Published Date
Received: 17 April 2015 / Revised: 22 July 2015 / Accepted: 31 July 2015 / Published: 4 August 2015
Author
Abstract
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For further details log on website :
http://www.mdpi.com/2073-445X/4/3/656
Received: 17 April 2015 / Revised: 22 July 2015 / Accepted: 31 July 2015 / Published: 4 August 2015
Author
1
European Commission, Joint Research Centre, Institute for Environment and Sustainability, Via E. Fermi, 2749, I-21027 Ispra (VA), Italy
2
Graduate School of Agriculture, Kyoto University, Oiwake-cho, Kitashirakawa, Sakyo-ku, Kyoto 606-8502, Japan
3
Department of International Studies, Graduate School of Frontier Science, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa-shi, Chiba 277-8563, Japan
*
Author to whom correspondence should be addressed.
Academic Editor: Nophea Sasaki
Received: 17 April 2015 / Revised: 22 July 2015 / Accepted: 31 July 2015 / Published: 4 August 2015
(This article belongs to the Special Issue Carbon Emission Reductions and Removals in Tropical Forests)
Abstract
This study investigates how two existing pan-tropical above-ground biomass (AGB) maps (Saatchi 2011, Baccini 2012) can be combined to derive forest ecosystem specific carbon estimates. Several data-fusion models which combine these AGB maps according to their local correlations with independent datasets such as the spectral bands of SPOT VEGETATION imagery are analyzed. Indeed these spectral bands convey information about vegetation type and structure which can be related to biomass values. Our study area is the island of Borneo. The data-fusion models are evaluated against a reference AGB map available for two forest concessions in Sabah. The highest accuracy was achieved by a model which combines the AGB maps according to the mean of the local correlation coefficients calculated over different kernel sizes. Combining the resulting AGB map with a new Borneo land cover map (whose overall accuracy has been estimated at 86.5%) leads to average AGB estimates of 279.8 t/ha and 233.1 t/ha for forests and degraded forests respectively. Lowland dipterocarp and mangrove forests have the highest and lowest AGB values (305.8 t/ha and 136.5 t/ha respectively). The AGB of all natural forests amounts to 10.8 Gt mainly stemming from lowland dipterocarp (66.4%), upper dipterocarp (10.9%) and peat swamp forests (10.2%). Degraded forests account for another 2.1 Gt of AGB. One main advantage of our approach is that, once the best fitting data-fusion model is selected, no further AGB reference dataset is required for implementing the data-fusion process. Furthermore, the local harmonization of AGB datasets leads to more spatially precise maps. This approach can easily be extended to other areas in Southeast Asia which are dominated by lowland dipterocarp forest, and can be repeated when newer or more accurate AGB maps become available.
This is an open access article distributed under the Creative Commons Attribution License (CC BY 4.0).
For further details log on website :
http://www.mdpi.com/2073-445X/4/3/656
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