Dear Colleagues,
Ecosystem management under changing conditions needs new tools to
insight and forecast forest dynamic and management. Artificial
intelligence is a game changer in forest management. Artificial
intelligence (AI) encompasses a wide range of techniques and frameworks
dating back to the mid twenty century. The use of AI in forestry is
relatively new, especially when compared to the early adoption of AI in
other fields. The irruption of AI spins researchers and practitioners to
unfold the analysis of complex big data. Narrow AI, defined as an AI
system that is specified to perform a limited task, is commonly applied
in biometry (e.g., analysis of forest structure with 3D point cloud
data) but no so common in other ecosystem management domains. Currently,
adequate AI algorithms can be efficiently prototyped due to plenty of
publicly available databases, open-source libraries and the
accessibility to computing platforms.
To insight on this topic and share last works, We, at the University of
Valladolid (Campus at Palencia), are organizing a *Conference on
Artificial Intelligence and Ecosystems Management *You can have update
information at
https://eventos.uva.es/92504/detail/artificial-intelligence-and-ecosystems-…
*Registration is currently open*
This conference is part o the IUFRO unit 4.01.02 - Growth models for
tree and stand simulation, but is open to the whole Division 4 and the
IUFRO community as a whole.
Looking forward to seen you in Palencia
Best regards
--
Prof. Dr. Felipe Bravo
Please note the new email:felipe.bravo@uva.es
Catedrático de Planificación Forestal/Professor of Forest Management
Chair SMART Global Ecosystems | Senior Researcher at iuFOR
Instituto Universitario de Gestión Forestal Sostenible | Sustainable Forest Management Research Institute
Universidad de Valladolid
ETS Ingenierías Agrarias, Universidad de Valladolid
Avda. de Madrid, 44 -- 34004 Palencia
España-Spain
Tl +34 979108424 Fx.+34 979108440
https://smartglobalecosystems.uva.es/ |http://www.research4forestry.eu
https://orcid.org/0000-0001-7348-6695 |https://portaldelaciencia.uva.es/investigadores/181874/detalle