EGU22-6853
https://doi.org/10.5194/egusphere-egu22-6853
EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Quantifying glacier area changes using object-based image analysis in Google Earth Engine

Asim Ali1, Paul Dunlop1, Sonya Coleman2, Dermot Kerr2, Robert W McNabb1, and Riko Noormets3
Asim Ali et al.
  • 1School of Geography and Environmental Sciences, Ulster university, United Kingdom of Great Britain – Northern Ireland
  • 2School of Computing, Engineering, and Intelligent Systems, Ulster university, United Kingdom of Great Britain – Northern Ireland
  • 3Department of Arctic Geology, University Centre in Svalbard

Glaciers are an important component of the cryosphere and are key indicators of climate change. Observations of temporal changes in glacier extent are essential for understanding the impacts of climate change, but these observations are not widely available in many parts of the world. Research indicates that climate change has had a significant impact on glacier recession, particularly in the Arctic, where glacier meltwater is an important contributor to global sea-level rise. Therefore, it is important to accurately quantify glacier recession within this sensitive region. In this study, we mapped 480 glaciers in Russian Arctic, Novaya Zemlya, using object-based image analysis (OBIA) applied to multispectral Landsat satellite imagery in Google Earth Engine (GEE) to quantify the area changes between 1986-89 to 2019-21.  Our results confirm that in 1986-89, the total glacierized area was 22958.98 km2 and by 2019-21 there was an 5.56% reduction in glacier area to 21680.63 km2.  Comparison between manually corrected glacier outlines taken from the Randolph Glacier Inventory (RGI) and the mapped glacier outlines derived using the OBIA method shows there is a 90.26% similarity between both datasets. This confirms that OBIA, combined with the GEE platform, is a promising method for accurately mapping glaciers, reduces the time required for manual correction, and can be applied in other glacierized regions for rapid assessment of glacier change.

How to cite: Ali, A., Dunlop, P., Coleman, S., Kerr, D., W McNabb, R., and Noormets, R.: Quantifying glacier area changes using object-based image analysis in Google Earth Engine, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6853, https://doi.org/10.5194/egusphere-egu22-6853, 2022.