Dingfan Xing

Dingfan Xing is a Postdoctoral Research Associate in the Department of Geography & Sustainability at the University of Tennessee, Knoxville. Her research focuses on the application and development of statistical methods for area estimation of forest characteristics and land cover, with an emphasis on uncertainty evaluation.

Education

• Ph.D. in Environmental Science, State University of New York College of Environmental Science and Forestry, 2023

Research Interests: Dr. Xing's research is directed towards two main topics: (1) Small area estimation of forest characteristics using model-assisted estimators to improve precision; and (2) Uncertainty evaluation of sample-based area estimates, particularly for land cover and land cover change. She develops advanced methods for estimating confidence intervals and total variance, and incorporates spatial heterogeneity and interpreter variability into estimation frameworks. Her work has applications in sustainable forest management, carbon accounting, and environmental monitoring.

Publication Trends: Dr. Xing's publications from 2019 to 2024 reveal a strong methodological focus in environmental statistics. Her recent work (2023-2024) centers on improving forest inventory estimation through multi-metric approaches, incorporating spatial heterogeneity, and addressing under-sampled mangrove forests. She has also made significant contributions to land cover monitoring by developing methods to account for interpreter variability and to estimate confidence intervals under complex sampling designs. Her research bridges statistics, forestry, and remote sensing, and increasingly addresses climate-relevant topics such as carbon estimation.

Advising and Grants: No information is available regarding students advised or research grants.

Labs and Teams: Dr. Xing is affiliated with the GIST (Geographic Information Science and Technology) research group within the Department of Geography & Sustainability.