The Arctic is a hotspot of land-cover and land-use change (LCLUC) due to polar amplification of global warming, thawing permafrost, human activity, and greening/browning of tundra vegetation. Arctic ecosystems are susceptible to disturbances such as energy exploration, fires, and construction, changing the structure, composition, and function of natural plant communities, and causing permafrost degradation. Further, regions in the Arctic are susceptible to infrastructure failure due to relatively high ground-ice content and thick deposits of frost-susceptible sediments, increasing the potential for thaw. Changes in infrastructure and land use related to oil and gas exploration, opening of the Northern Sea Route and the Northwest Passage (roads, new routes, construction codes, pipelines, deepwater ports, settlements), associated environmental impacts, and the human adaptations to climate change are critical research priorities for the Arctic. Our goal in this proposal is to identify land disturbances and societal vulnerabilities associated with expanding the human footprint of oil and gas exploration concomitant to thawing permafrost around two Arctic regions with an extensive history of oil and gas exploration – the Prudhoe Bay in North Slope Borough (NSB), Alaska, and the Yamal Peninsula in Russia.

Microtopography is a defining feature of Arctic landscapes, driving variability in permafrost state and other important ecological processes at the 1-10 m scale. Accurate characterization of Arctic LCLUC will thus require a multiscale approach capable of both the regional spatial extent to capture a regional study area and sensitivity to governing biophysical dynamics that occur well below the scale of Landsat pixels. We thus propose to base our image analysis on an analytic framework explicitly designed to accommodate such “sub-pixel” processes: spectral and temporal mixture models. Understanding the impact of LCLUC in the Arctic will necessarily involve the characterization of change at these scales. Our approach would extend an image analysis methodology that has been shown to produce time series of accurate, scalable estimates of sub-pixel processes at both decameter and hectometer resolutions in diverse, challenging environments. Here, we will leverage satellite and airborne imagery spanning two orders of magnitude in spatial and spectral resolution to track anthropogenic Arctic LCLUC (roads, pipelines, structures). The availability of data from AVIRIS-NG, a rigorously calibrated airborne Imaging Spectrometer, in the NSB study area allows us to significantly extend our multispectral analysis, establishing a baseline and set of best practices for the integration of future global IS datasets into the LCLUC program’s framework and potentially becoming an early example of the power of the next generation of land imaging to quantify LCLUC dynamics in hotspots of global significance.

Along with the remote-sensing based time-series analysis, our research will identify vulnerabilities of communities in the NSB due to LCLUC. Communities already impacted by climate change may see further vulnerabilities arise from infrastructure expansion. Previous research in the Yamal Peninsula has shown that the indigenous Nenet communities in Yamal have been resilient to land-use changes from increasing oil and gas fields in the region. However, the ongoing development of oil reserves requires constant adaptation and puts communities at risk. To evaluate human impacts in the NSB region, we will utilize a framework to assess vulnerability based on previous research at Yamal, adapted for Northern Alaska. Resource development and oil and gas exploration are also part of plans in NSB, specifically in the National Petroleum Reserve-Alaska. The parallel nature of this proposed research to previous work in Yamal will help understand the drivers of vulnerability in both study regions and differences in vulnerability and exposure for communities to LCLUC.