Arctic Greening Across Scales

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,, NASA Arctic Boreal Vulnerability Experiment (ABoVE, and the Canadian Airborne Biodiversity Observatory (CABO, 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.

Grant reference
Natural Environment Research Council
Total awarded
£0 GBP
Start date
30 Sep 2020
3 years 8 months 29 days
End date
29 Jun 2024