Using GIS to Map the Distribution of Peoria Loess on the Green Bay
Lobe Glacial Surface in South-Central Wisconsin
Carlene Polk & Peter Jacobs (mentor), Geography and Geology.
• Loess is windblown dust that was transported from distant barren land-surfaces.
• Peoria Loess is the term applied to a recognizable deposit of dust that covers much of the mid-continent, from Colorado to Ohio and down the Mississippi Riv
• Loess is a paleoenvironmental indicator and an important sediment in which soils have formed because the physical and mineralogical properties of loess im
• The Green Bay Lobe (GBL) is the name applied to the glacial lobe that affected south central Wisconsin.
• Loess has long been recognized on the GBL surface, but the chronology, source, and distribution are not well understood.
Glacial Boundary
Sand Dunes
Loess >100cm
Loess >50cm and <100cm
Loess <50cm
Thick loess in south central Nebraska. Peoria
Loess is above dark band. Note person for scale.
Analyzing The Map
• Regional thinning pattern is to the E and SE of the Central WI
Sand Plain.
90 cm
Source: U.S. Geological Survey
Typical thin loess mantle in south central Wisconsin. Peoria Loess mantles
stony glacial sediment below.
Producing The Map
• Maps were created from digital soil survey data (SSURGO) for each county.
• Soil series descriptions were evaluated for occurrence and thickness of a
loess mantle.
• Sharp boundaries with sandy soils and dunes in Columbia
and counties to NW indicates sand mobilized dust and
provided a local source of dust.
• Loess thickness in Jefferson Co. appears to have been under
recorded by soil surveyors (see poster of Degen).
• Thick loess on the Rock Prairie and outwash fans in front of
Lake MI Lobe indicates there surfaces stabilized because
new drainage routes for glacial melt water must have
established quickly.
• Soil series were grouped into three classes of loess thickness: <50 cm, 50100 cm, and >100 cm.
• Each thickness layer for a county was exported and joined to the regional
map to interpret source and distribution.
• The GIS tools that were utilized for this map were; layering, categorizing,
extract, overlay, projections and transformations, exporting, clipping,
querying, and union.
We wish to acknowledge support for this research
from the Provost’s Summer Research Scholars
program, the UWW Undergraduate Research
Program, and Dr. Tom Jeffery for GIS help.