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National Exposure Research Laboratory (NERL) Research Publications
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Records 1 to 6 of 6 records from ORD-NERL published between 10/21/2013 and 10/21/2018 from author John Iiames
Iiames, J., E. Cooter, D. Schwede, AND J. Williams. A Comparison of Simulated and Field-Derived Leaf Area Index (LAI) and Canopy Height Values from Four Forest Complexes in the Southeastern USA. Forests. MDPI AG, Basel, Switzerland, 9(1):26, (2018).
Iiames, J. AND E. Cooter. EPIC-Simulated and MODIS-Derived Leaf Area Index (LAI) Comparisons Across mMltiple Spatial Scales RSAD Oral Poster based session. Imaging and Geospatial Technology Forum (IGTF 2016), Fort Worth, TX, April 11 - 15, 2016.
Iiames, J., R. Congalton, T. Lewis, AND D. Pilant. Uncertainty Analysis in the Creation of a Fine-Resolution Leaf Area Index (LAI) Reference Map for Validation of Moderate Resolution LAI Products. Remote Sensing. MDPI AG, Basel, Switzerland, 7(0):1397-1421, (2015).
Iiames, J. AND E. Cooter. LAI (in situ, simulated, Landsat-derived, and MODIS): A comparison within an Oak-Hickory Forest Complex in southwestern Virginia, USA. Presented at PECORA 19- Sustaining Land Imaging UAS to Satellites, Denver, CO, November 18, 2014.
Iiames, J. AND R. Lunetta. Classification and Accuracy Assessment for Coarse Resolution Mapping within the Great Lakes Basin, USA. N/A (ed.), PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING. American Society for Photogrammetry and Remote Sensing, Bethesda, MD, 79(11):1015-1026, (2014).
Iiames, J., J. Riegel, AND R. Lunetta. A Comparison of Two Above-Ground Biomass Estimation Techniques Integrating Satellite-Based Remotely Sensed Data and Ground Data for Tropical and Semiarid Forests in Puerto Rico. Presented at American Geophysical Untion Fall Meeting, San Francisco, CA, December 09 - 13, 2013.