Detection of soil erosion within pinyon-juniper woodlands using Thematic Mapper (TM) data

Journal Article · Wed Sep 01 04:00:00 EDT 1993 · Remote Sensing of Environment; (United States)

DOI:https://doi.org/10.1016/0034-4257(93)90107-9· OSTI ID:5983873

Price, K P ^[1]

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1. Univ. of Kansas, Lawrence, KS (United States). Dept. of Geography

Multispectral measurements collected by Landsat Thematic Mapper (TM) were correlated with field measurements, direct soil loss estimates, and Universal Soil Loss Equation (USLE) estimates to determine the sensitivity of TM data to varying degrees of soil erosion in pinyon-juniper woodland in central Utah. TM data were also evaluated as a predictor of the USLE Crop Management C factor for pinyon-juniper woodlands. Correlation analysis showed that TM Band 4 (near infrared) accounted for 78% of the variability in percent trees (r=[minus] 0.88). In multiple regression, percent trees, total soil loss, and percent total nonliving cover together accounted for nearly 70% of the variability in TM Bands 2, 3, 4, and 5. TM spectral data were consistently better predictors of soil erosion factors than any combination of field factors. TM data were more sensitive to vegetation variations than the USLE C factor. USLE estimates showed low annual rates of erosion which varied little among the study sites. A number of hypotheses have been advanced to explain the apparent accelerated rate of pinyon-juniper spread in the western United States. These include removal of natural plant competition by livestock overgrazing, reduction of wildfires, climatic change, and reinvasion of sites cleared of trees by 19th century settlers.

• OSTI ID: 5983873
• Journal Information: Remote Sensing of Environment; (United States), Journal Name: Remote Sensing of Environment; (United States) Vol. 45:3; ISSN RSEEA7; ISSN 0034-4257
• Country of Publication: United States
• Language: English

Related Subjects

54 ENVIRONMENTAL SCIENCES
540210* -- Environment
Terrestrial-- Basic Studies-- (1990-)
CLIMATIC CHANGE
EROSION
FORECASTING
FORESTS
LANDSAT SATELLITES
REMOTE SENSING
SATELLITES
SOILS