- 2018–Present: PhD Researcher, NERC QMEE DTP, Institute of Zoology and University of Reading
- 2017–2018 Remote Sensing Technician, Institute of Zoology
- 2014–2017: MSc in Geography, Freie Universität Berlin
- 2005–2008: BSc in Geography, Durham University
ResearchGate Merry Crowson
I am interested in environmental and biodiversity monitoring to inform policy and decision making. I focus on the use of big data and machine learning within monitoring efforts.
Current Research Capitalising on the Big Data era: establishing a multi-source monitoring framework for England's natural capital assets and flows
From satellite remote sensing to camera traps and observations crowd-sourced from amateur naturalists, recent technological advances have revolutionised our ability to monitor biodiversity and are now providing biologists with a lot of new information. In addition, developments in open source platforms and automated data processes are allowing vast amount of data to be analysed in relatively short time frames. Theoretical work on the valuation of nature has also progressed rapidly over the past decade, which has led to a broad adoption of the natural capital approach by businesses and policy makers. These developments make it possible to assess and report on natural capital assets and flows on an annual basis to national bodies, providing that the various sources of information available can be brought together and synthetized efficiently. So far, however, this idea hasn’t been tested at large spatial scales. To fill this gap in knowledge, this project aims to demonstrate how large and diverse biodiversity datasets could be effectively combined to regularly assess the distribution and quality of natural capital assets and flows. The project will focus on England, taking adventage of the unprecedented biodiversity data that is available.
Crowson, M., Hagensieker, R. & Waske, B., 2019. Mapping land cover change in northern Brazil with limited training data. International Journal of Applied Earth Observation and Geoinformation, 78, pp.202–214. Available at: http://dx.doi.org/10.1016/j.jag.2018.10.004.
Crowson, M. , Warren‐Thomas, E. , Hill, J. K., Hariyadi, B. , Agus, F. , Saad, A. , Hamer, K. C., Hodgson, J. A., Kartika, W. D., Lucey, J. , McClean, C. , Nurida, N. L., Pratiwi, E., Stringer, L. C., Ward, C. and Pettorelli, N. (2019), A comparison of satellite remote sensing data fusion methods to map peat swamp forest loss in Sumatra, Indonesia. Remote Sens Ecol Conserv. doi:10.1002/rse2.102
Nathalie Pettorelli, Institute of Zoology
Andrew Wade, University of Reading
Nick Isaac, CEH
Ken Norris, Institute of Zoology