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首页> 外文期刊>Climatic Change >Relating radar remote sensing of biomass to modelling of forest carbon budgets.
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Relating radar remote sensing of biomass to modelling of forest carbon budgets.

机译：将生物量的雷达遥感与森林碳预算建模相关联。

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This paper addresses the use of radar remote sensing to map forest above-ground biomass, and discusses the use of biomass maps to test a dynamic vegetation model that identifies carbon sources and sinks and predicts their variation over time. For current radar satellite data, only the biomass of young/sparse forests or regrowth after disturbances can be recovered. An example from central Siberia illustrates that biomass can be measured by radar at a continental scale, and that a significant proportion of the Siberian forests have biomass values less than 50 tonnes/ha. Comparison between the radar map and calculations by the Sheffield Dynamic Global Vegetation Model (SDGVM) indicates that the model considerably overestimates biomass; under-representation of managed areas, disturbed areas and areas of low site quality in the model are suggested reasons for this effect. A case study carried out at the Budingen plantation forest in Germany supports the argument that inadequate representations of site quality and forest management may cause model overestimates of biomass. Comparison of the calculated biomass of stands planted after 1990 with biomass estimates by radar allows identification of forest stands where the growth conditions assumed by the model are not valid. This allows a quality check on model calculations of carbon fluxes: only calculations for stands where there is good agreement between the data and the model predictions should be accepted. Although the paper only uses the SDGVM model, similar effects are likely in other dynamic vegetation models, and the results show that model calculations attempting to quantify the role of forests as carbon sources or sinks could be qualified and potentially improved by exploiting remotely sensed measurements of biomass.
机译：本文介绍了使用雷达遥感绘制森林地上生物量的地图，并讨论了使用生物量地图测试动态植被模型的过程，该模型可以识别碳源和汇，并预测其随时间的变化。对于当前的雷达卫星数据，只能恢复干扰后的年轻/稀疏森林或再生长的生物量。西伯利亚中部地区的一个例子说明，可以通过雷达在大陆范围内测量生物量，并且很大一部分西伯利亚森林的生物量值均低于50吨/公顷。雷达图和谢菲尔德动态全球植被模型（SDGVM）的计算结果之间的比较表明，该模型大大高估了生物量。建议在模型中管理区域，受干扰区域和站点质量较低的区域的代表性不足。在德国Budingen人工林进行的案例研究支持以下论点：场地质量和森林管理的代表性不足可能会导致模型中生物量的高估。将1990年后种植的林分的生物量与雷达估算的生物量进行比较，可以识别模型所假设的生长条件无效的林分。这样可以对碳通量的模型计算进行质量检查：仅接受数据与模型预测之间具有良好一致性的展台计算。尽管本文仅使用SDGVM模型，但在其他动态植被模型中也可能产生类似的影响，结果表明，试图量化森林作为碳源或汇的作用的模型计算可以通过利用遥感测量的碳当量来限定和改进。生物质。

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