Ruiliang Pu home page

 

Conference Papers


[51] Yu, Q., R. Pu, S. Landry, 2018. Quantifying 3-D shade provision in urban landscape: multi-city comparison and relationship to land surface temperatures. AAG Annual Conference, New Orleans, LA, April 10 - 14, 2018.

 

[50] Guo, Q., R. Pu, K. Tapley, J. Cheng, and J. Li, 2018. Impact of Coastal Development Strategy on Long-Term Coastline Changes: a Comparison between Tampa Bay and Xiangshan Harbor. AAG Annual Conference, New Orleans, LA, April 10 - 14, 2018.

 

[49] Pu, R., S. Landry, and Q. Yu, 2018. Assessing the Potential of Multi-Seasonal High Resolution Pléiades Satellite Imagery for Mapping Urban Tree Species. AAG Annual Conference, New Orleans, LA, April 10 - 14, 2018.

 

[48] Pu, R. and S. Landry, 2017. A Study on the Potential of High Resolution Worldview-2 Imagery for Discriminating Urban Tree Species. AAG Annual Conference, Boston, April 5 - 8, 2017.

 

[47] Yu, Q., R. Pu, S. Landry, and M. Acheampong, 2017. Understanding the relationship between land surface temperature and vegetation structure for urban heat island studies using multisource remote sensing data. AAG Annual Conference, Boston, April 5 - 8, 2017.

 

[46] Pu, R., and S. Bell, 2016.  Mapping Seagrass Coverage and Spatial Patterns with High Spatial Resolution IKONOS Imagery. IGARSS 2016 annual conference, July 11 - 15, 2016 – Beijing, China.

 

[45] Guo, Q., R. Pu, L. Gao and B. Zhang, 2016. A Comparative Study of Coastline Changes at Tampa Bay and Xiangshan Harbor during the Last 30 Years. IGARSS 2016 annual conference, July 11 - 15, 2016 – Beijing, China.

 

[44] Guo, Q., and R. Pu, 2016. The Coastline Change Detection in Tampa Bay, Florida, USA during the last 30 Years Using Multitemporal Remote Sensing Images. AAG Annual Conference, San Francisco, March 29 - April 2, 2016.

 

[43] Pu, R., and J. Cheng, 2015. Mapping Forest Leaf Area Index Using Spectral and Spatial Information Derived from WorldView-2 Imagery in a Mixed Natural Forest Area in Florida, USA. IGTF 2015 - ASPRS Annual Conference Proceedings, May 4-7, 2015, Tampa, FL.

 

[42] Pu, R., and S. Bell, 2015. Mapping Seagrasses Coverage and Spatial Patterns with IKONOS Imagery: Enhanced Spatial Resolution Can Deliver Greater Mapping Accuracy and More Spatial Information. The proceedings of AAG annual meeting’15, April 21-25, 2014, Chicago, IL.

[41] Guo, Q., R. Pu, L. Gao, and B. Zhang, 2015. A Novel Anomaly Detection Method Incorporating Target Information Derived from Hyperspectral Imagery. The proceedings of AAG annual meeting’15, April 21-25, 2014, Chicago, IL

[40] Wang, H. and R. Pu, 2014. Mapping Health Levels of Robinia Pseudoacaci Forests in the Yellow River Delta, China, Using IKONOS and Landsat 8 OLI Imagery. The proceedings of AAG annual meeting’14, April 8-12, 2014, Tampa, Florida.

[39] Pu, R., S. Bell and C. Meyer, 2014. Mapping and Assessing Seagrass Bed Changes in Central Florida’s West Coast Using Multitemporal Landsat TM Imagery. The proceedings of AAG annual meeting’14, April 8-12, 2014, Tampa, Florida.

[38] Earls, J., B. Dixon, and R. Pu, 2014. Development of A Risk Assessment Index Tool (RAIT) for Pollutants On Organic Farms: Using An Integrated Geospatial Method. The proceedings of AAG annual meeting’14, April 8-12, 2014, Tampa, Florida.

[37] Anchang, J., and R. Pu, 2014. Combining Unsupervised Learning and Spatial Disaggregation as a Basis for Detecting Potential Slum and Informal Neighborhoods from Satellite Imagery: A Sub-Saharan Case Study. The proceedings of AAG annual meeting’14, April 8-12, 2014, Tampa, Florida.

[36] Meyer, C., and R. Pu, 2014. Seagrass + Urban Environment + Sea Level Rise = ? The proceedings of AAG annual meeting’14, April 8-12, 2014, Tampa, Florida.

[35] Pu, R., S. Bell and D. English, 2013. Developing Hyperspectral Vegetation Indices for Identifying Seagrass Species and Cover Classes. The proceedings of AAG annual meeting’13, April9-13, 2013, Los Angeles, California.

[34] Pu, R., S. Bell, Y. Zhang, L. Baggett, Y. Zhang, and C. Meyer, 2012, Mapping and assessing seagrass abundance using Landsat TM and EO-1 ALI/Hyperion Images, The proceedings of AGU Meeting’12, Dec. 3-7, 2012, San Francisco, USA.

[33] Weng, F, and R. Pu, 2012, Assessment of urban growth using multiple endmember spectral mixture analysis: A case study in Tampa, Florid, The proceedings of AAG annual meeting’12, February 24 - 28, 2012, New York City.

[32] Pu, R., and S. Landary, 2012, A comparative analysis of high resolution ikonos and worldview-2 imagery for mapping urban tree species, Florid, The proceedings of AAG annual meeting’12, February 24 - 28, 2012, New York City.

[31] Pu, R., S. Bell, K. H. Levy, C. Meyer, L. Baggett, Y. Zhang, and M. Harrison, 2011, Mapping and assessing seagrass habitats using satellite imagery, The proceedings of AAG annual meeting’11, April 12-16, 2011, Seattle, WA.

[30] Zhao, Y., R. Pu, S. Bell, L. Baggett, and M. Harrison, 2011, The Enhancement of seagrass classification effects from Hyperion images optimized by the cross track illumination correction algorithm of VRadCor and the adaptive filter of SRSSHF, The proceedings of AAG annual meeting’11, April 12-16, 2011, Seattle, WA.

[29] Pu, R., S. Bell, K. H. Levy, S. Meyer, and D. English, 2010.  Mapping detailed seagrass habitats using satellite imagery, IGARSS 2010 annual conference, July 25 - 30, 2010 - Honolulu, Hawaii, USA.

[28] Pu, R., 2010, Comparing Canonical Correlation Analysis with Partial Least Square Regression in Estimation of Forest Leaf Area Index with Multitemporal Landsat TM imagery,  The International Cartographic Association (ICA) Commission on Mapping from Satellite Imagery, Nov., 19, 2010, Orlando, FL.A.

[27] Pu, R., 2010, Identification and Mapping of Urban Forest Species with High Spatial/Spectral Resolution Data, FSG2010 in Jan. 2010, Tampa, FL, USA.

[26] Pu, R., 2009, An exploratory analysis of high resolution Ikonos imagery for mapping urban forest tree species, The proceedings of AAG annual meeting’09 , March 23-26, 2009, Las Vegas, NV, USA.

[25] Pu, R., S. Landry and Q. Yu, 2009, Object-based urban environment mapping with high spatial resolution ikonos imagery, The Proceedings of ASPRS 2009 Annual Conference, March 8-13, 2009, Baltimore, MD, USA. 

[24] Pu, R., P. Gong, and Q. Yu, 2008, Comparative Analysis of EO-1 ALI and Hyperion, and Landsat ETM+ Data for Mapping Forest Crown Closure and Leaf Area Index, The proceedings of AAG annual meeting’08 , April 15-19, 2008, Boston, MA, USA.

[23] Liu, D., and R. Pu, 2008, A Comparison of Physical and Statistical Approaches for Downscaling Thermal Radiance Using ASTER Data, The proceedings of AAG annual meeting’08, April, 15-19, 2008, Boston, MA., USA. 

[22] Pu, R., 2008, An exploratory analysis of in situ hyperspectral data for broadleaf species recognition, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008, July 3 to 11, 2008, pp. 255-260.

[21] Pu, R., P. Gong, and R. Michishita, 2007, Spectral Mixture Analysis for Mapping Abundance of Urban Surface Components from the Terra/ASTER Data, The Proceedings of ASPRS 2007Annual Conference, May 7-11, 2007, Tampa, FL, USA.

[20] Pu, R., P. Gong, Y. Tian, X. Miao and R. Carruthers, 2007, Invasive Species Change Detection Using Artificial Neural Networks and CASI Hyperspectral Imagery, The proceedings of AAG annual meeting’07, April 17-21, 2007, Sanfrancisco, CA, USA.

[19] Pu, R., Z. Li, P. Gong, R. Fraser, I. Csiszar, and W. Hao, 2005, Spatial and Temporal Patterns of Forest Fires in North America as Determined from 12 Years of Daily AVHRR Data, The proceedings of AGU Meeting’05, Dec. 5-9, 2005, San Francisco, USA.

 

[18] Pu, R., P. Gong, Y. Tian, X. Miao and R. Carruthers, 2005, Invasive species mapping using CASI hyperspectral data at Lovelock Site, Nevada, USA, The proceedings of AAG annual meeting’05, April 4-9, 2005, Denver, USA.

 

[17] Pu, R., M. Kelly, G. L. Anderson  and P.  Gong, 2004, A Multilevel Classification Scheme of CASI Data for Detecting Sudden Oak Death, The proceedings of AAG annual meeting’04, March 15-19, 2004, Philadelphia, USA.

 

[16] Pu, R., P. Gong, G. S. Biging and M. R. Larrieu, Estimation of forest leaf area index using vegetation indices and read edge parameters with Hyperion hyperspectral data, The Proceedings of Geoinformatics'02 Conference, June 1-3, 2002, Nanjing, China.

[15] Pu, R., P. Gong and G. S. Biging, 2002, Leaf area index mapping using retrieved reflectance from AVIRIS data, in Proceedings of AVIRIS Workshop 2002, March 3 - 8, 2002, Los Angeles, USA.

[14] Pu, R., P. Gong, G. S. Biging and M. R. Larrieu, 2002, Retrival of surface reflectance and LAI mapping with data from ALI, Hyperion and AVITRIS, in Proceedings of IGARSS'02, June 24-28, Toronto, Canada, USA.

[13] Li, X., P. Gong; R. Pu, P. Sh, 2001, Comparison of two vegetation classification techniques in China based on NOAA/AVHRR data and climate-vegetation indices of the Holdridge life zone, IGARSS '01. IEEE 2001 International , v4:1895 1897, Australia..

[12] Pu, R., S. Ge, N. M. Kelly, and P. Gong, 2001, Correlation analysis of hyperspectral absorption features with the water status of coast live oak leaves, in Proceedings of SPIE'01, July 29- August 3, San Diego, USA.

[11] Gong, P., R. Pu, Z. Li, and J. Scarborough, 2001, An integrated approach for wildland fire mapping in California, USA, using NOAA/AVHRR data, in Proceddings of IGARSS'01, July, 2001, Australia.

[10] Pu, R. and P. Gong, 2000, Band selection from hyperspectral data for conifer species identification, The Proceedings of Geoinformatics'00 Conference, Monterey Bay, June 21-23, 2000, pp.139-146.

[9] Pu, R., P. Gong and R. C. Heald, 1999, In situ hyperspectral data analysis for nutrient estimation of Giant Sequoia, ,IGARSS'99 Proceedings, 28 june - 2 July, 1999, Hamburg, Germany, pp.395-397.

[8] Pu, R., B. Xu, and P. Gong, 1998, Spectral analysis of conifer leaves at different ages, 1998, The Proceedings of Geoinformatics'98 Conference, Beijing, 17-19 June, 1998, pp. 221-228.

[7] Gong, P., G. S. Biging, S. M. Lee, X. Mei, Y. Sheng, R. Pu, B. Xu, K. P. Schwarz, and M. Mostafa, 1998, Photo ecometrics for forest inventory, Presented at the International Forum on Automated interpretation of High Spatial Resolution Digital Imagary for Forestry, Natural resources Canada, Canadian Forest Service, Victoria, BC, Feb. 10-12, 1998.

[6] Pu, R., Gong, P., Truex, R., Barrett, R. H., and Yang, R., 1997, Measuring the importance of input variables in neural network analysis, Proceedings of 1997 ACSM/ASPRS, Technical Paper Volume 3: Remote Sensing & Photogrammetry, April 7-10, 1997, Seattle, Washington, 727-732.

[5] Pu, R. and Gong, P., 1996, Band selection using fuzzy clustering analysis for tree species identification, Proceedings Of Geoinformatics'96, West Palm Beach, Florida USA, April 26-28, 464-471.

[4] Wang, D. X., Pu, R., Gong, P., and Yang, R., 1995, Predicting Forest Yield With An Artificial Neural Network And Multiple Regression, Proceedings Of Geoinformatics'95, Hong Kong, May 26-28, Vol. 2, 771-780.

[3] Freementle, J. R., Pu, R. and Miller, J. R., 1992, Calibration Of Imaging Spectrometer Data Of Reflectance Using Pseudo- Invariant Features, Proceedings Of The Fifteenth Canadian Symposium On Remote Sensing, Toronto, Ontario, 1-4 June, 452-457.

[2] Pu, R. and Miller, J. R. 1991, Classification And Evaluation Of A Shelter Forest Site In A Coastal Area Using Remote Sensing Techniques, Proceedings Of The Fourteenth Canadian Symposium On Remote Sensing, Calgary, Alberta, Canada, 1-4 May , 240-243.

[1] Pu, R., 1991, Remote sensing method of site resource inventory on the coastal zone, The Society of Forestry Graduate in Northern America, Freidericton, New Brunswick, Canada, February 14-18.

 


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