
Dr Peter Miller
Marine Earth Observation Scientist
pim @pml.ac.uk | +44 (0)1752 633100 (switchboard)"I am motivated by the challenge of applying my innovations to achieve impact in conservation and industry, and particularly enjoy this when my work crosses disciplines, for example physical oceanography, computer vision and marine ecology. I am proud that my research on ocean fronts has informed the designation of several marine protected areas around the UK and beyond, and that our satellite algorithms help to warn salmon farmers about harmful algal blooms."
Peter has over 25 years’ experience and 90 published papers (H-index of 32) in developing innovations for automated analysis of sea-surface biological and physical processes using satellite data. He leads research on ocean fronts, their impact upon animal behaviour and potential modulation by climate change. His harmful algal bloom (HAB) detection research has been tested in many European and UK funded projects for monitoring water quality for protecting aquaculture and human health. He generates impact in policy implementation, conservation and the aquaculture industry, with a focus on international collaboration and commercialisation. Peter draws upon his background in computer science and PhD in medical image analysis.
- PML (ed.) 2019. Satellite derived ocean front maps inform the designation of national and international areas for marine protection. A compilation of site selection documents, or other appropriate evidence, as corroboration of the impact of PML research in the MPA planning process.
- Miller, P.I., Scales, K.L., Ingram, S.N., Southall, E.J. & Sims, D.W. (2015) Basking sharks and oceanographic fronts: quantifying associations in the north-east Atlantic. Functional Ecology, 29(8), 1099-1109.
- Miller, P.I. & Christodoulou, S. (2014) Frequent locations of ocean fronts as an indicator of pelagic diversity: application to marine protected areas and renewables. Marine Policy, 45, 318–329.
- Miller, P.I. (2009) Composite front maps for improved visibility of dynamic sea-surface features on cloudy SeaWiFS and AVHRR data. Journal of Marine Systems, 78(3), 327-336.
- Scales, K.L., Miller, P.I., Hawkes, L.A., Ingram, S.N., Sims, D.W. & Votier, S.C. (2014) On the Front Line: frontal zones as priority at-sea conservation areas for mobile marine vertebrates. Journal of Applied Ecology, 51(6), 1575-1583.
- Queiroz, N., Humphries, N.E., Mucientes, G., Hammerschlag, N., Lima, F., Scales, K., Miller, P.I., Sousa, L.L., Seabra, R. & Sims, D.W. (2016). Ocean-wide tracking of pelagic sharks reveals extent of overlap with longline fishing hotspots. Proceedings of the National Academy of Sciences of USA, 113(6), 1582-1587.
- Kurekin, A.A., Miller, P.I., Van der Woerd, H.J. (2014). Satellite discrimination of Karenia mikimotoi and Phaeocystis harmful algal blooms in European coastal waters: Merged classification of ocean colour data. Harmful Algae, 31, 163-176.
Recent publications
- Cayetano, CB; Creencia, LA; Sullivan, E; Clewley, D; Miller, PI; 2023. Multi-spatiotemporal analysis of changes in mangrove forests in Palawan, Philippines: predicting future trends using a support vector machine algorithm and the Markov chain model. UCL Open Environment.
- Kurekin, A; Miller, PI; Avillanosa, AL; Sumeldan, JDC; 2022. Monitoring of Coastal Aquaculture Sites in the Philippines through Automated Time Series Analysis of Sentinel-1 SAR Images. Remote Sensing.
- Williamson, LD; Scott, BE; Laxton, M; Illian, JB; Todd, VLG; Miller, PI; Brookes, KL; 2022. Comparing distribution of harbour porpoise using generalized additive models and hierarchical Bayesian models with integrated nested laplace approximation. Ecological Modelling.
- Huthnance, JM; Hopkins, J; Berx, B; Dale, A; Holt, J; Hosegood, P; Inall, M; Jones, S; Loveday, BR; Miller, PI; Polton, J; Porter, M; Spingys, C; 2022. Ocean shelf exchange, NW European shelf seas: Measurements, estimates and comparisons. Progress in Oceanography.
- Lin, J; Miller, PI; Jonsson, B; Bedington, M; 2021. Early Warning of Harmful Algal Bloom Risk Using Satellite Ocean Color and Lagrangian Particle Trajectories. Frontiers in Marine Science.