TY  - JOUR
A1  - Jones, Benjamin M.
A1  - Arp, Christopher D.
A1  - Whitman, Matthew S.
A1  - Nigro, Debora
A1  - Nitze, Ingmar
A1  - Beaver, John
A1  - Gadeke, Anne
A1  - Zuck, Callie
A1  - Liljedahl, Anna
A1  - Daanen, Ronald
A1  - Torvinen, Eric
A1  - Fritz, Stacey
A1  - Grosse, Guido
T1  - A lake-centric geospatial database to guide research and inform management decisions in an Arctic watershed in northern Alaska experiencing climate and land-use changes
JF  - AMBIO
N2  - Lakes are dominant and diverse landscape features in the Arctic, but conventional land cover classification schemes typically map them as a single uniform class. Here, we present a detailed lake-centric geospatial database for an Arctic watershed in northern Alaska. We developed a GIS dataset consisting of 4362 lakes that provides information on lake morphometry, hydrologic connectivity, surface area dynamics, surrounding terrestrial ecotypes, and other important conditions describing Arctic lakes. Analyzing the geospatial database relative to fish and bird survey data shows relations to lake depth and hydrologic connectivity, which are being used to guide research and aid in the management of aquatic resources in the National Petroleum Reserve in Alaska. Further development of similar geospatial databases is needed to better understand and plan for the impacts of ongoing climate and land-use changes occurring across lake-rich landscapes in the Arctic.
KW  - Arctic
KW  - Climate Change
KW  - GIS
KW  - Lakes
KW  - Land-use change
KW  - Watershed
Y1  - 2017
U6  - https://doi.org/10.1007/s13280-017-0915-9
SN  - 0044-7447
SN  - 1654-7209
VL  - 46
SP  - 769
EP  - 786
PB  - Springer
CY  - Dordrecht
ER  - 
TY  - JOUR
A1  - Nitze, Ingmar
A1  - Grosse, Guido
A1  - Jones, Benjamin M.
A1  - Arp, Christopher D.
A1  - Ulrich, Mathias
A1  - Fedorov, Alexander
A1  - Veremeeva, Alexandra
T1  - Landsat-Based Trend Analysis of Lake Dynamics across Northern Permafrost Regions
JF  - Remote sensing
N2  - 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.
KW  - lake dynamics
KW  - lake change
KW  - permafrost region
KW  - Landsat
KW  - Alaska
KW  - Siberia
KW  - thermokarst
KW  - trend analysis
KW  - machine-learning
Y1  - 2017
U6  - https://doi.org/10.3390/rs9070640
SN  - 2072-4292
VL  - 9
PB  - MDPI
CY  - Basel
ER  -