Assessment of different topographic corrections in Landsat-TM data for mapping vegetation types (2003). - David Riaño 002; Emilio Chuvieco; Javier Salas; Inmaculada Aguado (IEEE Trans. Geosci. Remote. Sens., 2003)

Estimation of Fuel Moisture Content Using Neural Networks. - David Riaño 002; Susan L. Ustin; Luis Usero Aragonés; Miguel Ángel Patricio Guisado (IWINAC (2), 2005)

Estimation of fuel moisture content by inversion of radiative transfer models to simulate equivalent water thickness and dry matter content: analysis at leaf and canopy level. - David Riaño 002; Patrick Vaughan; Emilio Chuvieco; Pablo J. Zarco-Tejada; Susan L. Ustin (IEEE Trans. Geosci. Remote. Sens., 2005)

Post-fire vegetation phenology in Siberian burn scars. - Heiko Balzter; María Cuevas-González; France Gerard 001; David Riaño 002 (IGARSS, 2007)

Retrieval of Fresh Leaf Fuel Moisture Content Using Genetic Algorithm Partial Least Squares (GA-PLS) Modeling. - Lin Li 006; Susan L. Ustin; David Riaño 002 (IEEE Geosci. Remote. Sens. Lett., 2007)

Intercomparison of AVHRR PAL and LTDR Version 2 Long-Term Data Sets for Africa From 1982 to 2000 and Its Impact on Mapping Burned Area. - Jose Andres Moreno-Ruiz; David Riaño 002; José R. García-Lázaro; Susan L. Ustin (IEEE Geosci. Remote. Sens. Lett., 2009)

Estimation of vegetation water content through GA-PLS modeling of modis reflectance data. - Lin Li 006; Susan L. Ustin; David Riaño 002; Yen-Ben Cheng (IGARSS, 2010)

Terrestrial laser scanning to estimate plot-level forest canopy fuel properties. - Mariano García; F. Mark Danson; David Riaño 002; Emilio Chuvieco; F. Alberto Ramirez; Vishal Bandugula (Int. J. Appl. Earth Obs. Geoinformation, 2011)

Understanding the optical responses of leaf nitrogen in Mediterranean Holm oak (Quercus ilex) using field spectroscopy. - Javier Pacheco-Labrador; Rosario González-Cascón; María Pilar Martín; David Riaño 002 (Int. J. Appl. Earth Obs. Geoinformation, 2014)

Assessment of Methods for Land Surface Temperature Retrieval from Landsat-5 TM Images Applicable to Multiscale Tree-Grass Ecosystem Modeling. - Lidia Vlassova; Fernando Perez-Cabello; Hector Nieto; María Pilar Martín; David Riaño 002; Juan de la Riva (Remote. Sens., 2014)

The Synergy of the 0.05° ( 5km) AVHRR Long-Term Data Record (LTDR) and Landsat TM Archive to Map Large Fires in the North American Boreal Region From 1984 to 1998. - José Andrés Moreno Ruiz; José R. García-Lázaro; David Riaño 002; Shawn C. Kefauver (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2014)

Mapping Live Fuel Moisture Content and Flammability for Continental Australia Using Optical Remote Sensing. - Marta Yebra; Xingwen Quan; David Riaño 002; Pablo Rozas Larraondo; Albert I. J. M. van Dijk; Geoffrey J. Cary (IGARSS, 2018)

Estimation of Burned Area in the Northeastern Siberian Boreal Forest from a Long-Term Data Record (LTDR) 1982-2015 Time Series. - José R. García-Lázaro; Jose Andres Moreno-Ruiz; David Riaño 002; Manuel Arbelo (Remote. Sens., 2018)

Improving the Performance of 3-D Radiative Transfer Model FLIGHT to Simulate Optical Properties of a Tree-Grass Ecosystem. - José Ramón Melendo-Vega; María Pilar Martín; Javier Pacheco-Labrador; Rosario González-Cascón; Gerardo Moreno; Fernando Pérez; Mirco Migliavacca; Mariano García; Peter R. J. North; David Riaño 002 (Remote. Sens., 2018)

Spectral mapping methods applied to LiDAR data: Application to fuel type mapping. - Margarita Huesca; David Riaño 002; Susan L. Ustin (Int. J. Appl. Earth Obs. Geoinformation, 2019)

Seasonal Adaptation of the Thermal-Based Two-Source Energy Balance Model for Estimating Evapotranspiration in a Semiarid Tree-Grass Ecosystem. - Vicente Burchard-Levine; Hector Nieto; David Riaño 002; Mirco Migliavacca; Tarek S. El-Madany; Óscar Pérez-Priego; Arnaud Carrara; M. Pilar Martín (Remote. Sens., 2020)

Estimation of Canopy Gap Fraction from Terrestrial Laser Scanner Using an Angular Grid to Take Advantage of the Full Data Spatial Resolution. - John Gajardo; David Riaño 002; Mariano García; Javier Salas; M. Pilar Martín (Remote. Sens., 2020)

A Live Fuel Moisture Content Product from Landsat TM Satellite Time Series for Implementation in Fire Behavior Models. - Mariano García; David Riaño 002; Marta Yebra; Javier Salas; Adrián Cardil; Santiago Monedero; Joaquín Ramírez; M. Pilar Martín; Lara Vilar; John Gajardo; Susan L. Ustin (Remote. Sens., 2020)

Global fuel moisture content mapping from MODIS. - Xingwen Quan; Marta Yebra; David Riaño 002; Binbin He; Gengke Lai; Xiangzhuo Liu (Int. J. Appl. Earth Obs. Geoinformation, 2021)