Sydney Institute of Agriculture & School of Life and Environmental Sciences, The University of Sydney, Camperdown, Australia.
CSIRO Agriculture and Food, Black Mountain, ACT, Australia.
Sci Data. 2023 Mar 31;10(1):181. doi: 10.1038/s41597-023-02056-8.
We introduce a new dataset of high-resolution gridded total soil organic carbon content data produced at 30 m × 30 m and 90 m × 90 m resolutions across Australia. For each product resolution, the dataset consists of six maps of soil organic carbon content along with an estimate of the uncertainty represented by the 90% prediction interval. Soil organic carbon maps were produced up to a depth of 200 cm, for six intervals: 0-5 cm, 5-15 cm, 15-30 cm, 30-60 cm, 60-100 cm and 100-200 cm. The maps were obtained through interpolation of 90,025 depth-harmonized organic carbon measurements using quantile regression forest and a large set of environmental covariates. Validation with 10-fold cross-validation showed that all six maps had relatively small errors and that prediction uncertainty was adequately estimated. The soil carbon maps provide a new baseline from which change in future carbon stocks can be monitored and the influence of climate change, land management, and greenhouse gas offset can be assessed.
我们引入了一个新的高分辨率网格化总土壤有机碳含量数据集,该数据集在澳大利亚以 30m×30m 和 90m×90m 的分辨率生成。对于每个产品分辨率,数据集由六张土壤有机碳含量图以及 90%预测区间表示的不确定性估计组成。土壤有机碳图的生成深度可达 200cm,分为六个区间:0-5cm、5-15cm、15-30cm、30-60cm、60-100cm 和 100-200cm。这些地图是通过对 90025 个深度协调的有机碳测量值进行分位数回归森林插值,并结合大量环境协变量获得的。10 折交叉验证的验证表明,所有六张地图的误差都相对较小,并且预测不确定性得到了充分估计。这些土壤碳图提供了一个新的基线,可以用来监测未来碳储量的变化,并评估气候变化、土地管理和温室气体抵消的影响。