Skip to main content

Quantitative mapping of eskers using DEM and multispectral data

Eskers have commonly been mapped and symbolized manually from aerial photographic interpretation as either lines (ridges) and polygons (sand and gravel). To-date no method has been deployed that could automatically extract esker extents and quantify the esker volume. A methodology is
presented for the quantification of eskers that uses Canadian Digital Elevation Data (CDED), spectral remotely sensed imagery (e.g. LandSat, Spot), and legacy esker line work from Geological Survey of Canada publications. Using ArcGIS and an esker detection module (EDM) coded in Python, the CDED
data are smoothed using user defined filter windows. A difference surface is produced that emphasizes ridge areas and is used to create polygons. The legacy esker line work is used as a training dataset to extract ridge areas within a user defined buffer. EDM results have been tested against the
input training data and a local data set generated manually from aerial photographic interpretation. Depending upon terrain characteristics the success of the data extraction ranges from 65 to 81 % against the esker line work and 35 to 72 % against the more limited aerial photographic
interpretation. The variable success reflects esker size related to both relief and width in the CDED data. Ongoing development of this methodology focuses on enhanced delineation of low-relief areas of the esker not captured by the DEM analysis through incorporation of spectral imagery. A
multiclass (80-90) iso-cluster unsupervised classification of SPOT MSS data was completed to characterize the landscape. The isocluster classification is then overlain on the esker polygons. The most dominant classes in terms of area are identified and the user can specify the number of classes to
be chosen. The originally topographically defined polygons are then merged with the selected intersecting spectral classification.

In progress
Project URL
Start Date
End Date

The Great Lakes - St. Lawrence Research Inventory is an
interactive, Internet-based, searchable database created as a tool to collect and disseminate
up-to-date information about research projects in the
Great Lakes - St. Lawrence Region.