Remote sensing-based permafrost region disturbances: fire, 1999-2015, Alaska (US)

The data quantify the abundance and distribution of the permafrost region disturbance (PRD) wildfire, using trend analyses of 30-m-resolution Landsat imagery from 1999-2015 and auxiliary datasets. The dataset spans four continental-scale transects in North America (Alaska, Eastern Canada) and Eurasia (Western Siberia, Eastern Siberia), covering 2.3M km² or ~10% of the permafrost region. This data publication contains geospatial vector files (polygons) of the perimeters of PRD.

Detailed information about the dataset can be found in the data documentation.

Data and Resources

Additional Info

Field Value
Identifier DOI:10.1594/PANGAEA.894755
Project(s) ESA GlobPermafrost, ERC PETA-CARB
Institute AWI Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research
Source https://doi.pangaea.de/10.1594/PANGAEA.894755
Publication Date 2018-12-21
Version 1.0
Product Permafrost Region Disturbance
Sensor Landsat
Files
  1. polygon shapefile of permafrost regions disturbance (PRD) type wildfire
Variables [Units]
  1. Object ID
  2. Area in m² [m²]
  3. Area in km² [km²]
Region Alaska
Spatial Reference EPSG:4326 WGS 84
Spatial Resolution 30 m
Spatial Coverage Latitude 59.55 to 69.48, Longitude -164.96 to -137.49
Temporal Coverage 1999 to 2015
Temporal Resolution
Format Shapefile
Is Supplement To

Nitze, I et al. (2018): Remote sensing quantifies widespread abundance of permafrost region disturbances across the Arctic and Subarctic. Nature Communications, 9(1), https://doi.org/10.1038/s41467-018-07663-3
Related to

Nitze, Ingmar; Grosse, Guido; Jones, Benjamin M; Romanovsky, Vladimir E; Boike, Julia (2018): Remote sensing quantifies widespread abundance of permafrost region disturbances across the Arctic and Subarctic, Fire dataset. PANGAEA, https://doi.org/10.1594/PANGAEA.894753, In supplement to: Nitze, I et al. (2018): Remote sensing quantifies widespread abundance of permafrost region disturbances across the Arctic and Subarctic. Nature Communications, 9(1), https://doi.org/10.1038/s41467-018-07663-3

Dataset extent