David

Riaño Arribas

Moreno-Ruiz, J.A.; García-Lázaro, J.R.; Arbelo, M.; Riaño, D. (2019). A comparison of burned area time series in the alaskan boreal forests from different remote sensing products. Forests, 10.

Yebra, M.; Quan, X.; Riaño, D.; Rozas Larraondo, P.; van Dijk, A.I.J.M.; Cary, G.J. (2018). A fuel moisture content and flammability monitoring methodology for continental Australia based on optical remote sensing. Remote Sensing of Environment, 212, 260-272.

Lamelas-Gracia, M.T.; Riaño, D.; Ustin, S. (2019). A LiDAR signature library simulated from 3-dimensional Discrete Anisotropic Radiative Transfer (DART) model to classify fuel types using spectral matching algorithms. GIScience and Remote Sensing.

Burchard-Levine, V.; Nieto, H.; Riaño, D.; Kustas, W.P.; Migliavacca, M.; El-Madany, T.S.; Nelson, J.A.; Andreu, A.; Carrara, A.; Beringer, J.; Baldocchi, D.; Martín, M.P. (2022). A remote sensing-based three-source energy balance model to improve global estimations of evapotranspiration in semi-arid tree-grass ecosystems. Global Change Biology, 28, 1493-1515.

García-Lázaro, J.R.; Moreno-Ruiz, J.A.; Riaño, D.; Arbelo, M. (2018). Estimation of burned area in the Northeastern Siberian boreal forest from a Long-Term Data Record (LTDR) 1982-2015 time series. REMOTE SENSING, 10.

Quan, X.; Yebra, M.; Riaño, D.; He, B.; Lai, G.; Liu, X. (2021). Global fuel moisture content mapping from MODIS. International Journal of Applied Earth Observation and Geoinformation, 101.

Yebra, M.; Scortechini, G.; Badi, A.; Beget, M.E.; Boer, M.M.; Bradstock, R.; Chuvieco, E.; Danson, F.M.; Dennison, P.; Resco de Dios, V.; Di Bella, C.M.; Forsyth, G.; Frost, P.; Garcia, M.; Hamdi, A.; He, B.; Jolly, M.; Kraaij, T.; Martín, M.P.; Mouillot, F.; Newnham, G.; Nolan, R.H.; Pellizzaro, G.; Qi, Y.; Quan, X.; Riaño, D.; Roberts, D.; Sow, M.; Ustin, S. (2019). Globe-LFMC, a global plant water status database for vegetation ecophysiology and wildfire applications. Scientific Data, 6.

Huesca, M.; Riaño, D.; Riaño, D.; Ustin, S.L.; Ustin, S.L. (2019). Spectral mapping methods applied to LiDAR data: Application to fuel type mapping. International Journal of Applied Earth Observation and Geoinformation, 74, 159-168.

Burchard-Levine, V.; Nieto, H.; Riaño, D.; Migliavacca, M.; El-Madany, T.S.; Guzinski, R.; Carrara, A.; Martín, M.P. (2021). The effect of pixel heterogeneity for remote sensing based retrievals of evapotranspiration in a semi-arid tree-grass ecosystem. Remote Sensing of Environment, 260.