Greening of the Arctic: Comparison of trends in measured soil-surface and air temperature data to satellite-based trends of vegetation change on the Alaskan North Slope (1995-2016)
Presentation Type
Poster Presentation
Abstract/Artist Statement
This study compares 20 years’ worth of in-situ soil-surface and air temperature data to trends in vegetation change along the Alaskan North Slope. The National Science Foundation’s Circumpolar Active Layer Monitoring (CALM) Project has been monitoring 1-hectare plots along a latitudinal gradient in northern Alaska since 1995, and time series of soil-surface and air temperatures are available from 1995-2016. These time series reveal a small increasing trend in mean summer (July-August) air temperatures, yet a small decreasing trend in mean summer soilsurface temperatures. This study uses the cloud-based Google Earth Engine and its 30 m Landsat imagery archive to remotely investigate changes in vegetation over time by examining the Normalized Difference Vegetation Index (NDVI) as well as visual changes in vegetation cover. These differences are then compared to similar trends calculated using the 8 km AVHRRbased GIMMS NDVI 3g dataset which had significant manipulation to account for sensor changes and drift. This study contributes to our understanding of feedback processes between a warming climate and increased vegetation growth.
Greening of the Arctic: Comparison of trends in measured soil-surface and air temperature data to satellite-based trends of vegetation change on the Alaskan North Slope (1995-2016)
UC Ballroom (Center)
This study compares 20 years’ worth of in-situ soil-surface and air temperature data to trends in vegetation change along the Alaskan North Slope. The National Science Foundation’s Circumpolar Active Layer Monitoring (CALM) Project has been monitoring 1-hectare plots along a latitudinal gradient in northern Alaska since 1995, and time series of soil-surface and air temperatures are available from 1995-2016. These time series reveal a small increasing trend in mean summer (July-August) air temperatures, yet a small decreasing trend in mean summer soilsurface temperatures. This study uses the cloud-based Google Earth Engine and its 30 m Landsat imagery archive to remotely investigate changes in vegetation over time by examining the Normalized Difference Vegetation Index (NDVI) as well as visual changes in vegetation cover. These differences are then compared to similar trends calculated using the 8 km AVHRRbased GIMMS NDVI 3g dataset which had significant manipulation to account for sensor changes and drift. This study contributes to our understanding of feedback processes between a warming climate and increased vegetation growth.