Note: Program subject to change without notice

Wednesday, November 7, 2007: 9:25 AM
300: Digital Soil Prediction & Mapping: I. Methods, Examples, Issues
Sponsor: S05 Pedology
Presiding: Jonathan Hempel, USDA-NRCS
  Introductory Remarks
  The Natural Resources Conservation Service's Digital Soil Mapping Challenge.
Amanda Moore, National Geospatial Development Center, Darrell Kautz, National Geospatial Development Center, Jon Hempel, National Geospatial Development Center, James A. Thompson, West Virginia University, James Burt, University of Wisconsin-Madison, Craig Rasmussen, University of Arizona, A-Xing Zhu, University of Wisconsin-Madison
  Purposive Sampling for Digital Soil Mapping under Fuzzy Logic.
A-Xing Zhu, University of Wisconsin-Madison, Lin Yang, Chinese Academy of Sciences, Edward English, University of Wisconsin-Madison, Baolin Li, Chinese Academy of Sciences, Chengzhi Qin, Chinese Academy of Sciences, Pei Tao, Chinese Academy of Sciences, James E. Burt, University of Wisconsin-Madison
  Globalsoilmap.net Producing Soil Property Information for the World.
Jonathan Hempel, USDA-NRCS, James Thompson, West Virginia University
  Application of Machine Learning Techniques for Soil Survey Updates.
Brian Slater, The Ohio State University, Sakthi Kumaran Subburayalu, The Ohio State University
  Economic Benefits of the National Cooperative Soil Survey Program.
Gerald Fletcher, West Virginia University, Jonathan Hempel, USDA-NRCS, Archana Prahan, West Virginia University
  Break
  Scale Dependence of Environmental Correlation of Soil Spatial Variability: A Comparison of Three Adaptive Techniques.
Daehyun Kim, Texas A&M University, David M. Cairns, Texas A&M University, Keun Bae Yu, Seoul National University, Soo Jin Park, Seoul National University
  Determining the Optimal Spatial Interpolations for Soil Properties with Different Sample Sizes.
Qing Zhu, Pennsylvania State Univ., Hangsheng Lin, Pennsylvania State Univ., Xiaobo Zhou, Pennsylvania State Univ., Jun Zhang, Penn State University
  Using Decision Tree Analysis for Predictive Soils Mapping in the Great Basin.
Sarah Hash, Oregon State University, Jay S. Noller, Oregon State University
  Predicting the Distribution of Mollic Soils using a Solar Radiation Modelling Approach.
Dylan Beaudette, University of California at Davis, Anthony O'Geen, University of California-Davis
  Biogeography and Soil Development in the Pumice Zone of Central Oregon.
Sheila Slevin, Oregon State University, Jay S. Noller, Oregon State University
  Discussion
  Adjourn

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