Juan de la Riva
Orcid: 0000-0003-2615-270X
According to our database1,
Juan de la Riva
authored at least 16 papers
between 2008 and 2023.
Collaborative distances:
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Bibliography
2023
Assessing GEDI-NASA system for forest fuels classification using machine learning techniques.
Int. J. Appl. Earth Obs. Geoinformation, February, 2023
2021
Assessing the Potential of the DART Model to Discrete Return LiDAR Simulation - Application to Fuel Type Mapping.
Remote. Sens., 2021
2020
Fuel Type Classification Using Airborne Laser Scanning and Sentinel 2 Data in Mediterranean Forest Affected by Wildfires.
Remote. Sens., 2020
2019
Temporal Transferability of Pine Forest Attributes Modeling Using Low-Density Airborne Laser Scanning Data.
Remote. Sens., 2019
2018
Estimating Forest Residual Biomass in Mediterranean Pinus Halepensis Forest Using Low Point Density ALS Data.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018
2015
A Comparison of Open-Source LiDAR Filtering Algorithms in a Mediterranean Forest Environment.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2015
Interpolation Routines Assessment in ALS-Derived Digital Elevation Models for Forestry Applications.
Remote. Sens., 2015
2014
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2014
Assessment of Methods for Land Surface Temperature Retrieval from Landsat-5 TM Images Applicable to Multiscale Tree-Grass Ecosystem Modeling.
Remote. Sens., 2014
Remote. Sens., 2014
An insight into machine-learning algorithms to model human-caused wildfire occurrence.
Environ. Model. Softw., 2014
2010
Sensitivity of X-, C-, and L-Band SAR Backscatter to Burn Severity in Mediterranean Pine Forests.
IEEE Trans. Geosci. Remote. Sens., 2010
TerraSAR-X Data for Burn Severity Evaluation in Mediterranean Forests on Sloped Terrain.
IEEE Trans. Geosci. Remote. Sens., 2010
2009
Backscatter Properties of Multitemporal TerraSAR-X Data and the Effects of Influencing Factors on Burn Severity Evaluation, in a Mediterranean Pine Forest.
Proceedings of the IEEE International Geoscience & Remote Sensing Symposium, 2009
2008
Combined Methodology Based on Field Spectrometry and Digital Photography for Estimating Fire Severity.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2008
Estimation of Crown Biomass of <i>Pinus spp.</i> From Landsat TM and Its Effect on Burn Severity in a Spanish Fire Scar.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2008