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Reducing background effects in orchards through spectral vegetation index correction.

, , , , , and . Int. J. Appl. Earth Obs. Geoinformation, (2015)

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Remotely sensed vegetation moisture as explanatory variable of Lyme borreliosis incidence., , , , , , , , and . Int. J. Appl. Earth Obs. Geoinformation, (2012)Generic wavelet-based hyperspectral classification applied to vegetation stress detection., , , , and . IEEE Trans. Geosci. Remote. Sens., 43 (3): 610-614 (2005)Analysing space use patterns by Thiessen polygon and triangulated irregular network interpolation: a non-parametric method for processing telemetric animal fixes., , , and . Int. J. Geogr. Inf. Sci., 13 (5): 499-511 (1999)A Comparison of Nonlinear Mixing Models for Vegetated Areas Using Simulated and Real Hyperspectral Data., , , , and . IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 7 (6): 1869-1878 (2014)3D modeling of light interception in heterogeneous forest canopies using ground-based LiDAR data., , , , , and . Int. J. Appl. Earth Obs. Geoinformation, 13 (5): 792-800 (2011)Viewing Geometry Sensitivity of Commonly Used Vegetation Indices towards the Estimation of Biophysical Variables in Orchards., , , , , and . J. Imaging, 2 (2): 15 (2016)Biophysical drought metrics extraction by time series analysis of SPOT Vegetation data., , , , and . IGARSS, page 2062-2065. IEEE, (2004)CLabSpeG: a compact laboratory spectro-goniometer system enabling rapid and complete BRDF assessments of forest elements., , , , , , , and . IGARSS, page 4422-4424. IEEE, (2003)Validating nonlinear mixing models: Benchmark datasets from vegetated areas., , , and . WHISPERS, page 1-4. IEEE, (2014)Detecting Citrus Tree Water Status by Integrating Hyperspectral Remote Sensing and Physiological Data in a Water Flow-storage Model., , , , , , and . IGARSS (5), page 348-350. IEEE, (2009)