Ruiliang Pu

Professor, School of Geosciences, College of Arts & Sciences

Organization: University of South Florida

Education: Ph.D. in Cartography & Geographic Information System, Chinese Academy of Sciences, China, conducted at College of Natural Resources (CNR), UC Berkeley, USA

Dr. Pu's research experience and interests are in remote sensing, GIS and spatial statistics with direct applications to natural hazard monitoring, land use/cover change detection, biophysical and biochemical parameters extraction, and coastal and terrestrial ecosystems modeling. His current research interests are in mapping and characterization of seagrass habitats using spacecraft observations and urban environmental studies using thermal and optical remote sensing data with an emphasis on analysis of high spatial and spectral resolution satellite imagery.

Subject Areas:
Data Analysis/Modeling, Ecology, Sustainability

Selected Projects

Selected Publications

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  Pu, R., Landry, S.M., & Jingcheng, Z. (2015). Evaluation of Atmospheric Correction Methods in Identifying Urban Tree Species with WorldView-2 Imagery. Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(5), 1886-1897.
• Pu, R., & Cheng, J. (2015). Mapping Forest Leaf Area Index Using Reflectance and Textural Information Derived from WorldView-2 Imagery in a Mixed Natural Forest Area in Florida, USA. International Journal of Applied Earth Observation and Geoinformation, 42, 11-23.
• Pu, R., & Bell, S. (2013). A protocol for improving mapping and assessing of seagrass abundance along the West Central Coast of Florida using Landsat TM and EO-1ALI/Hyperion images. Journal of Photogrammetry and Remote Sensing, 83, 116-129.
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  Pu, R., & Landry, S.M. (2012). A comparative analysis of high spatial resolution IKONOS and WorldView-2 imagery for mapping urban tree species. Remote Sensing of Environment, 124, 516-533.
• Pu, R., Bell, S., Bagget, L., Meyer, C., & Zhao, Y. (2012). Discrimination of seagrass species and cover classes with in situ hyperspectral data. Journal of Coastal Research, 28(6), 1330-1344.
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  Pu, R., Landry, S.M., & Qiuyah, Y. (2011). Object-based urban detailed land cover classification with high spatial resolution IKONOS imagery. International Journal of Remote Sensing, 32(12), 3285-3308.
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  Landry, S.M., & Pu, R. (2010). The impact of land development regulation on residential tree cover: An empirical evaluation using high-resolution IKONOS imagery. Landscape and Urban Planning, 94(2), 94-104.
• Pu, R. (2009). Broadleaf Species Recognition with In Situ Hyperspectral Data. International Journal of Remote Sensing, 30(11), 2759-2779.
• Pu, R., Gong, P., Michishita, R., & Sasagawa, T. (2008). Spectral Mixture Analysis for Mapping Abundance of Urban Surface Components from the Terra/ASTER Data. Remote Sensing of Environment, 112, 939-954.
• Pu, R., Li, Z., Gong, P., Csiszar, I., Fraser, R., Hao, W.M., Kondragunta, S., & Weng, F. (2007). Development and Analysis of a 12-year Daily 1-km Forest Fire Data across the North America from NOAA/AVHRR Data. Remote Sensing of Environment, 108, 198-208.
• Pu, R., Gong, P., Michishita, R., & Sasagawa, T. (2006). Assessment of Multi-Resolution and Multi-Sensor Data for Urban Surface Temperature Retrieval. Remote Sensing of Environment, 104, 211-225.
• Pu, R., & Gong, P. (2004). Wavelet transform applied to EO-1 hyperspectral data for forest LAI and crown closure mapping. Remote Sensing of Environment, 91, 212-224.