Detection of landscape dynamics in the Arctic Lena Delta with temporally dense Landsat time-series stacks.

dc.contributor.authorNitze, Ingmar
dc.contributor.authorGrosse, Guido
dc.coverage.spatialMEDIAN LATITUDE: 72.950000 * MEDIAN LONGITUDE: 126.550000 * SOUTH-BOUND LATITUDE: 72.000000 * WEST-BOUND LONGITUDE: 123.600000 * NORTH-BOUND LATITUDE: 73.900000 * EAST-BOUND LONGITUDE: 129.500000
dc.date.accessioned2019-11-12T12:28:53Z
dc.date.available2019-11-12T12:28:53Z
dc.date.issued2016-03-21
dc.description.abstractArctic permafrost landscapes are among the most vulnerable and dynamic landscapes globally, but due to their extent and remoteness most of the landscape changes remain unnoticed. In order to detect disturbances in these areas we developed an automated processing chain for the calculation and analysis of robust trends of key land surface indicators based on the full record of available Landsat TM, ETM +, and OLI data. The methodology was applied to the ~ 29,000 km**2 Lena Delta in Northeast Siberia, where robust trend parameters (slope, confidence intervals of the slope, and intercept) were calculated for Tasseled Cap Greenness, Wetness and Brightness, NDVI, and NDWI, and NDMI based on 204 Landsat scenes for the observation period between 1999 and 2014. The resulting datasets revealed regional greening trends within the Lena Delta with several localized hot-spots of change, particularly in the vicinity of the main river channels. With a 30-m spatial resolution various permafrost-thaw related processes and disturbances, such as thermokarst lake expansion and drainage, fluvial erosion, and coastal changes were detected within the Lena Delta region, many of which have not been noticed or described before. Such hotspots of permafrost change exhibit significantly different trend parameters compared to non-disturbed areas. The processed dataset, which is made freely available through the data archive PANGAEA, will be a useful resource for further process specific analysis by researchers and land managers. With the high level of automation and the use of the freely available Landsat archive data, the workflow is scalable and transferrable to other regions, which should enable the comparison of land surface changes in different permafrost affected regions and help to understand and quantify permafrost landscape dynamics.
dc.formattext/tab-separated-values, 24 data points
dc.identifierhttps://doi.pangaea.de/10.1594/PANGAEA.854640
dc.identifierhttps://doi.org/10.1594/PANGAEA.854640
dc.identifier.citationNitze, Ingmar; Grosse, Guido (2016): Detection of landscape dynamics in the Arctic Lena Delta with temporally dense Landsat time-series stacks. Remote Sensing of Environment, 181, 27-41, https://doi.org/10.1016/j.rse.2016.03.038
dc.identifier.urihttps://repository.geologyscience.ru/handle/123456789/6500
dc.language.isoen
dc.publisherPANGAEA
dc.rightsCC-BY-3.0: Creative Commons Attribution 3.0 Unported
dc.rightsAccess constraints: unrestricted
dc.sourceSupplement to: Nitze, Ingmar; Grosse, Guido (2016): Detection of landscape dynamics in the Arctic Lena Delta with temporally dense Landsat time-series stacks. Remote Sensing of Environment, 181, 27-41, https://doi.org/10.1016/j.rse.2016.03.038
dc.subjectFile content
dc.subjectFile size
dc.subjectLenaDelta
dc.subjectLena Delta, Siberia, Russia
dc.subjectPETA-CARB
dc.subjectRapid Permafrost Thaw in a Warming Arctic and Impacts on the Soil Organic Carbon Pool
dc.subjectTheil-Sen regression algorithm
dc.subjectUniform resource locator/link to file
dc.titleDetection of landscape dynamics in the Arctic Lena Delta with temporally dense Landsat time-series stacks.
dc.title.alternativeRobust trends of landscape dynamics in the Arctic Lena Delta with temporally dense Landsat time-series stacks, with links to GeoTIFFs
dc.typeDataset

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