Qiming Zheng

Academic Qualifications

Ph.D. in Remote Sensing and Geographic Information System, Zhejiang University (2020)

B.S. in Environmental and Resource Sciences, Zhejiang University (2015)

Research Areas

Land cover and land use change; urbanization and its environmental consequences; vegetation phenology and climate change; remote sensing image processing and applications; time series analysis

Research Interests

Dr. Zheng’s research interest lies in using remote sensing, GIS and other geospatial techniques, environment and climate models, and AI/machine learning approaches to understand global environment changes, particularly in urban and peri-urban areas, and their environmental consequences. His research focus has always been on pushing the envelope on technical bottlenecks and bridging the gap between technical innovation and cutting edge environmental issues so that the interaction between human activities and global environment can be effectively measured, modeled, and evaluated.


Dr. Zheng is a postdoctoral research fellow with a research focus on global environment change. In 2020, Dr. Zheng joined the Centre for Nature-based Climate Solutions, directed by Prof. Koh Lian Pin, at the National University of Singapore.

He completed his five-year Ph.D. program at Zhejiang University, China, in 2020. During 2018-2019, he was also a visiting doctoral student funded by China Scholarship Council (CSC) at Indiana State University, USA. He has received a number of grants and awards for his scientific contribution, including Outstanding Doctoral Candidate Program of Zhejiang University (PI), Microsoft AI for Earth (Co-PI), National Ph.D. Student Scholarship of China, Excellent Doctoral Graduate of Zhejiang Province, etc.

Selected Publications

  1. Zheng Q, Teo HC, Koh LP. Artificial Light at Night Advances Spring Phenology in the United States. Remote Sensing. 2021; 13(3):399. https://doi.org/10.3390/rs13030399 
  2. Zheng Q, Weng Q, Wang K. Characterizing urban changes of 30 global mega-cities using dense nighttime light time series stacks. ISPRS Journal of Photogrammetry and Remote Sensing. 2021; 173:10-23. doi: 10.1016/j.isprsjprs.2021.01.002.
  3. Zheng Q, Weng Q, Wang K. Correcting the Pixel Blooming Effect (PiBE) of DMSP-OLS nighttime light imagery. Remote Sensing of Environment. 2020; 240. doi: 10.1016/j.rse.2020.111707.
  4. Zheng Q, Weng Q, Wang K. Developing a new cross-sensor calibration model for DMSP-OLS and Suomi-NPP VIIRS night-light imageries. ISPRS Journal of Photogrammetry and Remote Sensing 2019; 153:36-47. doi: 10.1016/j.isprsjprs.2019.04.019.
  5. Zheng Q, Weng Q, Huang L, Wang K, Deng J, Jiang R, et al. A new source of multi-spectral high spatial resolution night-time light imagery—JL1-3B. Remote Sensing of Environment. 2018; 215:300-12. doi: 10.1016/j.rse.2018.06.016.
  6. Zheng Q, Jiang R, Wang K, Huang L, Ye Z, Gan M, et al. Monitoring the trajectory of urban nighttime light hotspots using a Gaussian volume model. International Journal of Applied Earth Observation and Geo-information. 2017; 65: 24-34. doi: 10.1016/j.jag.2017.09.015.
  7. Xue X, Yi Lin, Zheng Q, et al. Mapping the fine-scale spatial pattern of artificial light pollution at night in urban environments from the perspective of bird habitats. Science of the Total Environment. 2020; 702. doi: 10.1016/j.scitotenv.2019.134725.
  8. Fu, Y, Li, J, Weng, Q, Zheng, Q, Li, L, Dai, S, & Guo, B. Characterizing the spatial pattern of annual urban growth by using time series Landsat imagery. Science of the Total Environment. 2019; 666: 274-284. doi: 10.1016/j.scitotenv.2019.02.178.

Conference and presentations

  1. Zheng Q. Earth Observation at Night: Nighttime Light Images Open Up New Applications. September 2019. Indiana State University, USA. (Invited talk)
  2. Zheng Q, Weng Q. Developing a new cross-sensor calibration model for DMSP-OLS and Suomi-NPP VIIRS night-light imageries. AAG 2019-Annual Meeting of American Association of Geographers, April 2019, Washington D.C., USA.
  3. Zheng Q, Wang K. Analysis of the spatio-temporal dynamic of polycentric city using night-time light remote sensing imagery. IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, July 2018, Valencia, Spain.
  4. Zheng Q, Wang K. Monitoring “ghost cities” in China from the view of night-time light remote sensing data. Workshop of “Sustainable Systems and Societies: energy, environment and policy frameworks”, November 2016, Campinas, Brazil.