Dr Marta Yebra is an Associate Professor in Environmental Engineering at the Fenner School of Environment & Society and the School of Engineering. She is the Director of the ANU/Optus Bushfire Research Centre of Excellence which aims to protect Australia from catastrophic bushfires. She is a Mission Specialist at the ANU Institute for Space and Associate editor for Remote Sensing of Environment. Her research focuses on developing applications of remote sensing for the management of fire risk and impact at local, regional and global scales.
From 2004-2010 she was employed at the University of Alcala, where she was involved in two large multidisciplinary projects which assessed and integrated the main fire risk factors and analysed fire risk trends, considering potential changes in socio-economic factors as well as foreseen impacts of climate change. During her research, she spent time at the Centre for Spatial Technologies and Remote Sensing (University of California at Davis, USA); the National Institute of Agricultural Technology (INTA, Argentina) and the School of Environmental and Life Sciences of Salford (UK).
From 2010 to 2013 Marta was a postdoctoral fellow at CSIRO Land and Water as developing innovative methods to integrate satellite and in-situ observations from micrometeorological tower sites with models to predict carbon-water coupling.
In 2017, Dr Yebra was awarded the prestigious Max Day Environmental Science Fellowship from the Australian Academy of Science. She was also awarded the CSIRO Pyne-Scott Career Award in 2013 and the Bushfire and Natural Hazards CRC's Outstanding Achievement in Research Utilization award in 2019.
She has been invited to present at >30 national and international conferences, including two keynote talks. Dr Yebra has been a member of nine scientific conference committees and convenor of national and international conferences and workshops.
She has taught in 13 undergraduate and graduate courses, including "Environmental Sensing, Mapping and Modelling", "Advanced Remote Sensing and GIS", "Fire in the Environment", and "Environmental measurement, modelling and monitoring". Accreditation as a senior lecturer by the Spanish Agency for Quality Assessment and Accreditation. She supervises honours and graduates research scholars in diverse wildland fire topics (see below).
- Nolan, R, Foster , B, Gabriel, A et al. 2022, 'Drought-related leaf functional traits control spatial and temporal dynamics of live fuel moisture content', Agricultural and Forest Meteorology, vol. 319.
- Miller, L, Zhu, L, Yebra, M et al. 2022, 'Multi-modal Temporal CNNs for Live Fuel Moisture Content Estimation', Environmental Modelling and Software, vol. 156.
- Rao, K, Williams, A, Diffenbaugh, N et al. 2022, 'Plant-water sensitivity regulates wildfire vulnerability', Nature Ecology & Evolution, vol. 6, pp. 332-339.
- Zhao L, Yebra M, Van Dijk AIJM, Cary GJ (2022) Representing vapour and capillary rise from the soil improves a leaf litter moisture model. Journal of Hydrology 612: 128087
- Ye, W, Van Dijk, A, Huete, A et al. 2021, 'Global trends in vegetation seasonality in the GIMMS NDVI3g and their robustness', International Journal of Applied Earth Observation and Geoinformation, vol. 94.
- Quan, X, Yebra, M, Riano, D et al. 2021, 'Global fuel moisture content mapping from MODIS', International Journal of Applied Earth Observation and Geoinformation, vol. 101.
- Resco de Dios, V, Hedo, J, Cunill Camprubi, A et al. 2021, 'Climate change induced declines in fuel moisture may turn currently fire-free Pyrenean mountain forests into fire-prone ecosystems', Science of the Total Environment, vol. 797.
- Vinodkumar, V, Dharssi, I, Yebra, M et al. 2021, 'Continental-scale prediction of live fuel moisture content using soil moisture information', Agricultural and Forest Meteorology, vol. 307.
- Zhu, L, Webb, G, Yebra, M et al. 2021, 'Live fuel moisture content estimation from MODIS: A deep learning approach', ISPRS Journal of Photogrammetry and Remote Sensing, vol. 179, pp. 81-91pp.
- Yebra, M, Gibson, R, Harrison, B et al. 2021, Fire, Australia and New Zealand CRC for Spatial Information, Australia.
- Vilar, L, Herrera, S, Tafur-Garcia, E et al. 2021, 'Modelling wildfire occurrence at regional scale from land use/cover and climate change scenarios', Environmental Modelling and Software, vol. 145.
- Levin, N, Yebra, M & Phinn, S 2021, 'Unveiling the Factors Responsible for Australiaâ€™s Black Summer Fires of 2019/2020', Fire, vol. 4, no. 3, p. 58.
- Yin, C, Xing, M, Yebra, M et al. 2021, 'Relationships between Burn Severity and Environmental Drivers in the Temperate Coniferous Forest of Northern China
', Remote Sensing, vol. 13, no. 24.
- Gale MG, Cary GJ, Van Dijk AIJM, Yebra M (2021) Forest fire fuel through the lens of remote sensing: Review of approaches, challenges and future directions in the remote sensing of biotic determinants of fire behaviour, Remote Sensing of Environment 255: 112282.
- Yebra M, Barnes N, Bryant C, Cary GJ, et al. (2021) An integrated system to protect Australia from catastrophic bushfires. Australian Journal of Emergency Management 36, no. 4, pp. 20-22.
- Zhao L, Yebra M, Van Dijk AIJM, Cary GJ, Matthews S, Sheridan G (2021) The influence of soil moisture on surface and sub-surface litter fuel moisture simulation at five Australian sites. Agricultural and Forest Meteorology 298-299: 108282
- Garcia-Haro, F, Campos-Taberner, M, Moreno, A et al. 2020, 'A global canopy water content product from AVHRR/Metop', ISPRS Journal of Photogrammetry and Remote Sensing, vol. 162, pp. 77-93.
- Evans, M, Scheele, B, Westgate, M et al. 2020, 'Beyond the pond: Terrestrial habitat use by frogs in a changing climate', Biological Conservation, vol. 249, pp. 1-11.
- Massetti, A, Rudiger, C, Yebra, M et al 2019, 'The Vegetation Structure Perpendicular Index (VSPI): A forest condition index for wildfire predictions', Remote Sensing of Environment, vol. 224, pp. 167-181.
- Chen, X, Evans, J, Parinussa, R et al 2018, 'Estimating fire severity and carbon emissions over Australian tropical savannahs based on passive microwave satellite observations', International Journal of Remote Sensing, vol. 39, no. 20, pp. 6479-6498.
- Liu, X, He, B, Quan, X et al 2018, 'Near real-time extracting Wildfire spread rate from Himawari-8 satellite data', Remote Sensing, vol. 10, no. 10, pp. 15pp.
- Van Dijk, A, Schellekens, J, Yebra, M et al. 2018, 'Global 5 km resolution estimates of secondary evaporation including irrigation through satellite data assimilation', Hydrology and Earth System Sciences, vol. 22, no. 9, pp. 4959-4980.
- Yebra M, Quan X, Riaño D, Rozas Larraondo P, van Dijk AIJM, Cary GJ (2018) A fuel moisture content and flammability monitoring methodology for continental Australia based on optical remote sensing. Remote Sensing of Environment 212, 260-272.
- Chen, Y, Zhu, X, Yebra, M et al 2017, 'Development of a predictive model for estimating forest surface fuel load in Australian eucalypt forests with LiDAR data', Environmental Modelling and Software, vol. 97, pp. 61-71.
- Quan, X, He, B, Yebra, M et al 2017, 'A radiative transfer model-based method for the estimation of grassland aboveground biomass', International Journal of Applied Earth Observation and Geoinformation, vol. 54, no. -, pp. 159-168pp.
- Quan, X, He, B, Yebra, M et al 2017, 'Retrieval of forest fuel moisture content using a coupled radiative transfer model', Environmental Modelling and Software, vol. 95, pp. 290-302pp..
- Holgate CM, Van Dijk AIJM, Cary GJ, Yebra M (2017) Using alternative soil moisture estimates in the McArthur Forest Fire Danger Index. International Journal of Wildland Fire, 26(9), 806-819.
- Chen, Y, Zhu, X, Yebra, M et al 2016, 'Estimation of forest surface fuel load using airborne LiDAR data', Earth Resources and Environmental Remote Sensing/GIS Applications VII, ed. Michel U.Schulz K.Ci, SPIE, Bellingham, Washington, pp. -.
- Chen, Y, Zhu, X, Yebra, M et al 2016, 'Strata-based forest fuel classification for wild fire hazard assessment using terrestrial LiDAR', Journal of Applied Remote Sensing, vol. 10, no. 4, pp. 1-16.
- Marselis, S, Yebra, M, Jovanovic, T et al 2016, 'Deriving comprehensive forest structure information from mobile laser scanning observations using automated point cloud classification', Environmental Modelling and Software, vol. 82, pp. 142-151.
- Yebra, M, Van Dijk, A, Leuning, R et al 2015, 'Global vegetation gross primary production estimation using satellite-derived light-use efficiency and canopy conductance', Remote Sensing of Environment, vol. 163, pp. 206-216.
- Yebra M, Marselis S, van Dijk A, Cary G and Chen Y (2015) Using
LiDAR for forest and fuel structure mapping: options, benefits, requirements
and costs. Bushfire & Natural Hazards CRC, Australia.
- Jurdao Knecht, S, Yebra, M, Oliva, P et al 2014, 'Laboratory Measurements of Plant Drying: Implications to Estimate Moisture Content from Radiative Transfer Models in Two Temperate Species', Photogrammetric Engineering and Remote Sensing, vol. 80, no. 5, pp. 451-459.
- Chuvieco Salinero, E, Aguado, I, Jurdao Knecht, S et al 2014, 'Integrating geospatial information into fire risk assessment', International Journal of Wildland Fire, vol. 23, no. 5, pp. 606-619.
- Jurdao Knecht, S, Yebra, M & Chuvieco Salinero, E 2013, 'FORUM - Live Fuel Moisture Content Derived from Remote Sensing Estimates in Temperate Shrublands and Grasslands'.
- Jurdao Knecht, S, Yebra, M, Guerschman, J et al 2013, 'Regional estimation of woodland moisture content by inverting Radiative Transfer Models', Remote Sensing of Environment, vol. 132, pp. 59-70.
- Yebra, M, Dennison, W, Chuvieco Salinero, E et al 2013, 'A global review of remote sensing of live fuel moisture content for fire danger assessment: Moving towards operational products', Remote Sensing of Environment, vol. 136, pp. 455-468.
- Jurdao Knecht, S, Yebra, M, Bastarrika Izagirre, A et al 2013, 'LIVE FUEL MOISTURE CONTENT AND IGNITION PROBABILITY IN THE IBERIAN PENINSULAR TERRITORY OF SPAIN', GeoFocus, no. 13, pp. 25-40.
- Romero, A, Aguado, I & Yebra, M 2012, 'Estimation of dry matter content in leaves using normalized indexes and PROSPECT model inversion', International Journal of Remote Sensing, vol. 33, no. 2, pp. 396-414.
- Glenn, E, Doody, T, Guerschman, J et al 2011, 'Actual evapotranspiration estimation by ground and remote sensing methods: the Australian experience', Hydrological Processes, vol. 25, no. 26, pp. 4103-4116.
- Jurdao Knecht, S, Arevalillo, J, Chuvieco Salinero, E et al 2011, 'Development of a method to transform life fuel moisture content into ignition probability', International Symposium on Remote Sensing of Environment (ISRSE 2011), International Symposium for Remote Sensing of the Environment, Sydney, NSW, pp. 3pp.
- Yebra, M, Beget, M, Oricchio, P et al 2010, 'InversiÃ³n de modelos de simulaciÃ³n de la reflectividad para la estimaciÃ³n del estado hÃdrico del combustible vivo en matorrales y pastizales de la Argentina', Serie Geografica, vol. 16, pp. 51-59.
- Chuvieco Salinero, E, Aguado, I, Yebra, M et al 2010, 'Development of a framework for fire risk assessment using remote sensing and geographic information system technologies', Ecological Modelling, vol. 221, no. 1, pp. 46-58.
- Yebra, M & Chuvieco Salinero, E 2009, 'Generation of Species-Specific Look-Up Table for Fuel Moisture Content Assessment', IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 2, no. 1, pp. 21-26.
- Chuvieco Salinero, E, Gonzalez, I, Verdu, F et al 2009, 'Prediction of fire occurrence from live fuel moisture content measurements in a Mediterranean ecosystem', International Journal of Wildland Fire, vol. 18, pp. 430-441.
- Yebra, M & Chuvieco Salinero, E 2009, 'Linking ecological information and radiative transfer models to estimate fuel moisture content in the Mediterranean region of Spain: Solving the ill-posed inverse problem', Remote Sensing of Environment, vol. 113, no. 11, pp. 2403-2411.
- Yebra, M & Chuvieco Salinero, E 2008, 'Modelos de Simulacion de Refectividad en ecologia: potencialidades y problemas', ecosistemas, vol. 17, no. 3, pp. 23-38.
- Yebra, M, Chuvieco Salinero, E & Riano, D 2008, 'Estimation of live fuel moisture content from MODIS images for fire risk assessment', Agricultural and Forest Meteorology, vol. 148, no. 4, pp. 523-536.
- Solana, H, Salinero, E, Suarez, I et al 2008, 'Propuesta de un sistema espacialmente explÃcito para evaluar el peligro de incendios', Serie Geografica, vol. 14, pp. 109-130.
- Yebra, M, Chuvieco Salinero, E & Aguado, I 2008, 'Comparison of empirical and Radiative transfer models for water content estimation in Grass-land: Generaliting Power', Spanish Journal of Remote Sensing, vol. 29, pp. 73-90.
- Yebra, M, de Santis, A & Chuvieco Salinero, E 2005, 'EstimaciÃ³n del peligro de incendios a partir de teledetecciÃ³n y variables meteorolÃ³gicas: variaciÃ³n temporal del contenido de humedad del combustible', Recursos Rurais, vol. 1, pp. 9-19.