**6. Conclusions**

Based on remote sensing data, we explored the spatiotemporal distribution patterns and variation characteristics of albedo in the Jing-Jin-Ji region. In addition, a quantitative approach based on partial derivatives was applied to calculate the contribution of urbanization and vegetation to albedo variability.

The results showed that albedo changed greatly before and after 2005. Albedo variation was mainly contributed by vegetation (44%) and other factors (41%) before 2005. However, after 2005, large-scale urbanization became the main controlling factor that affected the change in albedo, with a contribution proportion of 48.5%, and the vegetation and other factors contributions were 24% and 27.5%, respectively. Spatially, the contribution percentage of urbanization gradually increased from the Core Area to the Fringe Area, and the contribution percentage of vegetation gradually decreased. Temporally, the contribution of urbanization in the Core Area and Expanded Area decreased with time, and the contribution of vegetation increased. In contrast, the impact of urbanization in the Fringe Area increased, while that of vegetation decreased. Other factors (e.g., extreme weather, natural disasters et al.) contributed more to albedo variation in Core Areas than other areas, and exhibited an increasing trend over time.

In summary, our paper provides a method via mathematical statistics to quantitatively estimate the contribution of urbanization and vegetation to albedo changes in urban areas. Understanding the spatiotemporal differences in albedo via dominant factors will help us perform additional research on urban climate change, especially regarding temperature changes in urban areas. At the same time, it can also provide a data foundation for developing urban energy conservation policies.

**Author Contributions:** R.T. and X.Z. conceived of and designed the experiments. R.T. processed and analyzed the data. All authors contributed to the ideas, writing, and discussion.

**Funding:** This study was supported by the National Key Research and Development Program of China (No. 2016YFA0600103) and the State Key Laboratory of Remote Sensing Science (No. 16ZY-06).

**Acknowledgments:** The authors thank Jia Cheng, Yifeng Peng, Haoyu Wang, and Xiaozheng Du for helpful comments that improved this manuscript.

**Conflicts of Interest:** The authors declare no conflict of interest.
