EDUARDO MANUEL
GONZÁLEZ FERREIRO
Profesor Titular de Universidad
Universidade de Santiago de Compostela
Santiago de Compostela, EspañaPublikationen in Zusammenarbeit mit Forschern von Universidade de Santiago de Compostela (28)
2021
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3d point clouds in forest remote sensing
Remote Sensing
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Developing a site index model for P. Pinaster stands in NW Spain by combining bi-temporal ALS data and environmental data
Forest Ecology and Management, Vol. 481
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Estimating Stand and Fire-Related Surface and Canopy Fuel Variables in Pine Stands Using Low-Density Airborne and Single-Scan Terrestrial Laser Scanning Data
Remote Sensing, Vol. 13, Núm. 24
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Forest road detection using LiDAR data and hybrid classification
Remote Sensing, Vol. 13, Núm. 3, pp. 1-36
2019
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Estimación de la distribución vertical de combustibles finos del dosel de copas en masas de Pinus sylvestris empleando datos LiDAR de baja densidad
Revista de teledetección: Revista de la Asociación Española de Teledetección, Núm. 53, pp. 1-16
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PpC: a new method to reduce the density of lidar data. Does it affect the DEM accuracy?
Photogrammetric Record, Vol. 34, Núm. 167, pp. 304-329
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Predicting growing stock volume of eucalyptus plantations using 3-D point clouds derived from UAV imagery and ALS data
Forests, Vol. 10, Núm. 10
2018
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Comparison of ALS- and UAV(SfM)-derived high-density point clouds for individual tree detection in Eucalyptus plantations
International Journal of Remote Sensing, Vol. 39, Núm. 15-16, pp. 5211-5235
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Ensemble classification of individual Pinus crowns from multispectral satellite imagery and airborne LiDAR
International Journal of Applied Earth Observation and Geoinformation, Vol. 65, pp. 12-23
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Evaluating the potential of ALS data to increase the efficiency of aboveground biomass estimates in tropical peat-swamp forests
Remote Sensing, Vol. 10, Núm. 9
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Modeling diameter distributions in radiata pine plantations in Spain with existing countrywide LiDAR data
Annals of Forest Science, Vol. 75, Núm. 2
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Potential of Sentinel-2A data to model surface and canopy fuel characteristics in relation to crown fire hazard
Remote Sensing, Vol. 10, Núm. 10
2017
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Estimación de las existencias maderables de Pinus radiata a escala provincial utilizando datos LiDAR de baja resolución
Bosque, Vol. 38, Núm. 1, pp. 17-28
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Impact of plot size and model selection on forest biomass estimation using airborne LiDAR: A case study of pine plantations in southern Spain
Journal of Forest Science, Vol. 63, Núm. 2, pp. 88-97
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Modelling the vertical distribution of canopy fuel load using national forest inventory and low-density airbone laser scanning data
PLoS ONE, Vol. 12, Núm. 4
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Use of multi-temporal UAV-derived imagery for estimating individual tree growth in Pinus pinea stands
Forests, Vol. 8, Núm. 8
2016
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A preliminary study of the suitability of deep learning to improve LiDAR-derived biomass estimation
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
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Accuracy assessment of LiDAR-derived digital elevation models in a rural landscape with complex terrain
Journal of Applied Remote Sensing, Vol. 10, Núm. 1
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Comparison of ALS based models for estimating aboveground biomass in three types of Mediterranean forest
European Journal of Remote Sensing, Vol. 49, pp. 185-204
2014
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Evolutionary feature selection to estimate forest stand variables using LiDAR
International Journal of Applied Earth Observation and Geoinformation, Vol. 26, Núm. 1, pp. 119-131