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Bryan C Pijanowski

Forestry and Natural Resources 

  • Professor of Human-Environment Modeling & Analysis Laboratory
765.496.2215
765.496.2422
FORS Room 305
195 Marsteller Street
West Lafayette, IN 47907

Dr. Pijanowski specializes in spatial modeling and analysis of land use/cover change. Grounded in the theoretical framework of complex socio-ecological systems, his research employs advanced technologies and methodologies from a wide array of disciplines. Many of his models are used to forecast and backcast land use/cover change patterns which are then linked to other ecological and economic models. Research has been funded by the National Science Foundation, EPA Science to Achieve Results (STAR) program, NASA and various foundations (e.g., Kellogg Foundation, Great Lakes Fisheries Trust, Purdue Research Foundation). Dr. Pijanowski is interested in how results of simulations of the future can be used to achieve a more sustainable society.

A lot of the research being conducted uses geographic information systems, remote sensing, machine learning (e.g., neural networks), role playing simulation, agent-based modeling, expert judgment and semi-structured interview tools and approaches. He is a member of many national (e.g., American Association of Geographers) and international (e.g., Global Land Project) research organizations.

Research Group - Natural Resource Social Science, Forest Measurement and Assessment/GIS, Wildlife Science

Facilities - Human-Environment Modeling and Analysis Lab, Spatial Data Analysis Lab 

Areas of Excellence - Partnering for Land Use Sustainability, Applied Ecological Genetics 

Related Centers - Center for the Environment, Purdue Climate Change Research Center, Purdue Interdisciplinary Center for Ecological Sustainability

 

 

Awards & Honors

(2014) Seeds for Success Award. Purdue University.

(2013) National Research Council - Advancing Land Change Science (Review Team). National Academy of Sciences.

(2013) University Faculty Scholar. Purdue University.

(2011) Plenary talk: The role of online technologies for environmental decision making. EPA SOLEC.

(2010) Keynote talk: Uncertainty in Climate Change Research. World Congress on Biodiversity in Tropical Mesoamerica.

(2008) Keynote Address. SpatgialAccuracy2008.

(2007) NSF III-XT Machine Learning for Land Use/Cover Change. Purdue University and University of Texas at Austin.

Selected Publications

Pijanowski, B. C., & Song, W. (2014). The effects of China's cultivated land balance program on potential land productivity at a national scale. Applied Geography, 46, 158-170.

Tayyebi, A., Pijanowski, B. C., & Pekin, B. K. (in press). Land use legacies of the Ohio River Basin: Using a spatially explicit land use change model to assess past and future impacts on aquatic resources. Applied Geography.

Pijanowski, B. C. (2014). Soundscape science: a new frontier for socioecological research in terrestrial and acquatic environments. In Aquatic Noise (Vol. 27, pp. 1-12).

LaBeau, M. L., Robertson, D. M., Mayer, A. S., Pijanowski, B. C., & Saad, D. A. (2014). Effects of future urban and biofuel crop expansion on the riverine export of phosphorus to the Laurentian Great Lakes. Ecological Modelling, 277, 27-37.

Pijanowski, B. C., Tayyebi, A., Doucette, J., Pekin, B. K., Braun, D., & Plourde, J. (2014). A big data urban growth simulation at a national scale: Configuring the GIS and neural network based Land Transformation Model to run in a High Performance Computing (HPC) environment. Environmental Modelling and Software, 51, 250-268.

Smith, J. W., & Pijanowski, B. C. (2014). Human and policy dimensions of soundscape ecology. Global Environmental Change, 28, 63-74.

Tayyebi, A., & Pijanowski, B. C. (2014). Modeling multiple land use changes using ANN, CART, and MARS: Comparing tradeoffs in goodness of fit and explanatory power of data mining tools. International Journal of Applied Earth Observation and Geoinformation, 28, 102-116.

Fei, S., Pijanowski, B. C., Oswalt, C., Iannone, B., Guo, Q., Liebhold, A., & Clark, T. (in press). Understanding macroscale invasion dynamics processes. Journal of Forestry.

Madurapperuma, B., Iannone, B., Jung, J., Pijanowski, B. C., Fei, S., & Shao, G. (2014). How structural complexity of vegetation facilitates invasion: Integrating LiDAR and FIA invasive species plot data in the Appalachian Mountains of the USA. Purdue GIS Day.

Madurapperuma, B., Iannone, B., Jung, J., Pijanowski, B. C., & Fei, S. (2014). Relationship of structural vegetation complexity and plant invasivability: Integrating LiDAR and FIA invasive species plot data in the Appalachian Mountains of the USA. Restoring Forest Conference.