Dr. Stephen Grebby holds an MPhys (2005) in Physics with Space Science and Technology, an MSc (2006) in Physical Geography and PhD (2011) in Geological Remote Sensing from the University of Leicester. In 2011, he joined the British Geological Survey, where he took up a position as a Remote Sensing Geoscientist. In 2016, Dr. Grebby was appointed as Assistant Professor in Earth Observation, in the Faculty of Engineering. He is affiliated with the GeoEnergy Research Centre (GERC) - a joint venture between The University of Nottingham and British Geology Survey.
Dr. Grebby is a member of the Nottingham Geospatial Institute research group.
Dr. Grebby's expertise is in the acquisition, analysis, investigation and visualisation of Earth Observation data for a wide variety of geoscience applications. Whilst broad-ranging, he has considerable experience in the development of innovative remote sensing techniques for application to geological mapping, natural resources exploration, mapping and monitoring of geohazards, and land use/land cover mapping. He has expertise in utilising a wide variety of Earth Observation datasets and techniques, including InSAR, airborne and terrestrial LiDAR, multi- and hyperspectral imagery, airborne radiometric and geophysical data, field spectroscopy, photogrammetry, geomorphometry, and advanced image classification (i.e., neural networks and other machine learning algorithms).
Dr. Grebby's current research interests are focused on the use of satellite, airborne (manned and UAV) and ground-based Earth Observation techniques for the exploration of geoenergy resources and the… read more
SOWTER, ANDREW, ATHAB, AHMED, NOVELLINO, ALESSANDRO, GREBBY, STEPHEN and GEE, DAVID, 2017. Supporting energy regulation by monitoring land motion on a regional and national scale: A case study of Scotland JOURNAL OF POWER AND ENERGY. GEE, DAVID, BATESON, LUKE, SOWTER, ANDREW, GREBBY, STEPHEN, NOVELLINO, ALESSANDRO, CIGNA, FRANCESCA, MARSH, STUART, BANTON, CARL and WYATT, LEE, 2017. Ground motion in areas of abandoned mining:
application of the Intermittent SBAS (ISBAS) to the
Northumberland and Durham Coalfield, UK GEOSCIENCES. 7 (3), 85
KIRKWOOD, CHARLIE, CAVE, MARK, BEAMISH, DAVID, GREBBY, STEPHEN and FERREIRA, ANTONIO, 2016. A machine learning approach to geochemical mapping. JOURNAL OF GEOCHEMICAL EXPLORATION. 167, 49-61
Dr. Grebby's current research interests are focused on the use of satellite, airborne (manned and UAV) and ground-based Earth Observation techniques for the exploration of geoenergy resources and the monitoring of their exploitation. This includes identifying potential geothermal energy resources by mapping anomalous mineral assemblages and surface temperatures, determining key characteristics (e.g., porosity, permeability, fracture density) for reservoir modelling, and monitoring leakages and ground motion at sites associated with gas storage (i.e., CO2) and energy production.
He also has a strong interest in the mapping and monitoring of geohazards, in particular landslides. His research concerns the development of algorithms to aid the rapid identification and mapping of landslides using airborne LiDAR and optical imagery. Such methods enables comprehensive landslide inventories to be generated, which can then be used to assess the future risk posed by landslides. Dr. Grebby was recently involved in building landslide inventories from very-high resolution satellite imagery, in order to help support the relief efforts following the 2015 Nepal and 2016 Ecuador earthquakes.