Multitemporal remote sensing of crop residue cover and tillage practices: A validation of the minNDTI strategy in the United States

Abstract: Accurate, site-specific tillageinformation forms an important dimension for development of effective agricultural management practices and policies. Landsat Thematic Mapper(TM) imagery provides the opportunity for systematic mapping of tillagepractices via crop residue( plant litter/ senescent or non-photosynthetic vegetation) cover (CRC) estimation at broad scales because of its repetitive coverage of the Earth's land areas over several decades. This study evaluated the effectiveness of a multi-temporal approach using the minimal values of Normalized Difference TillageIndex (minNDTI) for assessing CRC at multiple locations over several years. Local models were generated for each dataset. In addition, an empirical model was applied to each dataset to test the feasibility of a regional model in mapping CRC. Results show that the minNDTI method was able to estimate CRC and a regional model is possible. We found that in addition to the known impact of emergent green vegetation, soil moisture and organic carbon can also confound the NDTI signal, thereby underestimating CRC for low-lying wet and dark areas. Accuracy of the minNDTI technique is comparable to the hyperspectral Cellulose Absorption Index (CAI) and the ASTER ShortwaveInfrared Normalized Difference Residue Index (SINDRI) for tillageclassification. This minNDTI technique is currently the best for monitoring CRC and tillagepractices from space, opening the door for generating field-level tillagemaps at broad spatial and temporal scales.