Panshi is a data scientist working on information extraction from satellite imagery. He has broad interests in remote sensing, image processing and machine learning techniques for land cover mapping and change detection. His research has led or contributed to the development of several large-scale land cover products, including the first 30-m global map of man-made impervious surface (GMIS), a 30-m global map of Human Built-up and Settlement Extent (HBASE) using Landsat satellite data and the first 30-m country-level building volume map based on open geospatial data.
Panshi holds a B.E. in Electronic Engineering from the University of Science and Technology of China, an M.E. in signal and information processing from the Chinese Academy of Sciences, and a Ph.D. in Geographical Sciences from the University of Maryland.
You can find more about Panshi’s past and ongoing research on this site.