Multispectral satellite mapping of crop residue cover and tillage intensity in Iowa

Quantifying crop residue cover is crucial for identifying tillage intensity and evaluating effectiveness of conservation management practices across large geographic areas. Current assessment protocols are labor intensive, time consuming, and costly. Our objective was to assess crop residue cover and soil tillage intensity in a watershed in central Iowa for three years (2009 to 2011) using multispectral satellite images. The watershed is dominated by corn (Zea mays L.) and soybean (Glycine max [L.] Merr.), which are grown on glacial-till derived soils across 85% of the land area. For each year, crop residue cover was measured for a few fields using the line-point transect method or visually estimating surface cover through roadside surveys. Conservation tillage fields had ≥30% residue cover, while more intensively tilled fields had <30% residue cover. Landsat Thematic Mapper (TM), Système Pour l'Observation de la Terre (SPOT) High Resolution Geometrical (HRG), Indian ResourceSat Advanced Wide Field Sensor (AWiFS), and Deimos satellite images were also acquired and analyzed to determine surface cover. SPOT and Landsat images provided similar classification accuracy ranging from 64% to 92%, while AWiFS and Deimos classifications had accuracies ranging from 61% to 73%. Clouds and the revisit interval for each satellite affected the timing of satellite images with respect to field operations, which also influenced classification accuracy. Overall soil tillage intensity varied little from year-to-year. Soil tillage intensity was also mapped as a function of slope, which could be useful for targeting additional conservation practices throughout the watershed. We conclude that satellite imagery is well suited for classifying crop residue cover. Furthermore, two recently launched satellites, Landsat-8 and Sentinel-2, have comparable multispectral sensors and together these satellites should provide frequent opportunities to acquire suitable imagery for assessing crop residue cover and soil tillage intensity over large geographic areas.