Filters: Contacts: Prakash, Anupma (X) > partyWithName: Solie, Diana N. (X) > Types: Map Service (X)
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We employed an integrated approach that combined remote sensing techniques with field measurements to predict the presence/absence of near-surface permafrost in a section of the Alaska Highway corridor. We investigated the correlative relationships among vegetation type, topography, moss thickness, tussock condition and near-surface permafrost in the study area. Analysis of moss thickness and active-layer depth in low-lying plains (slope <8?) showed an inverse relationship in different vegetation classes. The maximum likelihood classification of remotely sensed data mapped 80% of the study area as covered with vegetation. We developed an empirical-statistical (Binary Logistic Regression) model to establish the statistical...
Categories: Data,
Publication;
Types: Citation,
Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Modeling,
Monitoring 3-Improve Permafrost Mapping,
and Monitoring
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.; A combination of binary logistic regression (BLR) and remote sensing techniques was used to generate a high-resolution spatially...
Categories: Data,
Publication;
Types: Citation,
Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Modeling,
Monitoring 3-Improve Permafrost Mapping,
and Monitoring
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