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Local discrepancies in continental scale biomass maps: a case study over forested and non-forested landscapes in Maryland, USA

机译:大陆尺度生物量地图中的局部差异:以美国马里兰州森林和非森林景观为例

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Background Continental-scale aboveground biomass maps are increasingly available, but their estimates vary widely, particularly at high resolution. A comprehensive understanding of map discrepancies is required to improve their effectiveness in carbon accounting and local decision-making. To this end, we compare four continental-scale maps with a recent high-resolution lidar-derived biomass map over Maryland, USA. We conduct detailed comparisons at pixel-, county-, and state-level. Results Spatial patterns of biomass are broadly consistent in all maps, but there are large differences at fine scales (RMSD 48.5–92.7 Mg ha ?1 ). Discrepancies reduce with aggregation and the agreement among products improves at the county level. However, continental scale maps exhibit residual negative biases in mean (33.0–54.6 Mg ha ?1 ) and total biomass (3.5–5.8 Tg) when compared to the high-resolution lidar biomass map. Three of the four continental scale maps reach near-perfect agreement at ~4 km and onward but do not converge with the high-resolution biomass map even at county scale. At the State level, these maps underestimate biomass by 30–80 Tg in forested and 40–50 Tg in non-forested areas. Conclusions Local discrepancies in continental scale biomass maps are caused by factors including data inputs, modeling approaches, foreston-forest definitions and time lags. There is a net underestimation over high biomass forests and non-forested areas that could impact carbon accounting at all levels. Local, high-resolution lidar-derived biomass maps provide a valuable bottom-up reference to improve the analysis and interpretation of large-scale maps produced in carbon monitoring systems.
机译:背景大陆规模的地上生物量地图越来越多,但它们的估计值相差很大,尤其是在高分辨率下。需要全面了解地图差异,以提高其在碳核算和地方决策中的有效性。为此,我们将四个大陆比例尺的地图与最近在美国马里兰州进行的高分辨率激光雷达衍生生物量图的比较。我们在像素级,县级和州级进行了详细的比较。结果在所有地图上,生物量的空间格局大致一致,但在小尺度上有很大差异(RMSD 48.5–92.7 Mg ha?1)。差异随着聚集而减少,产品之间的一致性在县一级得到改善。但是,与高分辨率激光雷达生物量图相比,大陆规模图在平均值(33.0-54.6 Mg ha?1)和总生物量(3.5-5.8 Tg)中显示出残留的负偏差。四个大陆比例尺地图中的三个在〜4 km及以后达到了近乎完美的一致性,但即使在县级尺度上也无法与高分辨率生物质图收敛。在州一级,这些地图低估了森林中的生物量30–80 Tg,非森林中的生物量低40–50 Tg。结论大陆生物量图中的局部差异是由以下因素引起的,这些因素包括数据输入,建模方法,森林/非森林定义和时滞。高生物量森林和非森林地区的净低估可能会影响各个层面的碳核算。本地,高分辨率的激光雷达衍生生物量图提供了宝贵的自下而上的参考,可改善对碳监测系统中生成的大规模图的分析和解释。

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