College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China; Beijing Key Laboratory of Resources Environment and Geographic Information System, Beijing 100048, China.
College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China; Beijing Key Laboratory of Resources Environment and Geographic Information System, Beijing 100048, China.
Sci Total Environ. 2020 Sep 10;734:139457. doi: 10.1016/j.scitotenv.2020.139457. Epub 2020 May 16.
Mapping time-series anthropogenic heat flux (AHF) is of great significance for understanding the process of urbanization and its impact on urban environment and climate. By collecting energy consumption data and socioeconomic statistics, combined with multi-source remotely sensed data, this study mapped the surface AHF in China with a high spatial resolution of 500 m × 500 m from 2000 to 2016 with 4 years of interval through constructing AHF estimation scheme. The main conclusions are: (1) There is a strong correlation between the vegetation adjusted nighttime light urban index (VANUI) and AHF. The highest coefficient of determination (R) of VANUI and AHF is 0.97 in partition of northwest region (NWR). The average R value in partitions is 0.76, which shows that VANUI can well reflect the spatial differentiation characteristics of anthropogenic heat emissions. In addition, the fitting R value of the AHF estimation result and the AHF calculated by the inventory method is between 0.7 and 0.9, which indicates that the AHF estimation model constructed by VANUI can obtain reliable AHF estimation results. (2) In 2000-2016, the composition of AHF value changed a lot. The most obvious change is the AHF of 2-5 W·m, with a total increase of 21.53%. The area ratio of the low-value AHF of 0-2 W·m showed a decreasing trend, from 91.93% in 2000 to 50.45% in 2016. Due to the increase of AHF, the reduced area has evolved to a high anthropogenic heat emission area. By constructing the AHF estimation model, this study acquired the time-series AHF with good accuracy and time-variation consistency in China from 2000 to 2016, which can effectively serve the research on urban environment and climate.
绘制时间序列人为热通量（AHF）图对于理解城市化进程及其对城市环境和气候的影响具有重要意义。本研究通过收集能源消耗数据和社会经济统计数据，并结合多源遥感数据，构建了 AHF 估算方案，以 500 m×500 m 的高空间分辨率，对 2000 年至 2016 年期间中国的地表 AHF 进行了每 4 年一次的绘制。主要结论为：（1）植被调整夜间灯光城市指数（VANUI）与 AHF 之间具有很强的相关性。VANUI 与 AHF 的决定系数（R）最高值为 0.97，出现在西北地区（NWR）的分区中。分区内的平均 R 值为 0.76，表明 VANUI 能够很好地反映人为热排放的空间分异特征。此外，VANUI 构建的 AHF 估算结果与清单法计算的 AHF 之间的拟合 R 值在 0.7 到 0.9 之间，表明 VANUI 构建的 AHF 估算模型可以获得可靠的 AHF 估算结果。（2）2000-2016 年间，AHF 值的构成发生了很大变化。最明显的变化是 2-5 W·m 的 AHF，总增加量为 21.53%。0-2 W·m 的低值 AHF 的面积比例呈下降趋势，从 2000 年的 91.93%下降到 2016 年的 50.45%。由于 AHF 的增加，减少的面积已演变为高人为热排放区。通过构建 AHF 估算模型，本研究获得了 2000-2016 年中国具有良好精度和时变一致性的时间序列 AHF，这将有效地为城市环境和气候的研究服务。
