School of Geography and Ocean Science, Nanjing University, Nanjing, 210023, China.
State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, CAS, Beijing, 100101, China.
Sci Rep. 2020 Aug 7;10(1):13316. doi: 10.1038/s41598-020-70088-w.
Understanding the spatial and temporal patterns of human pressures provides a foundation for understanding interactions between human and environment and managing human activities for a sustainable development. This study is the first attempt focused within China at calculating the spatial-temporal human footprint and its driving forces in a highly urbanized area with intensive human activities. Population, land use, night-time lights, and road impacts were used to generate human footprint maps of Jiangsu Province for 2000, 2010 and 2015 with a resolution of 1 km * 1 km. Five natural drivers and four anthropogenic drivers were employed to construct generalized additive models for explaining the spatial variation of human footprint and its change. It shows that a large difference is between the human footprint in northern and southern Jiangsu, and the pattern of human pressures conforms to the "Matthew effect", with spatial aggregation of high human footprint areas accelerating. Slope, industrialization level are significant in explaining the spatial variation of human footprint in 2000, 2010 and 2015. The effect of natural drivers decreases for explaining the human footprint over time. Furthermore, annual precipitation, mean annual temperature and urban per capita disposable income are also significant drivers for human footprint in 2010 and 2015. And the increasing of human footprint slows with increasing of industrialization level. The difference of industrialization level and urban income between northern and southern Jiangsu mainly caused different driving pattern for human footprint and its change. Our study has generated new insights on the interaction pattern between human and nature in highly developed regions based on the human footprint concept, and can provide references for managing human activities in similar regions rapid socioeconomic development.
了解人类压力的时空格局为理解人类与环境的相互作用以及为可持续发展管理人类活动提供了基础。本研究首次尝试在中国高度城市化和人类活动密集的地区计算时空人类足迹及其驱动力。本研究使用人口、土地利用、夜间灯光和道路影响数据，生成了江苏省 2000 年、2010 年和 2015 年分辨率为 1km×1km 的人类足迹图。采用五个自然驱动因素和四个人为驱动因素构建广义加性模型，解释人类足迹的空间变化及其变化的原因。结果表明，江苏南北部的人类足迹存在较大差异，人类压力格局符合“马太效应”，高人类足迹地区的空间聚集速度加快。坡度、工业化水平在解释 2000 年、2010 年和 2015 年人类足迹的空间变化方面具有显著意义。随着时间的推移，自然驱动因素对解释人类足迹的影响减小。此外，年降水量、年平均温度和城镇人均可支配收入也是 2010 年和 2015 年人类足迹的重要驱动因素。随着工业化水平的提高，人类足迹的增长速度逐渐放缓。江苏南北部工业化水平和城镇人均收入的差异主要导致了人类足迹及其变化的不同驱动模式。本研究基于人类足迹概念，为高度发达地区人类与自然的相互作用模式提供了新的见解，可为类似地区快速社会经济发展的人类活动管理提供参考。
