Ehrlich D, Kemper T, Pesaresi M, Corbane C
Joint Research Centre, European Commission, Via Enrico Fermi, 2749, I-21027 Ispra, Italy.
Environ Sci Policy. 2018 Dec;90:73-82. doi: 10.1016/j.envsci.2018.10.001.
Scientists use Essential Climate Variables to understand and model the Earth's climate. Complementary to the Climate Variables this paper introduces global built-up area and population density, referred to as Essential Societal Variables, that can be used to model human activities and the impact of climate induced hazards on society. Climate impact scenarios inform policy makers on current and future risk and on the cost for mitigation and adaptation measures. The global built-up area and global population densities are generated from Earth observation image archives and from national population census data in the framework of the Global Human Settlement Layer (GHSL) project. The layers are produced with fine granularity for four epochs: 1975, 1990, 2000 and 2015, and will be updated on a regular basis with open satellite imagery. The paper discusses the relevance of global built-up area and population density for a number of policy areas, in particular to understand regional and global urbanization processes and for use in operational crisis management and risk assessment. The paper also provides examples of global statistics on exposure to natural hazards based on the two ESVs and their use in policy making. Finally, the paper discusses the potential of using population and built-up area for developing indicators to monitor the progress in Agenda 2030 including the Sustainable Development Goals (SDGs).
科学家们使用基本气候变量来理解地球气候并建立气候模型。作为气候变量的补充，本文引入了全球建成区面积和人口密度，即基本社会变量，它们可用于模拟人类活动以及气候诱发灾害对社会的影响。气候影响情景向政策制定者通报当前和未来的风险以及缓解和适应措施的成本。全球建成区面积和全球人口密度是在全球人类住区层（GHSL）项目框架内，根据地球观测图像档案和国家人口普查数据生成的。这些图层针对1975年、1990年、2000年和2015年这四个时期以精细粒度制作，并将通过开放卫星图像定期更新。本文讨论了全球建成区面积和人口密度在多个政策领域的相关性，特别是对于理解区域和全球城市化进程以及用于运营危机管理和风险评估。本文还提供了基于这两个基本社会变量的自然灾害暴露全球统计数据示例及其在政策制定中的应用。最后，本文讨论了利用人口和建成区面积制定指标以监测包括可持续发展目标（SDGs）在内的《2030年议程》进展情况的潜力。
