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The RSLab is deeply involved in the application of the results obtained in the developed researches to the real-world domain. In particular, the members of the RSLab have been involved in important national and international projects funded by different organizations. A selection of the most recent projects is reported below:

Current Projects

PRISMALearn - Advanced machine learning techniques for PRISMA mission data fusion and image analysis (Italian Space Agency) [2022 - 2024]

Orbiting Arid Subsurface and Ice Sheet Sounder (OASIS) Pre-Phase A Study (NASA-JPL, University of Southern California) [2021 -2022].

Multispectral camera takes small-scale farms into the digital age. (EU-H2020-MSCA-IF) [2021-2023]

Reinforcing the AI4EU Platform by Advancing Earth Observation Intelligence, Innovation and Adoption. (EU-H2020-ICT-IA) [2021 - 2023]

Phase 0 and Phase A study of the Sub-Surface Radar Sounder (SRS) instrument for the EnVision mission to Venus (European Space Agency - Italian Space Agency) [2018-2021].

Climate Change Initiative Extension (CCI+) Phase 1, New Essential Climate Variables (NEW ECVS) High Resolution Land Cover ECV (HR_LandCover_cci) -ESA (European Space Agency) [2018-2021]

Past Projects

From Copernicus Big Data to Extreme Earth Analytics (ExtremeEarth), European Commission (H2020-ICT-2018-2020, RIA) [2019-2021].

Technological evolution and experimental validation of an airborne radar in VHF and UHF bands (frequency lower than 1 GHz) (Italian Space Agency) [2015-2019]

Improve the science of pocesses within the cryosphere by integrating hydrological modelling with remote sensing in a multi-level data fusion approach
(EUREGIO) [2016-2019]

SaTellite Radar sounder for eArTh sUb-surface Sensing
(Italian Space Agency) [2017-2018]

  • MS-TS – Analysis of MultiSensor VHR image Time Series (DigitalGlobe Foundation) [2014-2016].
  • A novel integrated system for the analysis of very high spatial and spectral resolution remote sensing data (MIUR-Italian Ministry of the Education, Research and University) [2014-2016].
  • RAMSES – RAdarsat2 based Monitoring of Surface ESsential variables: An integrative framework for retrieval of soil and vegetation parameters (moisture and biomass) in agricultural areas (Canadian Space Agency) [2013-2015].
  • ITPAR (phase 3) – India-Trento Program for Advanced Research – Advanced methods for the analysis of optical and radar remote sensing images acquired by last generation satellite systems – [2012-2015]
  • Advanced remote sensing systems for environmental monitoring – [2010-2015]
  • Evaluation of Digital Elevation Models derived from TerraSAR-X data (DLR – German Aerospace Center)-[2010-2015]
  • NEWFOR/FORLIDAR – Automatic estimation of forest dendrometric variables in complex forests by using LiDAR and Hyperspectral data [2013-2014].
  • SISAR – Automatic Recognition of Very High Resolution SAR Images – [2010-2014]
  • MaleRS – Machine learning techniques for the analysis and classification of the last generation of remote sensing data (Outgoing post-doc of Claudio Persello to Max Planck Institute for Biological Cybernetics, Empirical Inference department in cooperation with University of Trento funded by Trento Autonomous Province) – [2011-2014]
  • FORLIDAR (phase 3) – Methods for the estimation of forest volume and biomass from LIDAR and Hyperspectral data – [2011-2012]
  • Development and validation of multitemporal image analysis methodologies for monitoring of structures and infrastructures after natural disasters (Italian Space Agency) – [2009-2012]
  • FORLIDAR (phase 2) – Methods for the estimation of forest density and structure from LIDAR and Hyperspectral data [2009-2010]
  • ITPAR (phase 2) – India-Trento Program for Advanced Research – Advanced techniques for remote sensing image processing and recognition – [2008-2010]
  • LIMES – Land and sea integrated monitoring for European security (Integrated Project FP6-2005- European Union) [2006-2010]
  • HYPERKERNEL – Development of advanced semi-supervised kernel methods for classification of hyperspectral remote sensing images (MIUR – Italian Ministry of the Education, Research and University, Integrated Actions Italy-Spain) [2006-2009]
  • FORLIDAR (phase 1) – Methods for forest area classification based on LiDAR and Hyperspectral data fusion [2007-2009]
  • FOREST-PAT – Feasibility study on the application of remote sensing to forest management in the Trentino region (Autonomous Province of Trento, Italy) [2006-2007]
  • ITPAR (phase 1) – India-Trento Program for Advanced Research – Advanced techniques for remote sensing image processing and recognition – [2004-2007]
  • Processing and Analysis of Multitemporal and Hypertemporal Remote Sensing images for Environmental Monitoring (MIUR – Italian Ministry of the Education, Research and University. Prime contractor) [2003-2004]
  • Analysis and classification of hyperspectral remote-sensing images (MIUR – Italian Ministry of the Education, Research and University) [2002-2003]
  • TIDE – Tidal Inlets Dynamics and Environment (European Community project; Programme: Energy, Environment and sustainable Development; Research Priority: Integrated studies on coastal zone changes) [2001-2004]
  • MA_MISS – Automatic techniques for the analysis of hyperspectral images acquired on the Marsis surface (Italian Space Agency) [2001-2003]
  • Development of automatic methodologies for the analysis of data acquired by satellite InFrared sensors [2001-2002]
  • Experimental methodologies for water colours analysis by MERIS data (Italian Space Agency) [2001-2002]
  • Hyperspectral sensors (DAIS 7915, ROSIS) over the Venice Lagoon (DLR – German Remote Sensing Data Center) [2000-2001]
  • Novel methodologies to the integration, management and analysis of remotely-sensed data for monitoring hydrosphere, rain-fall, and soil (Italian Space Agency) [1998-2001]