Estimating Mean Field Residue Cover on Midwestern Soils Using Satellite Imagery

Knowledge of residue cover is crucial for targeting conservation efforts to reduce soil erosion, runoff, and associated environmental impacts; however, a rapid, accurate, inexpensive methodology is not currently available. Previous studies have shown mixed results detecting crop residue using Landsat residue indices, but conditions generally included poor soil color contrast, emergent vegetation, or categorized residue cover. Our objectives were to evaluate a new normalized difference residue index (NDRI), along with other indices, over multiple image dates in 2005 and 2006 on dark soils in north-central Iowa. An automated method for field boundary delineation was used. The NDRI, using Landsat Bands 3 and 7, performed best overall, explaining 81% of the residue cover differences overall, 78% before emergence, and 9% after emergence. The normalized difference tillage index (NDTI), using Landsat Bands 5 and 7, also performed well explaining 68% of the variation overall, 86% before emergence, and 6% after emergence. Introduction of an empirical correction of the influence of green vegetation improved index performance. The NDTI outperformed the NDRI after green vegetation correction, explaining 67% of the variation versus 63%. The NDTI also returned the best RMSE (0.11) under preemergence conditions, and 0.15 after green vegetation correction. Generally, indices utilizing Landsat Band 7, which contain lignin and cellulose absorption bands absent in soil, returned the best residue detection results. Indices utilizing Landsat Band 4, where the reflectance of green vegetation is high, had difficult), detecting residue cover, especially after plant emergence.