Optimizing Landsat Next Shortwave Infrared Bands for Crop Residue Characterization

This study focused on optimizing the placement of shortwave infrared (SWIR) bands for pixel-level estimation of fractional crop residue cover (f(R)) for the upcoming Landsat Next mission. We applied an iterative wavelength shift approach to a database of crop residue field spectra collected in Beltsville, Maryland, USA (n = 916) and computed generalized two- and three-band spectral indices for all wavelength combinations between 2000 and 2350 nm, then used these indices to model field-measured f(R). A subset of the full dataset with a Normalized Difference Vegetation Index (NDVI) < 0.3 threshold (n = 643) was generated to evaluate green vegetation impacts on f(R) estimation. For the two-band wavelength shift analyses applied to the NDVI < 0.3 dataset, a generalized normalized difference using 2226 nm and 2263 nm bands produced the top f(R) estimation performance (R-2 = 0.8222; RMSE = 0.1296). These findings were similar to the established two-band Shortwave Infrared Normalized Difference Residue Index (SINDRI) (R-2 = 0.8145; RMSE = 0.1324). Performance of the two-band generalized normalized difference and SINDRI decreased for the full-NDVI dataset (R-2 = 0.5865 and 0.4144, respectively). For the three-band wavelength shift analyses applied to the NDVI < 0.3 dataset, a generalized ratio-based index with a 2031-2085-2216 nm band combination, closely matching established Cellulose Absorption Index (CAI) bands, was top performing (R-2 = 0.8397; RMSE = 0.1231). Three-band indices with CAI-type wavelengths maintained top f(R) estimation performance for the full-NDVI dataset with a 2036-2111-2217 nm band combination (R-2 = 0.7581; RMSE = 0.1548). The 2036-2111-2217 nm band combination was also top performing in f(R) estimation (R-2 = 0.8690; RMSE = 0.0970) for an additional analysis assessing combined green vegetation cover and surface moisture effects. Our results indicate that a three-band configuration with band centers and wavelength tolerances of 2036 nm (+/- 5 nm), 2097 nm (+/- 14 nm), and 2214 (+/- 11 nm) would optimize Landsat Next SWIR bands for f(R) estimation.