Abstract:
Forests provide the biggest carbon pool used to counter-balance the concentration of Green
House Gases (GHG) in the atmosphere. Threats of excessive concentration of GHG to climate
patterns has drawn much attention around the world that different measures have been taken.
Knowledge of the amount of Carbon sequestered by forests is important for appropriate
mitigation measures, to this end, various methods are employed for quantification of above
ground biomass (AGB). Field techniques yields accurate results but tedious, time consuming
and sometimes unsafe for workers. Light Detection and Ranging (LiDAR) and Radio Detection
and Ranging (RADAR) are appropriate techniques but involves high costs and complexity in
data processing. AGB estimation based on Unmanned Aerial Vehicle (UAV) images is the
simple and cost-effective technique suited for small and medium size forests.
In the current study, AGB were estimated using UAV images and compared to AGB estimated
based on field observations. The mean AGB estimated from field data was 0.576 t/ha, 0.622
t/ha, and 0.309 t/ha compared to 0.613 t/ha, 0.546 t/ha and 0.245 t/ha estimated using UAV
images in sample plot1, sample plot2 and sample plot3 respectively. Likewise, the Root Mean
Square Error (RMSE) computed for sample plot1 was 0.087 t/ha while for sample plot2 the
RMSE was 0.015 t/ha and for sample plot3 RMSE was 0.516 t/ha. The results suggest the
application of the method for small and medium size forests and is recommended down to local
government authorities and individual companies in Tanzania to collect forest information that
helps combat excessive GHG by taking appropriate measures to prevent much threats.
