Near-Surface Permafrost Distribution Mapping Using Logistic Regression and Remote Sensing in Interior Alaska

TitleNear-Surface Permafrost Distribution Mapping Using Logistic Regression and Remote Sensing in Interior Alaska
Publication TypeJournal Article
Year of Publication2012
AuthorsPanda, SK, Prakash, A, Jorgenson, M, Solie, D
JournalGIScience & Remote Sensing
Volume49
Pagination346 - 363
Date Published2012/05/01/
Abstract

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.

URLhttp://dx.doi.org/10.2747/1548-1603.49.3.346