Formación

Remote sensing for forest resources

The evaluation and characterisation of forest resources through the application of the most up-to-date remote sensing technologies is the key to this research area.

We develop methodologies and applications to quickly put in value the increasing volume of available information from remote sensors. The integration of platforms and the application of the latest techniques in machine learning help to generate high resolution cartographic products that are customized to each client, such as:

  • Inventory of forest resources
  • Phytosanitary condition of forests and agricultural crops
  • Habitat quality and connectivity
  • Detection of deforestation and degradation processes within the REDD+ framework

Projects

Publications

An Operational Framework for Land Cover Classification in the Context of REDD+ Mechanisms. A Case Study from Costa Rica

An Operational Framework for Land Cover Classification in the Context of REDD+ Mechanisms. A Case Study from Costa Rica

Seasonal and temporal changes in species use of the landscape: how do they impact the inferences from multi-scale habitat modeling?

Seasonal and temporal changes in species use of the landscape: how do they impact the inferences from multi-scale habitat modeling?

Assessing post-storm forest dynamics in the pyrenees using high-resolution LiDAR data and aerial photographs

Assessing post-storm forest dynamics in the pyrenees using high-resolution LiDAR data and aerial photographs

Combining aerial LiDAR and multispectral imagery to assess postfire regeneration types in a Mediterranean forest

Combining aerial LiDAR and multispectral imagery to assess postfire regeneration types in a Mediterranean forest

Other lines of research

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