116 Sensor-Driven Digital Soil Mapping: II

Poster Session
S05 Pedology

Soil sensors (diffuse reflectance spectroscopy, electromagnetic induction, and others) and remote sensors derive proximal soil and environmental data that are incorporated into spatially-explicit soil prediction models. This session will focus on advancements in sensor technologies and synthesis with field and lab-derived data into complex soil prediction models. Uncertainty and accuracy of sensor-derived data will be given special attention.

Cosponsor(s):

Pedology
Monday, November 1, 2010: 2:00 PM-4:30 PM
Long Beach Convention Center, Exhibit Hall BC, Lower Level

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Poster #1038
Multi-Scale Modeling of Biogeochemical Soil Properties Using Remote Sensing.
Jongsung Kim, Soil and Water Science Department, University of Florida; Sabine Grunwald, Soil and Water Science Department, University of Florida; Todd Osborne, Soil and Water Science Department, University of Florida; R.G. Rivero, Everglades Foundation
Poster #1039
Digital Soil Phosphorus Mapping Using Satellite Imagery and Ancillary Spatial Environmental Datasets.
Jinseok Hong, East Tennessee State University; Sabine Grunwald, University of Florida, Soil and Water Science Department; Nicholas Comerford, University of Florida, Soil and Water Science Department
Poster #1040
Predictive Digital Soil Mapping: A Case Study in the Tibagi Watershed, Central-Eastern Region of Paraná, Brazil.
Selma Regina Aranha Ribeiro, State University of Ponta Grossa; Rodrigo La Scalea, State Univerity of Ponta Grossa; Neyde Fabíola Giarola, State Univesity of Ponta Grossa
Poster #1041
Conditioned Latin Hypercube Sampling to Accomplish Multiple Research Objectives in the Powder River Basin, WY.
Skye Wills, USDA-NRCS; Colby Brungard, Utah State University; Janis L. Boettinger, Utah State University; Shawn Nield, Natural Resources Conservation Service; Mike Leno, USDA; Michael Duniway, USDA ARS
Poster #1042
Discriminating Inorganic From Total Soil Carbon Using Stoichiometric Relationships From Laser-Induced Breakdown Spectroscopy.
Ross Bricklemyer, Washington State University; David Brown, Washington State University; James Barefield, Los Alamos National Laboratory; Samuel M. Clegg, Los Alamos National Laboratory
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A Comparison of Three Light Sources for VNIR Analysis of Soil Samples.
R. Ferguson, USDA/NRCS; Ellis Benham, USDA/NRCS; M. J. Pearson, USDA/NRCS; Larry West, USDA/NRCS
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