特码

一作通讯论文

1. Shang, H., Ju, Y.*, Zhang, X., Xu, J., Li, X., & Delclòs-Alió, X. (2025). OSM land use data quality and its association with city-level socioeconomic conditions in China. Environment and Planning B, 23998083251341667. //doi.org/10.1177/23998083251341667

2. Ju, Y., Liang, Y., Kong, J., Wang, X., Wen, S., Shang, H., & Wang, X.* (2025). 100-m resolution Age-Stratified Population Estimation from the 2020 China Census by Township (ASPECT). Scientific Data, 12(1), 1058. //doi.org/10.1038/s41597-025-05401-1

3. Ju, Y.*, Dronova, I., Ma, Q., Lin, J., Moran, M. R., Gouveia, N., Hu, H., Yin, H., & Shang, H. (2024). Assessing Normalized Difference Vegetation Index as a proxy of urban greenspace exposure. Urban Forestry & Urban Greening, 99, 128454. //doi.org/10.1016/j.ufug.2024.128454

4. Ju, Y.*, Dronova, I., Rodriguez, D. A., Bakhtsiyarava, M., & Farah, I. (2023). Recent greening may curb urban warming in Latin American cities of better economic conditions. Landscape and Urban Planning, 240, 104896. //doi.org/10.1016/j.landurbplan.2023.104896

5. Ju, Y.*, Dronova, I., & Delclòs-Alió, X. (2022). A 10 m resolution urban green space map for major Latin American cities from Sentinel-2 remote sensing images and OpenStreetMap. Scientific Data, 9, Article 1. //doi.org/10.1038/s41597-022-01701-y

6. Lindbergh, S., Ju, Y.*, He, Y., Radke, J., & Rakas, J. (2022). Cross-sectoral and multiscalar exposure assessment to advance climate adaptation policy: The case of future coastal flooding of California’s airports. Climate Risk Management, 38, 100462. //doi.org/10.1016/j.crm.2022.100462

7. Ju, Y., Moran, M., Wang, X., Avila-Palencia, I., Cortinez-O’Ryan, A., Moore, K., Slovic, A. D., Sarmiento, O. L., Gouveia, N., Caiaffa, W. T., et al. (2021). Latin American cities with higher socioeconomic status are greening from a lower baseline: Evidence from the SALURBAL project. Environmental Research Letters. //doi.org/10.1088/1748-9326/ac2a63

8. Cunha, M. da C. M., Ju, Y.*, et al. (2021). Disentangling associations between vegetation greenness and dengue in a Latin American city: Findings and challenges. Landscape and Urban Planning, 216, 104255. //doi.org/10.1016/j.landurbplan.2021.104255

9. Ju, Y., Cushing, L. J., & Morello-Frosch, R.* (2020). An equity analysis of clean vehicle rebate programs in California. Climatic Change, 162(4), 2087–2105. //doi.org/10.1007/s10584-020-02836-w

10. Ju, Y.*, Lindbergh, S., He, Y., & Radke, J. D. (2019). Climate-related uncertainties in urban exposure to sea level rise and storm surge flooding. Cities, 92, 230–246. //doi.org/10.1016/j.cities.2019.04.002

11. Ju, Y., Dronova, I., Ma, Q., & Zhang, X. (2017). Analysis of urbanization dynamics in mainland China using pixel-based night-time light trajectories from 1992 to 2013. International Journal of Remote Sensing, 38(21), 6047–6072. //doi.org/10.1080/01431161.2017.1302114

12. 居阳, 张翔, 徐建刚 (2012). 基于话语权的历史街区更新公众参与研究——以福建长汀店头街为例. 现代城市研究, 27(9), 49–57.

13. 石飞, 居阳* (2015). 公交出行分担率影响因素分析——基于南京主城区的实证研究. 城市规划, 39(2), 76–84.

其他作者论文（部分）

1. Du, H., Zhan, W.*, Zhou, B., Ju, Y., et al. (2025). Exacerbated heat stress induced by urban browning in the Global South. Nature Cities, 1–13. //doi.org/10.1038/s44284-024-00184-9

2. Bakhtsiyarava, M.*, Moran, M., Ju, Y., et al. (2024). Potential drivers of urban green space availability in Latin American cities. Nature Cities, 1–11. //doi.org/10.1038/s44284-024-00162-1

3. Bakhtsiyarava, M.*, Ju, Y., et al. (2024). Associations between urban greenspace and depressive symptoms in Mexico’s cities using different greenspace metrics. Applied Geography, 164, 103219. //doi.org/10.1016/j.apgeog.2024.103219

4. Ramarao, M. V. S., Arunachalam, S.*, Ju, Y., et al. (2024). Projected changes in heatwaves over Central and South America using high-resolution regional climate simulations. Scientific Reports, 14(1), 1–11. //doi.org/10.1038/s41598-024-73521-6