%0 Journal Article
%T Estimation of Above Ground Biomass in Forests Using Alos Palsar Data in Kericho and Aberdare Ranges
%A Eunice Wamuyu Maina
%A Patroba Achola Odera
%A Mwangi James Kinyanjui
%J Open Journal of Forestry
%P 79-96
%@ 2163-0437
%D 2017
%I Scientific Research Publishing
%R 10.4236/ojf.2017.72006
%X Above Ground Biomass is one of the six pools identified in the inventory of forest resources and estimation of greenhouse gas emissions and sinks from the forestry sector. The pool varies by management practices in different agro-ecological or agro-climatic zones in forests. The quantification of above ground biomass (AGB) hence carbon sequestration in forests has been very difficult due to the immense costs required. This research was done to estimate AGB using ALOS PALSAR L band data (HH, HV polarisation) acquired in 2009 in relation with ground measurements data in Kericho and Aberdares ranges in Kenya. Tree data information was obtained from ground measurement of DBH and tree heights in 100 circular plots of 15 m radius, by use of random sampling technique. ALOS PALSAR image is advantageous for its active microwave sensor using L-band frequency to achieve cloud free imageries, and the ability of long wavelength cross-polarization to estimate AGB accurately for tropical forests. The variations result between Natural and plantation forest for measured and estimated biomass in Kericho HV band regression value was 0.880 and HH band was 0.520. In Aberdare ranges HV regression value of 0.708 and HH band regression value of 0.511 for measured and estimated biomass respectively. The variations can be explained by the influence of different management regimes induced human disturbances, forest stand age, density, species composition, and trees diameter distribution. However, further research is required to investigate how strong these factors affect relationship between AGB and Alos Palsar backscatters.
%K Above Ground Biomass Estimation
%K Green House Gas
%K Carbon Credits
%K Alos Palsar Backscatter
%K Cross-Polarization
%K Regression Analysis
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=74783