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Arctic Greening Across Scales (part of the SENSE Centre for Doctoral Training)

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  • Full or part time
    Dr I Myers-Smith
  • Application Deadline
    No more applications being accepted
  • Competition Funded PhD Project (UK Students Only)
    Competition Funded PhD Project (UK Students Only)

Project Description

Background: As the Arctic warms, plants are responding and satellite-measures indicate widespread greening at high latitudes. This “greening of the Arctic” is among the world’s most significant large-scale ecological responses to global climate change1. However, the underlying causes and future dynamics of Arctic greening and browning patterns and trends are complex, variable, and inherently scale dependent. This PhD project will test the correspondence among in situ, drone, plane and satellite datasets in collaboration with the High Latitude Drone Ecology Network (HiLDEN, https://arcticdrones.org/), NASA Arctic Boreal Vulnerability Experiment (ABoVE, https://above.nasa.gov/) and the Canadian Airborne Biodiversity Observatory (CABO, http://www.caboscience.org/) to advance applications of satellite and in situ observations to the study of past, present, and future Arctic vegetation change.

Key Research Questions: The PhD project will explore the drivers of tundra greening and browning patterns and trends by addressing the following research questions:

How do greening patterns and trends vary across scales of observation including data from drones, planes, satellites and on-the-ground ecological monitoring?
How can remotely-sensed estimates of greenness and environmental drivers improve predictions of vegetation change across the tundra biome?
Methods: This interdisciplinary project PhD project combines the fields of ecoinformatics, remote sensing and ecology. The student will have access to existing long-term records of remotely-sensed multispectral, hyperspectral and RGB drone data, NASA collected airborne hyperspectral data, freely-available satellite data, the opportunity to conduct multi-site data synthesis and to establish new field data collection. Satellite datasets include but are not limited to Sentinel, Landsat, MODIS and AVHRR optical data. The student will have significant scope to develop their own research ideas within the research themes.

Training: In addition to the extensive training provided by the SENSE CDT, the student will gain skills in remote sensing, plant ecology, statistical analysis including Bayesian hierarchical modelling, image analysis including structure-for-motion photogrammetry, spatial analysis and training in open science best practice, science communication and field logistics. In addition, the student will develop expertise in the safe operation of drones.

This PhD is part of the NERC and UK Space Agency funded Centre for Doctoral Training "SENSE": the Centre for Satellite Data in Environmental Science. SENSE will train 50 PhD students to tackle cross-disciplinary environmental problems by applying the latest data science techniques to satellite data. All our students will receive extensive training on satellite data and AI/Machine Learning, as well as attending a field course on drones, and residential courses hosted by the Satellite Applications Catapult (Harwell), and ESA (Rome). All students will experience extensive training on professional skills, including spending 3 months on an industry placement. See www.eo-cdt.org

Funding Notes

This 3 year 9 month long NERC SENSE CDT award will provide tuition fees (£4,500 for 2019/20), tax-free stipend at the UK research council rate (£15,009 for 2019/20), and a research training and support grant to support national and international conference travel. www.eo-cdt.org

How good is research at University of Edinburgh in Earth Systems and Environmental Sciences?

FTE Category A staff submitted: 104.98

Research output data provided by the Research Excellence Framework (REF)

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