Assessment of Above-Ground Biomass of Borneo Forests through a New Data-Fusion Approach Combining Two Pan-Tropical Biomass Maps
Assessment of Above-Ground Biomass of Borneo Forests through a New Data-Fusion Approach Combining Two Pan-Tropical Biomass Maps
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通过结合两张泛热带生物量图的新数据融合方法评估婆罗洲森林的地上生物量
DOI：
10.3390/land4030656
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发表时间：
2015
期刊：
影响因子：
3.9
通讯作者：
M. Nakayama
中科院分区：
文献类型：
--
作者：
A. Langner;F. Achard;C. Vancutsem;Jean;D. Simonetti;G. Grassi;K. Kitayama;M. Nakayama
本研究调查了如何将两个现有的泛热带地上生物量（AGB）地图（Saatchi 2011，Baccini 2012）结合起来，以得出森林生态系统特定的碳估计值。几个数据融合模型，联合收割机结合这些AGB地图，根据其本地相关性与独立的数据集，如光谱波段的SPOT VEGETATION图像进行了分析。事实上，这些光谱带传达了关于植被类型和结构的信息，这些信息可能与生物量值有关。我们的研究区域是婆罗洲岛。的数据融合模型进行评估，对参考AGB地图可用于两个森林特许权在沙巴。最高的准确度是通过一个模型，它结合了AGB地图，根据平均值的本地相关系数计算在不同的内核大小。结合由此产生的AGB地图与新的婆罗洲土地覆盖地图（其总体准确度估计为86.5%）导致平均AGB估计为279.8吨/公顷的森林和退化的森林分别为233.1吨/公顷。低地龙脑香林和红树林的AGB值最高和最低，分别为305.8 t/ha和136.5 t/ha。所有天然林的AGB达10.8 Gt，主要来自低地龙脑香林（66.4%）、上部龙脑香林（10.9%）和泥炭沼泽林（10.2%）。退化的森林占AGB的另外2.1 Gt。我们的方法的一个主要优点是，一旦选择了最佳拟合数据融合模型，就不需要进一步的AGB参考数据集来实现数据融合过程。此外，AGB数据集的地方协调导致空间上更精确的地图。这种方法可以很容易地扩展到东南亚其他地区占主导地位的低地龙脑香林，并可以重复更新或更准确的AGB地图成为可用。
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.