Formación

Remote sensing for forestry resources

The evaluation and characterisation of forestry resources through the application of the most up-to-date remote sensing technologies is the key to this working line.

We develop methodologies and applications to deal flexibly with large volumes of information from remote sensors, which are increasing exponentially. The integration of platforms and the application of the latest techniques in automatic learning help to generate high definition cartographic products that are adapted to the needs of each client, such as:

 

  • Inventory of forestry stock
  • Phytosanitary condition of forests and agricultural crops
  • Quality and connectedness of habitats
  • Detection of degradation processes within the framework of REDD+

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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