Remote Sensing and Machine Learning

19 Jun 2020 12:39 PM

There is increasing interest in using machine learning to automatically analyse remote sensing data and increase our understanding of complex environmental systems. While there are benefits from this approach, there are also some barriers to its use. This POSTnote examines the value of these approaches, and the technical and ethical challenges for wider implementation.

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Environmental remote sensing involves the use of satellites and other air-borne instruments to collect data about the environment. Substantial quantities of data are produced in this way and environmental remote sensing is now considered an area of Big Data. Experts are using artificial intelligence (AI) tools such as machine learning for more efficient data analysis of such data.  

Machine learning algorithms allow a system to learn and improve from data and experience without being specifically programmed, reducing the level of human intervention. This data-driven approach means valuable information about a natural phenomenon can be extracted from the data alone. This has benefits such as being able to manage more complex environmental data but has challenges such as data accessibility. 

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Acknowledgements  

POSTnotes are based on literature reviews and interviews with a range of stakeholders and are externally peer reviewed. POST would like to thank interviewees and peer reviewers for kindly giving up their time during the preparation of this briefing, including: 

Alberto Arribas, Met Office 

Heiko Baltzer, University of Leicester 

John Bloomfield, British Geological Survey 

Julie Bremner, University of East Anglia & CEFAS* 

Rene Breton, University of Manchester 

Sue Chadwick, Pinsent Masons LLP* 

Michael Cross, Rezatec* 

Timothy Darlington, Met Office 

Tony Dolphin, CEFAS* 

Joseph Fennell, University of Manchester 

Karen Frake, Natural Scotland* 

Tanvir Islam, NASA Jet Propulsion Laboratory 

Tom Jones, Satellite Applications Catapult 

Gwawr Jones, JNCC* 

Alexandra Kilcoyne, Natural England 

Peter Kohler, CEFAS 

Stefan Leutenegger, Imperial College London 

Paula Lightfoot, JNCC* 

Encarni Medina-Lopez, University of Edinburgh 

Paul Monks, University of Leicester 

Boguslaw Obara, Durham University* 

Rami Qahwaji, University of Bradford 

John Remedios, NCEO and University of Leicester 

Cristian Rossi, Satellite Applications Catapult 

Edward Salakpi, University of Sussex 

Anna Scaife, University of Manchester 

Ivan Tyukin, University of Leicester 

Hong Wei, University of Reading 

Daniel Wicks, Satellite Applications Catapult 

*denotes people and organisations who acted as external reviewers of the briefing. 

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