General information
Universidad Politécnica de Madrid
-
Research GroupComplex Systems Research Group (GSC)
-
Hosting Organisiation
-
AddressCampus, Av. Puerta de Hierro, nº 2, 4
-
Contact Info:
-
Phone
-
Emailgi.gsc@upm.es
Description
The Complex Systems Research Group (GSC), led by Professor Rosa M. Benito, works on the development of technologies for the analysis and modelling of massive data from mobile telephony, remote sensing, drones, proximal sensors and meteorological stations, among others. The application of these analysis allows to understand the agro-ecosystems and their responses to fluctuations or extreme events. It combines complex systems analysis techniques with agricultural and environmental issues collaborating with The Research Centre for the Management of Agricultural and Environmental Risks (CEIGRAM).
CEIGRAM is a Joint Research Centre of UPM established thanks to the collaboration agreement signed between the Spanish National Agency for Agriculture Insurance (ENESA) and AGROSEGURO (The Spanish Association of Combined Agricultural Insurance Companies).
Summary of Research Services
Agricultural Systems: Developing machine learning-based predictive models and analyzing scale laws for sustainable agricultural environments.
Complex Networks: Modeling social networks, human behavior, and ecological relationships using non-linear dynamics.
Interdisciplinary Networks: Active participation in atmospheric/soil and sustainability networks like GUMNET and AGRISOST.
Technology Capabilities
Non-linear methods: laws of scale change (Scaling Laws), self-organizing maps (SOM), machine learning (ML) and convolutional neural network (CNN).
Classification and segmentation of images: computer tomography – scanner, drones and satellites.
Definition of agro-ecosystems areas.
Vegetation index time series of pastures in arid and semi-arid.
Combined drought index in rainfed cereals.
Monitoring deficient irrigation strategy.
3D soil architecture.
Main equipment or Facilities
The GSC has eight high-performance equipment for use as scientific calculation and information storage servers and one as a web server, which are detailed below:
2.5 GHz Intel Xeon processor; with 8 cores. 8GB of RAM and 2 Tb of hard disk.
3.2 GHz Intel I7 processor with 12 cores. 32GB of RAM and 2 Tb of hard disk.
2.4GHz Intel Xeon processor with 36 cores. 64GB of RAM and 3 Tb of hard disk.
2.5GHz Intel Xeon processor with 40 cores. 64GB of RAM and 3 Tb of hard disk.
2.5GHz Intel Xeon processor with 40 cores. 64GB of RAM and 3 Tb of hard disk.
2.5GHz Intel Xeon processor with 8 cores. 8GB of RAM and 1 Tb of hard disk.
2.5GHz Intel Xeon processor with 40 cores. 128GB of RAM and 4 Tb of hard disk .
Computer resources from UPM.
Meteorological data from the stations located in Alameda and La Herreria (Comunidad de Madrid).
Software, tools or licenses to be applied to Big Science
Linux operating system.
Python, Fortran; C.
Matlab, R.
Stata, ArcGis, Qgis.
Google Earth Engine.