Journal
GISCIENCE & REMOTE SENSING
Volume 49, Issue 3, Pages 346-363Publisher
BELLWETHER PUBL LTD
DOI: 10.2747/1548-1603.49.3.346
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Funding
- Alaska Division of Geologic and Geophysical Surveys (ADGGS)
- Alaska Space Grant Program (ASGP)
- Center for Global Change and Arctic System Research
- Office of Polar Programs (OPP)
- Directorate For Geosciences [1023623] Funding Source: National Science Foundation
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A combination of binary logistic regression (BLR) and remote sensing techniques was used to generate a high-resolution spatially continuous near-surface (< 1.6 m) permafrost map. The BLR model was used to establish the relationship between vegetation type, aspect-slope, and permafrost presence; it predicted permafrost presence with an accuracy of 88%. Near-surface permafrost occupies 45% of the total vegetated area and 37% of the total study area. As less than 50% of the study area is underlain by near-surface permafrost, this distribution is characterized as sporadic for the study area.
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