LIST ERIN department

CORE BUSINESS

The Environmental Research and Innovation (ERIN) department is active in the use of Earth Observation (EO) data for environmental management, precision agriculture, maritime surveillance and risk management applications. The focus of the research in remote sensing is geared towards a better use of EO data in operational water resources and ecosystem management tools and to integrate remote sensing data (satellite, airborne and ground) together with global navigation satellite systems for near real-time eco-hydrological, hydraulic, and crop growth modelling. These activities are supported by computer scientists active in data analytics, statistics, interactive 2D/3D visualization and data management. ERIN is also active in studying how satellite networks will be integrated in future 5G-IoT (Internet of Things) systems, enabling efficient crisis management, and environmental monitoring.

PRODUCTS & SERVICES

  • Development of retrieval algorithms for biochemical and structural parameters from vegetation and soils, as well as for extracting hydrology-related variables such as evapotranspiration, soil moisture and flooded areas from EO data
  • Integration of satellite, airborne and in-situ remote sensing data together with global navigation satellite systems and telecommunication for developing space-based environmental, agricultural and risk management applications
  • Service activities for surveys, environmental monitoring, civil security using the thermal hyperspectral airborne platform and drones
  • Maritime traffic monitoring based on the integration of Synthetic Aperture Radar and AIS data.
  • High-dimension data analytics and visualisation
  • Geospatial software technologies and platforms for web based data integration
  • Training

TECHNICAL MEANS

  • Thermal hyperspectral airborne platform, including a lightweight and compact imaging radiometric spectrometer (Hyper-Cam-LW built by Telops), a stabilisation platform, an Image Motion Compensator mirror, a GPS/INS unit, and a visible boresighted camera
  • Airborne imaging spectrometer for simultaneous acquisition of VNIR and SWIR data (400-2500 nm), an ASD FieldSpec3 non-imaging spectrometer, a LI-COR LAI-2000 Plant Canopy Analyzer and a Minolta SPAD 502 DL Portable Chlorophyll Meter for Leaf Area Index (LAI) and chlorophyll reference measurements in the canopy
  • UAV platform: DJI multicopter platform equipped with hyperspectral, LIDAR and thermal sensors
  • HPC infrastructure for advanced computation and visualization wall
  • IoT-satellite integrated testbed

MAIN CUSTOMERS

ESA, CNES, Ministry of Environment, Water Agency, Civil security, Ministry of Agriculture, Luxspace, HITEC Luxembourg, Terrasphere, Aerovision BV, Aurea Imaging, Capgemini, VITO, TELOPS-Canada, University of Leuven, TU Vienna, University of Bristol, space4environment, adwaïsEO, SES, EarthLab, Cybercultus, Kleos, Blue Horizon, Hydrosat, World Bank, ISARDSAT, CIMA Research Foundation, Earth Observation Data Centre, Wageningen University, ISRIC World Soil Information Center, University of Münster, JPL, NASA AMES Research Centre, European Space Operations Centre, Agroptimize

MAJOR SPACE PROJECTS

LANDCOVER CCI – Global land cover map development for climate modelling applications

SOC3D – 3D soil organic carbon monitoring using VNIR reflectance spectroscopic techniques

PLANTSENS – Detection of plant stress using advanced thermal and spectral remote sensing techniques for improved crop management.

TOPBOX – Time series analysis of PROBA-V vegetation data toolbox

M2MSAT – Light-weight application and transport protocol for future

M2M application

YPANEMA - Mapping of crop nitrogen status from Sentinel-2 images through inversion of a canopy reflectance model

SKUA – Vessel monitoring and kinematic modelling based on satellite Earth Observation and ground measurements

SENSECO - Optical synergies for spatiotemporal sensing of Scalable ecophysiological traits

CASCADE - Combining earth observation with a large scale model cascade for assessing flood hazard at high spatial resolution

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