The Geometry of Large Tundra Lakes Observed in Historical Maps and Satellite Images
Ivan Sudakov, Almabrok Essa, Luke Mander, Ming Gong, Tharanga, Kariyawasam

TL;DR
This study analyzes the geometry and size changes of large tundra lakes in the Russian High Arctic using historical maps and satellite images, revealing bifurcation in fractal dimensions and variable lake size dynamics over 39 years.
Contribution
It introduces an image-processing algorithm for measuring tundra lake geometry and compares historical and satellite data to analyze geometric patterns and temporal size changes.
Findings
Fractal dimension bifurcation occurs at lakes larger than 100 km².
Lakes with fractal dimension near 2 tend to be self-similar.
Lake sizes have increased or decreased over 39 years, with changes up to half the original size.
Abstract
Tundra lakes are key components of the Arctic climate system because they represent a source of methane to the atmosphere. In this paper, we aim to analyze the geometry of the patterns formed by large ( km) tundra lakes in the Russian High Arctic. We have studied images of tundra lakes in historical maps from the State Hydrological Institute, Russia (date 1977; scale km/pixel) and in Landsat satellite images derived from the Google Earth Engine (G.E.E.; date 2016; scale km/pixel). The G.E.E. is a cloud-based platform for planetary-scale geospatial analysis on over four decades of Landsat data. We developed an image-processing algorithm to segment these maps and images, measure the area and perimeter of each lake, and compute the fractal dimension of the lakes in the images we have studied. Our results indicate that as lake size increases, their fractal…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
