Huesca, Margarita

Margarita Huesca is a Forestry Engineering at the Technical University of Madrid. She obtained her MSc in Geo-information Sciences at Wageningen University (The Netherlands) and she finished her Ph.D at the Technical University of Madrid in the Agricultural School in January 2013. Currently, she is a postdoctoral researcher here at CSTARS (Center for Spatial Technologies and Remote Sensing) lab at University of California Davis.

In her doctoral dissertation Huesca was focused on the quantitative assessment of remote sensing time series and its application to model environmental variables. She started my research line based on Statistical Time Series Analysis to quantify and monitor ecological processes, such as forest fires, phenological dynamics and evapotranspiration among others, in the Iberian Peninsula. During her postdoctoral stay she will be  completing the temporal multiespectral remote sensing skill with the knowledge of imaging spectroscopy and LiDAR data. Currently her interest is how to take advance of the advantages of each type of remote sensing data to improve our knowledge about the ecosystem processes

  • Current Projects 

        1Huesca is working as part of the NASA HyspIRI Preparatory Science initiative, to assess the potential and capabilities of the mission for accurately estimating pigment content across a wide range of plant species. Specifically focusing on evaluating the estimation of structural properties directly from hyperspectral data, with the broader goal that these might be used to constrain retrievals of canopy chemistry.

       2.  Huesca is working in a project where we are analyzing if different management practices may increase the forest resistance to drought using imaging spectroscopy and LiDAR remote sensing data and fieldwork data.

       3.  Huesca is also involved in a project based on generating LiDAR signature library for automatic fuel type classification of active fires in real time.

       4. Huesca will be starting another project with the goal of discriminating an invasive herb (Lepidium latifolium) using time series of SENTINEL data.




  1. T. Schmid, M. Rodriguez-Rastrero, P. Escribano, A. Palacios-Orueta, E. Ben Dor, A. Plaza, R. Milewski, M. Huesca, A. Bracken, V. Cicuendez, M. Pelayo, S. Chabrillat. Characterization of soil erosion indicators using hyperspectral data from a Mediterranean rainfed cultivated region. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2015, PP, 1-16.
  2. V. Cicuendez; M. Rodriguez-Rastrero; M. Huesca, C. Uribe, T. F Schmid, R. Inclán, J. Litago, V. Sanchez-Girón, S. Merino de Miguel, A. Palacios-Orueta. Assessment of soil respiration patterns in an irrigated corn field based on spectral information acquired by field spectroscopy. Agriculture, Ecosystems and Environment,2015, 212, 158-167.
  3. M. Huesca, S. Merino-de-Miguel, L. Eklundh, J. Litago, V. Cicuéndez, M. Rodríguez-Rastrero, S.L. Ustin, A. Palacios-Orueta. Ecosystem functional assessment based on the “optical type” concept and self-similarity patterns: An application using MODIS-NDVI time series autocorrelation. International Journal of Applied Earth Observation and Geoinformation. 2015, 43, 132-148.
  4. V. Cicuéndez, J. Litago, M. Huesca, M. Rodriguez-Rastrero, L. Recuero, S. Merino-de-Miguel, A. Palacios-Orueta. Assessment of the gross primary production dynamics of a Mediterranean holm oak forest by remote sensing time series analysis. Agroforestry Systems, 2015. 89,491-510.
  5. L. Tornos, M. Huesca, J.A. Dominguez, M.C. Moyano, V. Cicuendez, L. Recuero, A. Palacios-Orueta. Assessment of MODIS spectral indices for determining rice paddy agricultural practices and hydroperiod. ISPRS Journal of Photogrammetry and Remote Sensing, 2015,101, 110-124.
  6. M. Huesca, J. Litago, S. Merino-de-Miguel, V. Cicuendez-López-Ocaña, A. Palacios-Orueta. Modeling and forecasting MODIS-based Fire Potential Index on a pixel basis using time series models. International Journal of Applied Earth Observation and Geoinformation, 2014, 26, 363–376. 
  7. M. Huesca, S. Merino-de-Miguel, F. González-alonso An intercomparison of satellite-derived burned area maps: Application to the August 2006 Galicia (Spain) forest fires. . Forest System. 2013, 22, 222-231.
  8. M. Huesca, S. Merino-de-Miguel, F. Gónzalez-Alonso, S. Martínez, J.M. Cuevas, Abel Calle. Using hyperspectral images to study forest vegetation recovery after fire.  International Journal of remote sensing. 2013, 34, 4025-4048.
  9. A. Palacios-Orueta, M. Huesca, M. L. Whiting, J. Litago, S. Khanna, M. García, S.L. Ustin.Derivation of phenological metrics by function fitting to time-series of spectral shape indexes AS1 and AS2: Mapping cotton phenological stages using MODIS time series. Remote Sensing of Environment, 2012, 126, 148–159.
  10. Colombia. S. Merino-de-Miguel, F. González-Alonso, M. Huesca, D. Armenteras.MODIS Reflectance and Active Fire Data for Burn Mapping in Colombia. Earth Interact., 2011, 15, 1–17.
  11. F. González-Alonso, M. Huesca, J.M. Cuevas, S. Martínez, J. A. Gómez, E. de Miguel.Utilización de imágenes hiperespectrales AHS para el estudio de zonas afectadas por incendios forestales. Revista de teledetección. 2010, 33, 29-46
  12. J.M. Cuevas, F. González-Alonso, A. Roldán, M. Huesca Productividad Potencial Climática y una imagen IRS-1C WiFS en el Parque Natural Los Alcornocales. Relación con la biomasa forestal real.. Investigación Agraria: Sistemas y Recursos Forestales, 2009, 18, 276-288.
  13. S. Merino-de-Miguel, M. Huesca, F. Gonzalez-Alonso.An assessment on the Galician (Northwest Spain) forest fires using remote sensing data and ancillary maps. Ecological Modelling. 2009, 221, 67-74.
  14. M. Huesca, J. Litago, A. Palacios-Orueta, F. Montes, A. Sebastián-López, P. Escribano. Assessment of forest fire regimes using MODIS fire potential: a time series approach.  Agricultural and Forest Meteorology. 2009,149 1946–1955.
  15. M. Huesca, F. González-Alonso, J.M. Cuevas, S. Merino-de-miguel. Comparación de dos algoritmos para la estimación de áreas quemadas a partir de imágenes MODIS. Aplicación a los incendios de canarias de julio de 2007. M. Huesca, F. González-Alonso, J.M. Cuevas, S. Merino-de-miguel. Revista de Teledetección, 2009,1, 24-36.
  16. M. Huesca, F. González-Alonso, J.M. Cuevas, S. Merino-de-Miguel. Estimación de la superficie quemada en los incendios forestales de canarias en julio de 2007 utilizando sinérgicamente imágenes MODIS y anomalías térmicas.   Investigación Agraria: Sistemas y Recursos Forestales. 2008, 17, 308-316.
  17. F. González-Alonso, S. Kaiser, S. Merino de Miguel, M. Huesca, A. Roldán, J.M. Cuevas, G. Vetura.Comparing AWiFS and MERIS images for land use-land cover maping in Spain. Revista de Teledetección, 2008, 30: 85-91.
  18. M. Huesca, M. Garcia, K. Roth, A. Casas, S. Ustin. Canopy Structural Attributes derived from imaging spectrocopy AVIRIS Data in a Mixed Broadleaf/Conifer Forest. Remonte Sensing of Environment2016, 182, 208-226.
  19. K.L. Roth, A. Casas, M. Huesca, S.L. Ustin, M.M. Alsina, S.A. Mathews, M.L. Whiting. Leaf spectral clusters as potential optical leaf functional types within California ecosystems. Remote Sensing of Environment2016, 184, 229-246.