09%), Grevillea robusta (28.65%), and Eucalyptus citriodora (20.87%) were the species with the highest importance value. The majority of tree species belonged to the diameter at breast height class of 5–25 cm accounting for 79.1% and 73.3% in plantation and natural forests, respectively. The total above ground biomass of the forest in the study area in 2011 was estimated at 1.72 Megatons. Although using generalized allometric equations demonstrated variations in above ground biomass estimates compared to the local species specific equations, results from this research effort can be used in absence of area specific models.