JOSÉ RAMÓN
RODRÍGUEZ PÉREZ
Catedrático de Universidad
Universidad de Oviedo
Oviedo, EspañaPublicaciones en colaboración con investigadores/as de Universidad de Oviedo (12)
2024
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A Handheld Laser-Scanning-Based Methodology for Monitoring Tree Growth in Chestnut Orchards
Sensors, Vol. 24, Núm. 6
2020
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Evaluating Lightning-Caused Fire Occurrence Using Spatial Generalized Additive Models: A Case Study in Central Spain
Risk Analysis, Vol. 40, Núm. 7, pp. 1418-1437
2018
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Accuracy of Unmanned Aerial Vehicle (UAV) and SfM photogrammetry survey as a function of the number and location of ground control points used
Remote Sensing, Vol. 10, Núm. 10
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Determining optimum wavelengths for leaf water content estimation from reflectance: A distance correlation approach
Chemometrics and Intelligent Laboratory Systems, Vol. 173, pp. 41-50
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Leaf water content estimation by functional linear regression of field spectroscopy data
Biosystems Engineering, Vol. 165, pp. 36-46
2017
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Vineyard zone delineation by cluster classification based on annual grape and vine characteristics
Precision Agriculture, Vol. 18, Núm. 4, pp. 525-573
2016
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Biophysical and lightning characteristics drive lightning-induced fire occurrence in the central plateau of the Iberian Peninsula
Agricultural and Forest Meteorology, Vol. 225, pp. 36-47
2013
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A Bootstrap-Based Covariate Selection Method for Modeling the Risk of Lightning-Induced Fires at a Local Scale: A Case Study in Northwest Spain
Human and Ecological Risk Assessment, Vol. 19, Núm. 1, pp. 254-267
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Analysis of the influence of forestry environments on the accuracy of GPS measurements by means of recurrent neural networks
Mathematical and Computer Modelling, Vol. 57, Núm. 7-8, pp. 2016-2023
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Using hyperspectral spectrometry and functional models to characterize vine-leaf composition
IEEE Transactions on Geoscience and Remote Sensing, Vol. 51, Núm. 5, pp. 2610-2618
2012
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Using model-based geostatistics to predict lightning-caused wildfires
Environmental Modelling and Software, Vol. 29, Núm. 1, pp. 44-50
2011
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Analysis of the influence of forest environments on the accuracy of GPS measurements by using genetic algorithms
Mathematical and Computer Modelling, Vol. 54, Núm. 7-8, pp. 1829-1834