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Standing crop residue is important for erosion control and soil water storage, while laid flat crop residue is beneficial for carbon sequestration and subsequent farm operations. Remote sensing provides a quick, objective and efficient tool for measuring the amount of crop residue in the field. The relative position of stubble creates a layer of complexity in remote sensing in addition to distinguishing the crop residue against the soil background. The objective of this study was to estimate crop residue cover and amount for both standing and laid flat stubbles, and between two winter wheat harvest methods (i.e. stripper-header and conventional header) using a select Landsat Thematic Mapper (TM) and hyperspectral-based indices. Data collected from plots in Colorado include hyperspectral scans, crop residue amount (by weight), and residue cover (by photo-grid). Mean analyses, correlation tests, and spectral signature comparison showed the relative position of the crop residues affected the values of some remote sensing indices more than harvest management. However, there was inadequate evidence to support the use of these indices to accurately estimate the amount of residue. This information will be useful in analyzing remotely sensed data, especially for soil and water conservation across different landscapes.