In young glaciated landscapes the variability of soil materials imparts a m
ajor control on crop growth and yield and environmental quality associated
with production agriculture. Two common soil materials found on these glaci
ated landscapes are glacial till and reworked loess. Soil materials can be
characterized by a combination of physical and morphological soil attribute
s. We hypothesized that penetration resistance is the response signal to a
complex of multiple soil attributes and can be used as an integrating indic
ator to map soil materials. Our objective was to test the ability of a prof
ile cone penetrometer to map soil materials at lands cape-scale. The study
site was located in southern Wisconsin, USA, on soils developed in reworked
loess material overlying glacial till, which are classified as Typic or Mo
llic Hapludalfs and Typic Argiudolls. We collected a dense data set of cone
index profiles from a 2.73 ha. area on a 10 m grid up to depths of 1.3 m.
Additionally, we collected soil cores randomly at 21 penetration locations
and analyzed these by layer for texture, bulk density, and water content. W
e utilized point elevation data collected with a differential global positi
oning system to create a digital elevation model and derive slope and compo
und topographic index to subdivide the study area into landform element cla
sses. We used expert knowledge to characterize soil materials and subsequen
tly measured soil attributes to identify soil materials. A hierarchical clu
ster analysis was used to group cone index profiles. Combining the sparse s
oil material data with the dense cone index and landform element data resul
ted in soil material information covering, the entire study area. The spati
al distribution of soil materials was visualized using a three-dimensional
soil layer model. The proposed method is associated with large uncertaintie
s in some areas and can be recommended only for coarse mapping of contrasti
ng soil materials such as glacial till and reworked loess at landscape-scal
e, when used in combination with landform. element data. (C) 2001 Elsevier
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