Professional summary
Dr Christopher Marston is an Earth Observation specialist with extensive experience of satellite and airborne remote sensing applications for landscape and vegetation characterisation. These are used for a variety of environmental problems and processes.
He has a particular focus on using multi-scale, multi-source satellite datasets with in-situ environmental data for monitoring temporal changes in land cover composition of landscapes at locations throughout Europe, Africa and Asia. In the UK, this includes co-production of the series of UK Land Cover Map products. Internationally, recent applications include epidemiological studies modelling the distribution of the disease transmission vectors of malaria (mosquito) and Echinococcus multilocularis (small mammals) in relation to the presence of key habitat types critical for the life cycle of the transmission vector, mapped using satellite data. This has involved forming international research collaborations, and submitting successful funding bids to support the work from the Global Challenges Research Fund (GCRF) to improve the targeting of disease control activities and reduce human mortality in endemic regions.
In recent years, Christopher has also been involved in a diverse range of African-focused projects. These have included assessing spatio-temporal vegetation changes and woody encroachment and resulting ecological impacts, and modelling elephant selective feeding behaviour in relation to C3/C4 food availability in savannah landscapes in Kruger National Park, South Africa. Additionally, he has conducted pan-African mapping of modern-day mosaic habitats, as an analogous study to improve our understanding of palaeo-environmental reconstructions within the context of hominin (pre-human) evolutionary sites.
Marston, C.G., O'Neil, A.W., Morton, R.D., Wood, C.M., and Rowland, C. S.: (2023) LCM2021 – the UK Land Cover Map 2021, Earth Syst. Sci. Data, 15, 4631–4649.
Marston C.G., Raoul F, Rowland C, Quéré J-P, Feng X, Lin R, et al. (2023) Mapping small mammal optimal habitats using satellite-derived proxy variables and species distribution models. PLoS ONE 18(8): e0289209.
Marston, C.G.; Rowland, C.; O’Neil, A.; Irish, S.; Wat’senga, F.; Martín-Gallego, P.; Aplin, P.; Giraudoux, P.; Strode, C. Developing the Role of Earth Observation in Spatio-Temporal Mosquito Modelling to Identify Malaria Hot-Spots. Remote Sens. 2023, 15, 43.
Marston C.G, Wilkinson DM, Sponheimer M, Codron D, Codron J, O’Regan HJ. 2020. ‘Remote’ behavioural ecology: do megaherbivores consume vegetation in proportion to its presence in the landscape? PeerJ 8:e8622.
Martín-Gallego, P.; Aplin, P.; Marston, C.G., Altamirano, A., and Pauchard, A. (2020) Detecting and modelling alien tree presence using Sentinel-2 satellite imagery in Chile's temperate forests, Forest Ecology and Management, 474, 118353.
Marston, C.G; Giraudoux, P. On the Synergistic Use of Optical and SAR Time-Series Satellite Data for Small Mammal Disease Host Mapping. Remote Sens. 2019, 11, 39.
Marston, C.G., Wilkinson, D.M., Reynolds, S.C. et al. Water availability is a principal driver of large-scale land cover spatial heterogeneity in sub-Saharan savannahs. Landscape Ecol 34, 131–145 (2019).
Marston, C.G.; Aplin, P.; Wilkinson, D.M.; Field, R.; O’Regan, H.J. Scrubbing Up: Multi-Scale Investigation of Woody Encroachment in a Southern African Savannah. Remote Sens. 2017, 9, 419.
Marston, C.G., Giraudoux, P., Armitage, R.P., Danson, F.M., Reynolds, S.C., Wang, Q., et al. (2016) Vegetation phenology and habitat discrimination: Impacts for E. multilocularis transmission host modelling, Remote Sensing of Environment, 176, 320-327.
Marston, C.G., Danson, F.M., Armitage, R.P., Giraudoux, P., Pleydell, D.R.J., Wang, Q., et al. A random forest approach for predicting the presence of Echinococcus multilocularis intermediate host Ochotona spp. presence in relation to landscape characteristics in western China, Applied Geography, 2014, 55, 176-183.