Geospatial analysis, nighttime light remote sensing, vulnerability to environmental disasters.

I am interested in using Geographic Information System (RS), Remote Sensing (RS), and spatial analysis techniques (such as spatial statistics) to study issues in urban and environmental planning. My dissertation will be focusing on measuring disaster impact and recovery using longitudinal data, and understand whether the differences between places can be explained by socioeconomic, policy, or other indicators.

LDARCH C188/GEOG C188 Geographic Information Systems

LD ARCH C177/ESPM C177 GIS and Environmental Spatial Data Analysis

LD ARCH 221 Quantitative Methods in Environmental Planning

Ju, Y., Dronova, I., Ma, Q., & Zhang, X. (2017). Analysis of urbanization dynamics in mainland China using pixel-based nighttime light trajectories from 1992 to 2013. International Journal of Remote Sensing (in press). https://doi.org/10.1080/01431161.2017.1302114

Ju, Y., Hsu, W.-C., Radke, J. D., Fourt, W., Lang, W., Hoes, O., … Neuhausler, R. (2017). Planning for the change: mapping sea level rise and storm inundation in Sherman Island using 3Di hydrodynamic model and LiDAR. In Seeing Cities Through Big Data (pp. 313–329). Springer. https://link.springer.com/chapter/10.1007/978-3-319-40902-3_18

Ju, Y., & Radke, J. (2015). Mapping sea level rise and storm inundation by 3di hydrodynamic model in the San Francisco Bay Area and its implications for future planning and design. In Landscape Research Record No.4 (pp. 211–222). Retrieved from http://thecela.org/wp-content/uploads/LRR4_Revised-12017.pdf