remote sensing Article Use of Remotely Sensed Data to Enhance Estimation of Aboveground Biomass for the Dry Afromontane Forest in South-Central Ethiopia Habitamu Taddese 1,2,* , Zerihun Asrat 2,3 , Ingunn Burud 1, Terje Gobakken 3 , Hans Ole Ørka 3 , Øystein B. Dick 1 and Erik Næsset 3 1 Faculty of Science and Technology, Norwegian University of Life Sciences, P.O. Box 5003, 1432 Ås, Norway;
[email protected] (I.B.);
[email protected] (Ø.B.D.) 2 Wondo Genet College of Forestry and Natural Resources, Hawassa University, P.O. Box 128, Shashemene 3870006, Ethiopia;
[email protected] 3 Faculty Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, 1432 Ås, Norway;
[email protected] (T.G.);
[email protected] (H.O.Ø.);
[email protected] (E.N.) * Correspondence:
[email protected]; Tel.: +47-4671-8534 Received: 31 July 2020; Accepted: 11 October 2020; Published: 13 October 2020 Abstract: Periodic assessment of forest aboveground biomass (AGB) is essential to regulate the impacts of the changing climate. However, AGB estimation using field-based sample survey (FBSS) has limited precision due to cost and accessibility constraints. Fortunately, remote sensing technologies assist to improve AGB estimation precisions. Thus, this study assessed the role of remotely sensed (RS) data in improving the precision of AGB estimation in an Afromontane forest in south-central Ethiopia. The research objectives were to identify RS variables that are useful for estimating AGB and evaluate the extent of improvement in the precision of the remote sensing-assisted AGB estimates beyond the precision of a pure FBSS.