Skip Ribbon Commands Skip to main content


Profile Image

Guofan Shao

Forestry and Natural Resources 

  • Professor of Forestry
PFEN Room 221B
715 W State St.
West Lafayette, IN 47907

Dr. Guofan Shao is a professor of the Department of Forestry and Natural Resources (FNR) at Purdue University. Dr. Shao received his PhD in ecology from Chinese Academy of Sciences in 1989, received his post-doctorial education from the Department of Environmental Sciences, University of Virginia between 1991 and 1994, and received professional trainings in remote sensing and GIS technologies from world-geospatial leaders, such as ESRI and ERDAS, in the 1980-1990s. Dr. Shao is the Director of Forest Informatics and Landscape Monitoring (FILM) Laboratory at the Department of Forestry and Natural Resources, Purdue University, and also serves at the Laboratory for Application of Remote Sensing (LARS) at Purdue University. Dr. Shao teaches Digital Remote Sensing and GIS (FNR 558), Fundamental Remote Sensing (FNR 357), and Forest Resources Practicum (FNR 330). Dr. Shao is adjunct research professor at two institutes of Chinese Academy of Sciences, and is honorary dean of Jilin Changbai Mountain Academy of Sciences.

Dr. Shao’s overall research interest is digital forestry technologies (DFT), including remote sensing, geographic information systems (GIS), forest modeling, and forestry decision-support systems (DSS). Shao applies DFT in better understanding forest landscape changes and sustaining the management of forest resources. Dr. Shao is especially interested in developing algorithms for accurate land use and land cover mapping with remote sensing, developing web-based GIS protocols for land use analysis and forest conservation, developing applicable forest simulation models for forestry professionals, and developing user-friendly forestry DSS for assisting forestry decision making. Dr. Shao is conducting research projects for the temperate forest ecosystems in the Midwest of the United States and northeastern China. Dr. Shao has published over a hundred scholarly works. His book, “Forest Dynamics Modeling”, is one of few forestry books that have received national-level awards in China. His journal publications, such as that published in Science, have been widely cited. His new book, titled Computer Applications in Sustainable Forest Management, represents his interdisciplinary strength and collaborative achievement.

Research Group - Forest Measurement and Assessment/GIS

Facilities - John S. Wright Center, Forest Informatics and Landscape Monitoring Lab (FILM)

Areas of Excellence - Partnering for Land Use Sustainability, Sustaining Hardwood Ecosystems

Related Centers - Center for the Environment, Purdue Climate Change Research Center, Purdue Interdisciplinary Center for Ecological Sustainability, Laboratory for Applications of Remote Sensing, Purdue Terrestrial Observation

Awards & Honors

(2014) International forestry research. Rocky Branch Farm.

(2013) Upgrading Consumer-Grade GPS Receivers for Undergraduate and Graduate Education. Purdue University.

(2010) Habitat Conservation Plan Development and Implementation for the Indiana Bat. Indiana Department of Natural Resources.

Selected Publications

Dai, L. M., Qi, L., Lewis, B. J., Shao, G., Yu, D. P., & Zhou, L. (2014). The design and use of forest management decision support systems in China. In Computer-based Tools for Supporting Forest Management: The Experience and Expertise World-wide (Vol. 1, pp. 84-94). Austria: Sveriges lantbruksuniversitet.

Liao, J. H., Tang, L. N., Shao, G., Qiu, Q. Y., & Wang, C. P. (2014). Neighbor decay cellular automata approach for simulating urban expansion based on particle swarm intelligence. International Journal of Geographical Information Science, 28(5), 720-738.

Zhao, J. Z., Xiao, L. S., Tang, L. N., Shi, L. Y., Su, X. D., Wang, H. W., . . . Shao, G. (2014). . Effects of spatial form on urban commute for major cities in China. International Journal of Sustainable Development & World Ecology, 21(4), 361-368.

Shao, G., Bauli, B. P., Haulton, G. S., Zollner, P. A., & Shao, G. (2014). Mapping hardwood forests through a two-stage unsupervised classification by integrating Landsat Thematic Mapper and forest inventory data. Journal of Applied Remote Sensing, 8(1).

Lin, T. F., & Shao, G. (2014). A Remote-Sensing Assessment of Drought Effects on Vegetation in West Lafayette, IN, the United States. LAB Symposium on BiodiverCities without Boundaries: Science, Policy, and Local Governance.

Ren, Y., Deng, L. Y., Zuo, S. D., Luo, Y. J., Shao, G., Wei, X. H., . . . Yang, Y. S. (2014). Geographical modeling of spatial interaction between human activity and forest connectivity in an urban landscape of southeast China. Landscape Ecology, 29(10), 1741-1758.

Wang, Y. Y., Bai, G. X., Shao, G., & Cao, Y. K. (2014). An analysis of potential investment returns and their determinants of poplar plantations in state-owned forest enterprises of China. New Forests, 45(2), 251-264.

Li, X. X., & Shao, G. (2014). A county-scale object-based land-cover mapping in U.S. Midwest region with high resolution aerial photography. Remote Sensing, 6(11), 11372-11390.

Shao, G. (2013). Seeking a Technical and Political Convergence to Diminish the Barriers of Cross-Border Conservation on Changbai Mountain. East Asian and European Regional Environmental Governance (EE-REG).

Li, X., & Shao, G. (2013). Object–based urban vegetation mapping with high resolution aerial photography as a single data source. International Journal of Remote Sensing, 34(3), 771–789.