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Sherpa Romeo green journal; open accesSoil management practices that maintain crop residue cover and reduce tillageimprove soil structure, increase organic matter content in the soil, positively influence waterinfiltration, evaporation and soil temperature, and play an important role in fixing CO2 in thesoil. Consequently, good residue management practices on agricultural land have manypositive impacts on soil quality, crop production quality and decrease the rate of soil erosion.Several studies have been undertaken to develop and test methods to derive information oncrop residue cover and soil tillage using empirical and semi-empirical methods incombination with remote sensing data. However, these methods are generally not sufficientlyrigorous and accurate for characterizing the spatial variability of crop residue cover inagricultural fields. The goal of this research is to investigate the potential of hyperspectralHyperion (Earth Observing-1, EO-1) data and constrained linear spectral mixture analysis(CLSMA) for percent crop residue cover estimation and mapping. Hyperion data wereacquired together with ground-reference measurements for validation purposes at thebeginning of the agricultural season (prior to spring crop planting) in Saskatchewan(Canada). At this time, only bare soil and crop residue were present with no crop cover development. In order to extract the crop residue fraction, the images were preprocessed, andthen unmixed considering the entire spectral range (427 nm–2355 nm) and the pure spectra(endmember). The results showed that the correlation between ground-referencemeasurements and extracted fractions from the Hyperion data using CLMSA showed that themodel was overall a very good predictor for crop residue percent cover (index of agreement(D) of 0.94, coefficient of determination (R2) of 0.73 and root mean square error (RMSE) of8.7%) and soil percent cover (D of 0.91, R2 of 0.68 and RMSE of 10.3%). This performanceof Hyperion is mainly due to the spectral band characteristics, especially the availability ofcontiguous narrow bands in the short-wave infrared (SWIR) region, which is sensitive to theresidue (lignin and cellulose absorption features).Ye

Spatial Variability Mapping of Crop Residue Using Hyperion (EO-1) Hyperspectral Data