Qiang Pu

Qiang Pu.

Education:

BS: Geomatics Engineering, 2014, Central South University, China

MS: Cartography and Geographical Information Engineering, 2017, Central South University, China;

Research Interests:

My research interests mainly lie within GIScience and Environmental modeling using GIS, RS, machine learning, and geostatistic methods. I am currently working on spatial-temporal modeling of PM2.5 concentrations using satellite-derived aerosol optical depth.

Recent Courses Taught: 

GEO 483: Remote Sensing (Lab Section)

GEO 481: Introduction to Geographical Information System (Lab Section)

GEO 479: GIS for Environmental Modeling (Lab Section)

Publications:

Pu, Q., & Yoo, E. H. (2021). Ground PM2.5 prediction using imputed MAIAC AOD with uncertainty quantification. Environmental Pollution, 116574.

Pu, Q., Yoo, E. H., Rothstein, D. H., Cairo, S., & Malemo, L. (2020). Improving the spatial accessibility of healthcare in North Kivu, Democratic Republic of Congo. Applied Geography, 121, 102262.

Pu, Q., & Yoo, E. H. (2020). Spatio-temporal modeling of PM2. 5 concentrations with missing data problem: a case study in Beijing, China. International Journal of Geographical Information Science, 34(3), 423-447.

Cairo, S. B., Pu, Q., Kalisya, L. M., Bake, J. F., Zaidi, R., Poenaru, D., & Rothstein, D. H. (2020). Geospatial Mapping of Pediatric Surgical Capacity in North Kivu, Democratic Republic of Congo. World Journal of Surgery, 44(11), 3620-3628.  

Zou, B., Pu, Q., Bilal, M., Weng, Q., Zhai, L., & Nichol, J. E. (2016). High-resolution satellite mapping of fine particulates based on geographically weighted regression. IEEE Geoscience and Remote Sensing Letters, 13(4), 495-499.