I received a PhD in Forestry and Agriculture from the Technical University of Madrid. During my dissertation I developed a framework to assess the spatial and temporal variability of different environmental processes, such as forest fires, drought, vegetation dynamics, across different ecoregions, using statistical time series analysis applied to multispectral time series data. After my Ph.D., I received a postdoctoral scholar position at the University of California, Davis (USA), in the centre for spatial technologies and remote sensing (CSTARS), where I began working with imaging spectroscopy and LiDAR data. During this time, I was focused on combining several types of remote sensing data, such as multispectral, hyperspectral, LiDAR and UAV data, with in situ measurements to develop models for assessing biodiversity, drought effects, evapotranspiration, vegetation structure, functional traits, and tree mortality among others in very different ecosystems such as Mediterranean savannas, mix broadleaf-conifer forest, alpine forest, wetland o tropical forest.
(1) understanding the spatial and temporal variability in ecosystem functioning under global climate change scenarios and its relationship with biodiversity loss and the effect in natural resources;
(2) developing robust spatial and temporal models for monitoring and forecasting forest dynamics under the influence of several disturbance factors, such as forest fires, insect attacks, invasive species, and drought, among others;
(3) determining how we can apply each type of remote sensing data to improve our knowledge of ecosystem processes and develop a monitoring system that allows for upscaling and downscaling from local to global level.
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