Joint Global Change Research Institute, Pacific Northwest National Laboratory, 5825 University Research Ct., Suite 3500, College Park, MD, 20740, USA.
Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, P.O. Box 999, Richland, WA, 99352, USA.
Sci Data. 2020 Oct 2;7(1):320. doi: 10.1038/s41597-020-00669-x.
Global future land use (LU) is an important input for Earth system models for projecting Earth system dynamics and is critical for many modeling studies on future global change. Here we generated a new global gridded LU dataset using the Global Change Analysis Model (GCAM) and a land use spatial downscaling model, named Demeter, under the five Shared Socioeconomic Pathways (SSPs) and four Representative Concentration Pathways (RCPs) scenarios. Compared to existing similar datasets, the presented dataset has a higher spatial resolution (0.05° × 0.05°) and spreads under a more comprehensive set of SSP-RCP scenarios (in total 15 scenarios), and considers uncertainties from the forcing climates. We compared our dataset with the Land Use Harmonization version 2 (LUH2) dataset and found our results are in general spatially consistent with LUH2. The presented dataset will be useful for global Earth system modeling studies, especially for the analysis of the impacts of land use and land cover change and socioeconomics, as well as the characterizing the uncertainties associated with these impacts.
全球未来土地利用（LU）是预测地球系统动态的地球系统模型的重要输入，对于许多关于未来全球变化的建模研究至关重要。在这里，我们使用全球变化分析模型（GCAM）和名为 Demeter 的土地利用空间降尺度模型，根据五个共享社会经济路径（SSP）和四个代表性浓度路径（RCP）情景生成了一个新的全球网格化 LU 数据集。与现有类似数据集相比，该数据集具有更高的空间分辨率（0.05°×0.05°），涵盖了更全面的 SSP-RCP 情景集（总共 15 个情景），并考虑了来自强制气候的不确定性。我们将我们的数据集与土地利用协调版本 2（LUH2）数据集进行了比较，发现我们的结果在空间上通常与 LUH2 一致。该数据集将有助于全球地球系统建模研究，特别是用于分析土地利用和土地覆盖变化以及社会经济的影响，以及表征与这些影响相关的不确定性。
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