Remote sensing of contrasting tillage practices in the Texas Panhandle

Abstract

Tillage information is crucial in environmental modelling as it has a direct impact on water holding capacity, evapotranspiration, carbon sequestration and water quality. In this study, a set of Landsat Thematic Mapper (TM)‐based linear logistic models were developed for mapping tillage practices and verified with an independent dataset. For data collection purposes, 35 and 41 commercial fields were randomly selected in Moore and Ochiltree counties, respectively, in the Texas Panhandle. Tillage survey was planned and conducted to coincide with Landsat 5 satellite overpasses during the 2005 planting season and two TM scenes were acquired. Using the Moore County dataset, seven logistic regression models were developed and these were evaluated with the data collected from Ochiltree County. The overall classification accuracy of the models varied from 86% to 91% with the Moore County dataset. These models were evaluated against independent Ochiltree County dataset and resulted in somewhat less accurate (classification accuracy of 67–85%) but still useful results. Analysis of these results indicates that logistic regression models that have indices derived from the combination of TM band 5 with bands 4 or 6 may provide consistent and acceptably accurate results when they are applied in the same geographic region.

Acknowledgements

We thank Timothy Trimble and Scott Strawn of Texas Cooperative Extension for their logistical support in conducting field campaigns in Moore and Ochiltree counties.