ABSTRACT:
Tillage information is crucial in environmental modeling as it has a direct impact on sediment delivery, phosphorus loss, and water holding capacity of agricultural soils. Remote sensing techniques can provide information about tillage practices over large areas. In this study, six Thematic Mapper (TM)-based logistic regression models proposed by van Deventer et al. (1997) were used to distinguish conventional and conservation tillage practices in the Lower Minnesota River watershed located in southern Minnesota. Accuracy assessments of tillage maps derived from Landsat TM data were made using field data collected by the Natural Resources Conservation Service (NRCS). Regression models were easy to use, cost and time effective, and produced reasonably accurate tillage maps. The percentage correct and kappa (k) values varied from 42–77% and 0.03–0.51, respectively, with best values for logistic regression models that use TM band 5 or the difference between TM band 3 and 5 images. This approach is promising for the rapid collection of tillage information on individual fields over large areas.
Footnotes
Prasanna H. Gowda is a senior research associate, Brent J. Dalzell is a graduate student, David J. Mulla is a professor in the Department of Soil, Water, and Climate at the University of Minnesota in St. Paul. Fred Kollman is a Natural Resource Conservation Services (NRCS) liaison at the Upper Mississippi Environmental Sciences Center in La Crosse, WI.
- Copyright 2001 by the Soil and Water Conservation Society
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