Abstract
Lakes are a ubiquitous landscape feature in northern permafrost regions. They have a strong impact on carbon, energy and water fluxes and can be quite responsive to climate change. The monitoring of lake change in northern high latitudes, at a sufficiently accurate spatial and temporal resolution, is crucial for understanding the underlying processes driving lake change. To date, lake change studies in permafrost regions were based on a variety of different sources, image acquisition periods and single snapshots, and localized analysis, which hinders the comparison of different regions. Here, we present a methodology based on machine-learning based classification of robust trends of multi-spectral indices of Landsat data (TM, ETM+, OLI) and object-based lake detection, to analyze and compare the individual, local and regional lake dynamics of four different study sites (Alaska North Slope, Western Alaska, Central Yakutia, Kolyma Lowland) in the northern permafrost zone from 1999 to 2014. Regional patterns of lake area change on the Alaska North Slope (−0.69%), Western Alaska (−2.82%), and Kolyma Lowland (−0.51%) largely include increases due to thermokarst lake expansion, but more dominant lake area losses due to catastrophic lake drainage events. In contrast, Central Yakutia showed a remarkable increase in lake area of 48.48%, likely resulting from warmer and wetter climate conditions over the latter half of the study period. Within all study regions, variability in lake dynamics was associated with differences in permafrost characteristics, landscape position (i.e., upland vs. lowland), and surface geology. With the global availability of Landsat data and a consistent methodology for processing the input data derived from robust trends of multi-spectral indices, we demonstrate a transferability, scalability and consistency of lake change analysis within the northern permafrost region.
Highlights
More than 25% of the lakes on Earth are located in the northern high latitude region [1].The distribution of lakes can primarily be explained by prior glaciation histories, the presence of peatlands, and the presence of ice-rich permafrost [2]
Due to the rapid nature of reported lake and landscape changes occurring in the northern high latitudes, we developed a workflow to analyze Landsat-based trend data with machine-learning classification (MLC) and object-based image analysis (OBIA) for the detection and analysis of lake dynamics in two lake-rich regions in Alaska and two lake rich regions in Siberia spanning a total of
Their study site largely covers the area affected by widespread lake drainage and trends of lake change nicely resemble the spatial pattern we found in our study, e.g., lake growth in the Selawik river delta and widespread loss in the northern Selawik river valley
Summary
More than 25% of the lakes on Earth are located in the northern high latitude region [1].The distribution of lakes can primarily be explained by prior glaciation histories, the presence of peatlands, and the presence of ice-rich permafrost [2]. More than 25% of the lakes on Earth are located in the northern high latitude region [1]. Of the landscape in Arctic lowland regions [3,4]. Grosse et al [3] estimate that more than half of the lakes found in permafrost regions are likely of thermokarst origin; many other lake types in the Arctic are recognized [5,6]. Arctic lakes have developed in a highly dynamic environmental setting that is subject to both hydroclimatic and geomorphic changes [11,12]. With respect to thermokarst lakes, they may undergo several generations that include phases of formation, growth, drainage, and reformation [3,13,14,15].
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
