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Remote Monitoring of Ground Motion Hazards in High Mountain Terrain Using InSAR: A Case Study of the Lake Sarez Area, Tajikistan (2021)
Journal Article
Grebby, S., Sowter, A., Gee, D., Athab, A., De la Barreda-Bautista, B., Girindran, R., & Marsh, S. (2021). Remote Monitoring of Ground Motion Hazards in High Mountain Terrain Using InSAR: A Case Study of the Lake Sarez Area, Tajikistan. Applied Sciences, 11(18), Article 8738. https://doi.org/10.3390/app11188738

High mountain terrains, with steep slopes and deep valleys, are generally challenging areas to monitor using satellite earth observation techniques since the terrain creates perspective distortions and differences in illumination that can occlude or... Read More about Remote Monitoring of Ground Motion Hazards in High Mountain Terrain Using InSAR: A Case Study of the Lake Sarez Area, Tajikistan.

Nanopore Size Distribution Heterogeneity of Organic-Rich Shale Reservoirs Using Multifractal Analysis and Its Influence on Porosity–Permeability Variation (2021)
Journal Article
Yan, G., Qin, Z., Marsh, S., Grebby, S., Mou, Y., Song, L., & Zhang, C. (2021). Nanopore Size Distribution Heterogeneity of Organic-Rich Shale Reservoirs Using Multifractal Analysis and Its Influence on Porosity–Permeability Variation. Energy and Fuels, 35(17), 13700-13711. https://doi.org/10.1021/acs.energyfuels.1c01654

The shale nanopore size (diameter

A machine learning approach to tungsten prospectivity modelling using knowledge-driven feature extraction and model confidence (2020)
Journal Article
Yeomans, C. M., Shail, R. K., Grebby, S., Nykänen, V., Middleton, M., & Lusty, P. A. (2020). A machine learning approach to tungsten prospectivity modelling using knowledge-driven feature extraction and model confidence. Geoscience Frontiers, 11(6), 2067-2081. https://doi.org/10.1016/j.gsf.2020.05.016

Novel mineral prospectivity modelling presented here applies knowledge-driven feature extraction to a data-driven machine learning approach for tungsten mineralisation. The method emphasises the importance of appropriate model evaluation and develops... Read More about A machine learning approach to tungsten prospectivity modelling using knowledge-driven feature extraction and model confidence.

Delineating ground deformation over the Tengiz oil field, Kazakhstan, using the Intermittent SBAS (ISBAS) DInSAR algorithm (2019)
Journal Article
Grebby, S., Orynbassarova, E., Sowter, A., Gee, D., & Athab, A. (2019). Delineating ground deformation over the Tengiz oil field, Kazakhstan, using the Intermittent SBAS (ISBAS) DInSAR algorithm. International Journal of Applied Earth Observation and Geoinformation, 81, 37-46. https://doi.org/10.1016/j.jag.2019.05.001

Changes in subsurface pore pressures and stresses due to the extraction of hydrocarbons often cause deformation over oil and gas fields. This can have significant consequences, including ground subsidence, induced seismicity and well failures. Geodyn... Read More about Delineating ground deformation over the Tengiz oil field, Kazakhstan, using the Intermittent SBAS (ISBAS) DInSAR algorithm.

National geohazards mapping in Europe: interferometric analysis of the Netherlands (2019)
Journal Article
Gee, D., Sowter, A., Grebby, S., de Lange, G., Athab, A., & Marsh, S. (2019). National geohazards mapping in Europe: interferometric analysis of the Netherlands. Engineering Geology, 256, 1-22. https://doi.org/10.1016/j.enggeo.2019.02.020

The launch of Copernicus, the largest Earth Observation program to date, is significant due to the regular, reliable and freely accessible data to support space-based geodetic monitoring of physical phenomena that can result in natural hazards. In th... Read More about National geohazards mapping in Europe: interferometric analysis of the Netherlands.

Integrated Object-Based Image Analysis for semi-automated geological lineament detection in Southwest England (2018)
Journal Article
Yeomans, C. M., Middleton, M., Shail, R. K., Grebby, S., & Lusty, P. A. (2019). Integrated Object-Based Image Analysis for semi-automated geological lineament detection in Southwest England. Computers and Geosciences, 123, 137-148. https://doi.org/10.1016/j.cageo.2018.11.005

Regional lineament detection for mapping of geological structure can provide crucial information for mineral exploration. Manual methods of lineament detection are time consuming, subjective and unreliable. The use of semi-automated methods reduces t... Read More about Integrated Object-Based Image Analysis for semi-automated geological lineament detection in Southwest England.

Rapid prediction of single green coffee bean moisture and lipid content by hyperspectral imaging (2018)
Journal Article
Caporaso, N., Whitworth, M. B., Grebby, S., & Fisk, I. D. (2018). Rapid prediction of single green coffee bean moisture and lipid content by hyperspectral imaging. Journal of Food Engineering, 227, 18-29. https://doi.org/10.1016/j.jfoodeng.2018.01.009

© 2018 The Authors Hyperspectral imaging (1000–2500 nm) was used for rapid prediction of moisture and total lipid content in intact green coffee beans on a single bean basis. Arabica and Robusta samples from several growing locations were scanned usi... Read More about Rapid prediction of single green coffee bean moisture and lipid content by hyperspectral imaging.