Chunyuan Diao has been an assistant professor of Geography and Geographic Information Science at the university of Illinois Urbana-Champaign since 2017. She teaches courses including Introduction to Remote Sensing, Techniques of Remote Sensing, and Programming for GIS.

Her research focuses on computational remote sensing of terrestrial ecosystem dynamics at local to global spatial scales and daily to decadal temporal scales. She has a particular interest in advancing computational remote sensing paradigms in characterizing land surface patterns and processes, underlying mechanisms, and subsequent feedbacks to the atmosphere. Her work combines remote sensing, process-based models, field observations, artificial intelligence, and high-performance and cloud computing to study ecosystem structures, functions, and responses to climate change and human activities. This research traverses varying ecosystems, including natural (e.g., forest), human-dominated (e.g., agriculture), and disturbed (e.g., species invasion) ecosystems. Current focus areas include computational remote sensing, multi-scale land surface phenology, intelligent agriculture, and invasive species and biodiversity.

Her research team has developed a novel framework, called CropSight, to retrieve the object-based crop type ground truth. CropSight is a unique national-scale crop ground reference data repository and embodies a wealth of season-long remotely sensed crop growth and environmental attributes across crop growing locations for most crop types in the U.S.

She is a fellow of the Association of American Geographers and previously received the Early/Mid-Career Research Award from the University Consortium for Geographic Information Science (2023), a National Science Foundation CAREER Award (2021), the NASA Early Career Investigator Award (2021), and AAG Early Career Scholars in Remote Sensing Award (2020).

Research interests

  • Time series remote sensing, space-time analytics
  • Vegetation phenology, continuous vegetation monitoring
  • Computational remote sensing, deep learning
  • Agriculture, forest, and invasive species dynamics

Education

  • PhD, Geography, State University of New York at Buffalo
  • MA, Biostatistics, State University of New York at Buffalo
  • BS, Beijing Normal University

Website

https://diaorssilab.web.illinois.edu/

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