Dr David Riano

Position: Visiting Fellow
School and/or Centres: Centre for European Studies

Location: Forestry Building (48), room F15-E

Biography
Research interests
Publications

David Riaño Ph.D is an Associate Project Scientist at CSTARS with research interests in environmental applications and remote sensing, focusing on studies of natural hazards (wildfires, floods), agricultural management, the carbon budget and water cycle in the context of climate change.

Title: Evaluation of Fuel Moisture Content Products from MODIS over Europe and Australia Fire ignition and propagation depend on Live Fuel Moisture Content (LFMC). Fuels with high LFMC take longer to ignite and water acts as a heat sink, slowing down fire spread and intensity [1]. LFMC is defined as the water weight of the live fuel over the weight after oven drying it at 60–100 °C for 24–48 h. LFMC Remote Sensing (RS) estimates rely on the spectral response changes caused by the direct impact of liquid water absorption features and the indirect impact of pigment and structural changes associated to water content variations [2]. Two main approaches have been applied, empirical and radiative transfer models (RTM) [2]. RTM only outperform empirical models if they are constrained and structural information is known [3]. LFMC signal needs to be discriminated from atmospheric and topographic effects, sun and sensor geometry, soil background, species composition or other plant characteristics [2]. To compensate for some of these factors, several authors prefer to relate the pixel dynamics to the LFMC dynamics using relative spectral indices normalized for each pixel based on a sufficiently large temporal series [4]. Dr. Marta Yebra (Fenner School of Environment and Society, ANU) developed a MODIS FMC product using RTM inversion techniques [5]. The product is under evaluation in Australia using field data collected in 79 sites spread out in all states (Fig. 1).

Greenberg, J.A., Hestir, E.L., Riaño, D., Scheer, G.J., & Ustin, S.L. (2012). Using LiDAR data analysis to estimate changes in insolation under large-scale riparian deforestation. Journal Of The American Water Resources Association in press Casas, A., Riaño, D., Greenberg, J., & Ustin, S.L. (2012). Assessing levee stability with geometric parameters derived from airborne LiDAR. Remote Sensing of Environment, 117, 281288 García, M., Popescu, S.C., Riaño, D., Zhao, K., Neuenschwander, A., Agca, M., & Chuvieco, E. (2012). Characterization of canopy fuels using ICESat/GLAS data. Remote Sensing of Environment, 123, 81-89 Moreno Ruiz, J.A., Riaño, D., Arbelo, M., French, N.H.F., Ustin, S.L., & Whiting, M.L. (2012). Burned area mapping time series in Canada(1984-1999) from NOAA-AVHRR LTDR: A comparison with other remote sensing products and fire perimeters. Remote Sensing of Environment, 117, 407414 Rodriguez, J.M., Ustin, S.L., & Riaño, D. (2011). Contributions of imaging spectroscopy to improve estimates of evapotranspiration. Hydrological Processes 25, 40694081 Kasischke, E.S., Loboda, T., Giglio, L., French, N.H.F., Hoy, E.E., de Jong, B., & Riaño, D. (2011). Quantifying burned area for North American forests implications for direct reduction of carbon stocks. Journal of Geophysical Research-Biogeosciences, 116, 1-17 García, M., Danson, F.M., Riaño, D., Chuvieco, E., Ramirez, F.A., & Bandugula, V. (2011). Terrestrial laser scanning to estimate plot-level forest canopy fuel properties.International Journal of Applied Earth Observation and Geoinformation, 13, 636–645 García, M., Riaño, D., Chuvieco, E., Salas, F.J., & Danson, F.M. (2011). Multispectral and LiDAR data fusion for fuel type mapping using support vector machine and decision rules. Remote Sensing of Environment, 115, 1369-1379 Martín, M.P., Barreto, L., Riaño, D., Fernández-Quintanilla, C., & Vaughan, P. (2011). Assessing the potential of hyperspectral remote sensing for the discrimination of grassweeds in winter cereal crops. International Journal of Remote Sensing, 32, 49–67 García, M., Riaño, D., Chuvieco, E., & Danson, F.M. (2010). Estimating biomass carbon stocks for a Mediterranean forest in central Spain using height and intensity LiDAR data. Remote Sensing of Environment 114, 816-830 Cuevas-González, M., Gerard, F., Balzter, H., & Riaño, D. (2009). Analysing forest recovery after wildfire disturbance in boreal Siberia using remotely sensed vegetation indices. Global Change Biology 15, 561–577 Malmstrom, C.M., Butterfield, H.S., Barber, C., Dieter, B., Harrison, R., Qi, J., Riaño, D., Schrotenboer, A., Stone, S., & Stoner, C.J. (2009). Using remote sensing to evaluate the influence of grassland restoration activities on ecosystem forage provisioning services.Restoration Ecology 17, 526-538 Moreno Ruiz, J.A., Riaño, D., García Lázaro, J.R., & Ustin, S.L. (2009). Intercomparison of AVHRR PAL and LTDR Version 2 Long Term Datasets for Africa from 1982 to 2000 and Its Impact on Mapping Burned Area. IEEE Geoscience and Remote Sensing Letters, 6, 738-742 Cheng, Y.B., Ustin, S.L., Riaño, D., & Vanderbilt, V.C. (2008). Water Content Estimation from Hyperspectral Images and MODIS Indexes in Southeastern Arizona. Remote Sensing of Environment 112, 363-374 Cuevas-González, M., Gerard, F., Balzter, H., & Riaño, D. (2008). Studying the change in fAPAR after forest fires in Siberia using MODIS. International Journal of Remote Sensing 29, 6873-6892 Li, L., Cheng, Y.B., Ustin, S.L., Hua, X.T., & Riaño, D. (2008). Retrieval of vegetation equivalent water thickness from reflectance using genetic algorithm (GA)-partial least squares (PLS) regression. Advances in Space Research 41, 1755-1763 Trombetti, M., Riaño, D., Rubio, M.A., Cheng, Y.B., & Ustin, S.L. (2008). Multitemporal vegetation canopy water content retrieval using Artificial Neural Networks for the USA.Remote Sensing of Environment 112, 203–215 Yebra, M., Chuvieco, E., & Riaño, D. (2008). Estimation of live Fuel Moisture Content from MODIS images for fire risk assessment. Agricultural and Forest Meteorology 148, 523-536 Chuvieco, E., De Santis, A., Riaño, D., & Halligan, K. (2007). Simulation approaches for burn severity estimation using remotely sensed images. Fire Ecology, 3, 129-150 Khanna, S., Palacios-Orueta, A., Whiting, M.L., Riaño, D., Litago, J., & Ustin, S.L. (2007). Development of Angle Indexes for Soil Moisture Estimation, Dry Matter Detection and Land-Cover Discrimination. Remote Sensing of Environment 109, 154–165 Li, L., Ustin, S.L., & Riaño, D. (2007). Retrieval of Fresh Leaf Fuel Moisture Content Using Genetic Algorithm – Partial Least Squares Modeling (GA-PLS). IEEE Geoscience and Remote Sensing Letters, 4, 216-220 Riaño, D., Chuvieco, E., Ustin, S.L., Salas, F.J., Rodríguez-Pérez, J.R., Ribeiro, L.M., Viegas, D.X., Moreno, J.M., & Fernández, H. (2007). Estimation of shrub height for fuel type mapping combining airborne lidar and simultaneous colour infrared images.International Journal of Wildland Fire 16, 341–348 Riaño, D., Moreno Ruiz, J.A., Barón-Martínez, J., & Ustin, S.L. (2007). Burned area surface forecasting using past burned area surface records and Southern Oscillation Index for tropical Africa (1981-1999). Remote Sensing of Environment 107, 571–581 Riaño, D., Moreno Ruiz, J.A., Isidoro, D., & Ustin, S.L. (2007). Spatial and temporal patterns of burned area at global scale between 1981-2000 using NOAA-NASA Pathfinder. Global Change Biology 13, 40–50 Rodríguez Pérez, J.R., Riaño, D., Carlisle, E., Ustin, S.L., & Smart, D.R. (2007). Remote sensing of grapevine water status in vineyards using hyperspectral reflectance indices.American Journal of Enology and Viticulture 58, 302-317 Cheng, Y.B., Zarco-Tejada, P.J., Riaño, D., Rueda, C.A., & Ustin, S.L. (2006). Estimating vegetation water content with hyperspectral data for different canopy scenarios: Relationships between AVIRIS and MODIS indexes. Remote Sensing of Environment 105, 354-366 Chuvieco, E., Riaño, D., Danson, F.M., & Martín, M.P. (2006). Use of radiative transfer models to simulate reflectance of burn severity values. Journal of Geophysical Research-Biogeosciences, 111, G04S09, doi:10.1029/2005JG000143, 1-15 Riaño, D., Ustin, S.L., Usero, L., & Patricio, M.A. (2005). Estimation of fuel moisture content using neural networks. Lecture Notes in Computer Science 3562, 489-498 Riaño, D., Vaughan, P., Chuvieco, E., Zarco-Tejada, P.J., & Ustin, S.L. (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. IEEE Transactions on Geoscience and Remote Sensing 43, 819-826 Chuvieco, E., Cocero, D., Riaño, D., Martin, P., Martínez-Vega, J., de la Riva, J., & Pérez, F. (2004). Combining NDVI and Surface Temperature for the estimation of live fuels moisture content in forest fire danger rating. Remote Sensing of Environment 92, 322-331 Riaño, D., Chuvieco, E., Condés, S., González-Matesanz, J., & Ustin, S.L. (2004). Generation of crown bulk density for Pinus sylvestris L. from lidar. Remote Sensing of Environment 92, 345-352 Riaño, D., Valladares, F., Condés, S., & Chuvieco, E. (2004). Estimation of leaf area index and covered ground from airborne laser scanner (Lidar) in two contrasting forests.Agricultural and Forest Meteorology 124, 269-275 Chuvieco, E., Aguado, I., Cocero, D., & Riaño, D. (2003). Design of an Empirical Index to Estimate Fuel Moisture Content from NOAA-AVHRR Analysis In Forest Fire Danger Studies. International Journal of Remote Sensing 24, 1621-1637 Riaño, D., Chuvieco, E., Salas, F.J., & Aguado, I. (2003). Assessment of different topographic corrections in Landsat-TM data for mapping vegetation types. IEEE Transactions on Geoscience and Remote Sensing 41, 1056-1061 Riaño, D., Meier, E., Allgöwer, B., Chuvieco, E., & Ustin, S.L. (2003). Modeling airborne laser scanning data for the spatial generation of critical forest parameters in fire behavior modeling. Remote Sensing of Environment 86, 177-186 Chuvieco, E., Riaño, D., Aguado, I., & Cocero, D. (2002). Estimation of fuel moisture content from multitemporal analysis of Landsat Thematic Mapper reflectance data: applications in fire danger assessment. International Journal of Remote Sensing 23, 2145-2162 Riaño, D., Chuvieco, E., Salas, J., Palacios-Orueta, A., & Bastarrika, A. (2002). Generation of fuel type maps from Landsat TM images and ancillary data in Mediterranean ecosystems. Canadian Journal of Forest Research-Revue Canadienne de Recherche Forestier 32, 1301-1315 Riaño, D., Chuvieco, E., Ustin, S.L., Zomer, R., Dennison, P., Roberts, D., & Salas, J. (2002). Assessment of vegetation regeneration after fire through multitemporal analysis of AVIRIS images in the Santa Monica Mountains. Remote Sensing of Environment 79, 60-71