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An assessment of the effectiveness of a random forest classifier for land-cover classification
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Rodriguez-Galiano V.F., Ghimire B., Rogan J., Chica-Olmo M., Rigol-Sanchez J.P. An assessment of the effectiveness of a random forest classifier for land-cover classification. ISPRS J. Photogramm. Rem. Sens. 2012, 67:93-104.
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Differentiating plant species within and across diverse ecosystems with imaging spectroscopy
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Roth K.L., Roberts D.A., Dennison P.E., Alonzo M., Peterson S.H., Beland M. Differentiating plant species within and across diverse ecosystems with imaging spectroscopy. Rem. Sens. Environ. 2015, 167:135-151.
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Comparing endmember selection techniques for accurate mapping of plant species and land cover using imaging spectrometer data
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Roth K.L., Dennison P.E., Roberts D.A. Comparing endmember selection techniques for accurate mapping of plant species and land cover using imaging spectrometer data. Rem. Sens. Environ. 2012, 127:139-152.
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Hyperspectral data dimensionality reduction and the impact of multi-seasonal Hyperion EO-1 imagery on classification accuracies of tropical forest species
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Mapping plant functional types at multiple spatial resolutions using imaging spectrometer data
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Schaaf A.N., Dennison P.E., Fryer G.K., Roth K.L., Roberts D.A. Mapping plant functional types at multiple spatial resolutions using imaging spectrometer data. GISci. Rem. Sens. 2011, 48(3):324-344.
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Remote sensing of nitrogen and lignin in Mediterranean vegetation from AVIRIS data: decomposing biochemical from structural signals
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Serrano L., Penuelas J., Ustin S.L. Remote sensing of nitrogen and lignin in Mediterranean vegetation from AVIRIS data: decomposing biochemical from structural signals. Rem. Sens. Environ. 2002, 81(2):355-364.
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Multi-temporal hyperspectral mixture analysis and feature selection for invasive species mapping in rainforests
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Somers B., Asner G.P. Multi-temporal hyperspectral mixture analysis and feature selection for invasive species mapping in rainforests. Rem. Sens. Environ. 2013, 136:14-27.
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Pixels, blocks of pixels, and polygons: choosing a spatial unit for thematic accuracy assessment
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Atmospheric correction for global mapping spectroscopy: ATREM advances for the HyspIRI preparatory campaign
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Thompson D.R., Gao B.C., Green R.O., Roberts D.A., Dennison P.E., Lundeen S.R. Atmospheric correction for global mapping spectroscopy: ATREM advances for the HyspIRI preparatory campaign. Rem. Sens. Environ. 2015, 167:64-77.
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Opening the archive: how free data has enabled the science and monitoring promise of Landsat
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