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Monitoring deforestation trend and future outlooks of the aboveground forest carbon stocks in Central Sumatra using ALOS-PALSAR mosaic data

机译：使用ALOS-PALSAR镶嵌数据监测苏门答腊中部中部森林砍伐趋势和未来森林前景

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摘要

In this research, we present methods for monitoring deforestation and examining implication of the forest policies in forest carbon stocks in the future utilizing ALOS-PALSAR data. Riau Province of central Sumatra is selected for the study as it has received worldwide attention due to high forest-related carbon emissions. An aboveground forest carbon stocks (AFCS) model was calibrated with field measurement data and L-band backscatters from high-resolution slope corrected PALSAR mosaic data of 2009 and 2010. A total of 87 plots of field measured AFCS data ranging 1 - 340 t/ha was used. This AFCS model provides the AFCS map with RMSE of ±45 t/ha. The AFCS modeling results was extrapolated across the province using the mosaic data. The model estimated 315 million tons of AFCS in the province in 2010. A spatial model was used to spatialize three forest policy scenarios. These scenario maps were overlaid with AFCS map for deriving future perspective on AFCS. The future spatial patterns of the AFCS between the policy scenarios are apparent. If the historical trend continues, the forest cover will be consistently disappeared leaving very few small forest patches and releasing 77% of the current AFCS in to the atmosphere by 2030. However, one of the governance scenarios in the province indicates that almost half of the carbon emission can be reduced in the same period.
机译：在这项研究中，我们提出了利用ALOS-PALSAR数据监测森林砍伐和检查未来森林政策对森林碳储量的影响的方法。苏门答腊中部的廖内省被选为研究对象，因为与森林相关的高碳排放量已引起全世界的关注。利用现场测量数据和2009年和2010年高分辨率斜率校正的PALSAR镶嵌数据的L波段反向散射对地面森林碳储量（AFCS）模型进行了校准。总共87个现场实测AFCS数据范围为1-340 t /哈用。该AFCS模型为AFCS图提供了±45 t / ha的RMSE。 AFCS建模结果使用镶嵌数据外推到全省。该模型在2010年估计了该省3.15亿吨的AFCS。使用空间模型对三种森林政策方案进行空间化。这些场景图与AFCS图叠加在一起，以得出关于AFCS的未来观点。政策情景之间AFCS的未来空间格局是显而易见的。如果历史趋势继续下去，到2030年，森林覆盖率将持续消失，留下很少的小片森林，并释放77％的当前AFCS到大气中。但是，该省的一种治理方案表明，几乎一半的森林同期可以减少碳排放量。

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