Reduction of carbon emissions from peatlands is recognized as an important factor in global climate change mitigation. Within the SE Asia region, areas of deeper peat present the greatest carbon stocks, and therefore the greatest potential for future carbon emissions from degradation and fire. They also support most of the remaining lowland swamp forest and its associated biodiversity. Accurate maps of deep peat are central to providing correct estimates of peat carbon stocks and to facilitating appropriate management interventions. We present a rapid and cost-effective approach to peat thickness mapping in raised peat bogs that applies a model of peat bottom elevation based on field measurements subtracted from a surface elevation model created from airborne LiDAR data. In two raised peat bog test areas in Indonesia, we find that field peat thickness measurements correlate well with surface elevation derived from airborne LiDAR based DTMs (R2 0.83–0.88), confirming that the peat bottom is often relatively flat. On this basis, we created a map of extent and depth of deep peat (> 3 m) from a new DTM that covers two-thirds of Sumatran peatlands, applying a flat peat bottom of 0.61 m +MSL determined from the average of 2446 field measurements. A deep peat area coverage of 2.6 Mha or 60.1% of the total peat area in eastern Sumatra is mapped, suggesting that deep peat in this region is more common than shallow peat and its extent was underestimated in earlier maps. The associated deep peat carbon stock range is 9.0–11.5 Pg C in eastern Sumatra alone. We discuss how the deep peat map may be used to identify priority areas for peat and forest conservation and thereby help prevent major potential future carbon emissions and support the safeguarding of the remaining forest and biodiversity. We propose rapid application of this method to other coastal raised bog peatland areas in SE Asia in support of improved peatland zoning and management. We demonstrate that the upcoming global ICESat-2 and GEDI satellite LiDAR coverage will likely result in a global DTM that, within a few years, will be sufficiently accurate for this application.

中文翻译：

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利用基于LiDAR的DTM绘制深层泥炭碳库，并进行实地测量，并将其应用于苏门答腊东部。

减少泥炭地的碳排放被认为是缓解全球气候变化的重要因素。在东南亚地区，较深的泥炭地区碳储量最大，因此，未来因退化和火灾而产生的碳排放量最大。它们还支持大多数剩余的低地沼泽森林及其相关的生物多样性。准确的深泥炭地图对于提供正确的泥炭碳储量估算和促进适当的管理干预至关重要。我们提出了一种快速且经济高效的方法来处理升高的泥炭沼泽中的泥炭厚度，该方法基于从航空LiDAR数据创建的表面高程模型中减去的实地测量值，应用泥炭底部高程模型。在印度尼西亚的两个凸起的泥炭沼泽测试区，我们发现实地泥炭厚度测量值与基于机载LiDAR的DTM得出的表面高度高度相关（R2 0.83–0.88），证实了泥炭底部通常相对平坦。在此基础上，我们利用覆盖了苏门答腊三分之二泥炭地的新DTM绘制了深泥炭（> 3 m）的范围和深度图，应用了从2446油田的平均值确定的0.61 m + MSL平坦泥炭底部测量。在苏门答腊东部，泥炭深覆盖面积为2.6 Mha，占泥炭总面积的60.1％，这表明该地区的深泥炭比浅泥炭更为常见，其范围在早期的地图中被低估了。仅在苏门答腊东部，相关的深层泥炭碳储量范围为9.0-11.5 PgC。我们讨论了如何使用深泥炭地图来确定泥炭和森林保护的优先领域，从而帮助防止未来可能发生的主要碳排放，并支持维护剩余的森林和生物多样性。我们建议将此方法快速应用到东南亚其他沿海凸起的沼泽泥炭地地区，以支持改善泥炭地的分区和管理。我们证明，即将到来的全球ICESat-2和GEDI卫星LiDAR覆盖范围很可能会导致全球DTM，在几年之内，它将对该应用程序足够准确。我们建议将此方法快速应用到东南亚其他沿海凸起的沼泽泥炭地地区，以支持改善泥炭地的分区和管理。我们证明，即将到来的全球ICESat-2和GEDI卫星LiDAR覆盖范围很可能会导致全球DTM，在几年之内，它将对该应用足够准确。我们建议将此方法快速应用到东南亚其他沿海凸起的沼泽泥炭地地区，以支持改善泥炭地的分区和管理。我们证明，即将到来的全球ICESat-2和GEDI卫星LiDAR覆盖范围很可能会导致全球DTM，在几年之内，它将对该应用足够准确。