oBJECTIVES
- To implement the standardized database of natural resource inventories and species precedence tests, determining the distribution, characteristics and functioning of the attributes of the Amazonian ecosystems with a holistic perspective, generating reports from data science and through the interaction between faculties of UNAP and other universities.
- To implement the satellite monitoring system of the attributes of the Amazon ecosystems and the changes in climate conditions, through open-source monitoring platforms with satellite images, reducing the digital gap and providing geospatial analysis tools within the framework of data science.
- To establish a flow monitoring tower (Eddy-Covariance), estimating the net exchange of carbon dioxide and water vapor on a large-scale balance, seeking to estimate and understand the behavior of the interaction of matter and energy between the environment and the ecosystem itself and to characterize or better understand, if possible, their behavior, incorporating ourselves to national and international networks (FLUXNET, EUROFLUX, AMERIFLUX).
PRESENTATION OF THE PROJECT TEAM
Jose David Urquiza Muñoz
Waldemar Alegría Muñoz
Rodil Tello Espinoza
Tedi Pacheco Gómez
Javier del Águila Chávez
Overview of available domains of expertise in the project team
The team is formed of professionals whose technical skills address each of the objectives. Composed mainly of Doctors of Sciences, from the Faculties of Forest Sciences and Biological Sciences, who together have many years of experience in Amazonian ecosystems, capacities in inter-institutional articulation, capacity development, and implementation of improvements in the professional careers in which they work.
Comments on the expertise sought for at level of the Flemish HEIs
Knowledge in data infrastructure, standardization and information storage
Knowledge in integration and processing of field data and satellite data (data science)
Experience in gas flow towers (eddy covariance).
Information Technology projects related to data transfer for reports in near real time.
