Evaluating Crop Residue Bands for the Landsat Next Mission

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Non-photosynthetic vegetation (NPV) includes the residual material left on a field after crop harvest, such as stalks, stubble, and seeds. Satellite-based detection and mapping of NPV supports better understanding of soil health, adoption of conservation tillage practices, and vegetation dynamics in cropland, pasture, and rangeland settings. Lignin and cellulose, which are associated with NPV, display an absorption feature near 2100 nanometer that can be accurately measured using narrow-band shortwave infrared (SWIR) indices. However, no current satellites are capable of providing narrow-band SWIR reflectance data at large scales.

The Landsat Next mission, which is currently in pre-formulation and expected to launch in the late 2020s, provides the opportunity for achieving increased SWIR spectral sampling and resolution with the adoption of new sensor technology. The sensor will provide Landsat data continuity by preserving heritage Landsat spectral bands and will enhance synergy with the European Space Agency’s Sentinel-2 sensors by including additional spectral bands and improved spatial resolution. Landsat Next will also include spectral bands that address emerging applications such as water quality and quantity, snow and ice detection, crop residue, and improved surface temperature retrieval via temperature/emissivity separation. Narrow spectral bands in the SWIR region are planned additions for measurement of ligno-cellulose absorption features to support the detection of NPV, including crop residue.

A Landsat Next expert review panel was convened in 2020–2021 to focus on the use of narrowband SWIR reflectance to measure ligno-cellulose absorption features. Using a published dataset of 916 surface reflectance spectra collected from agricultural fields that ranged from 0% to 100% NPV cover, researchers calculated mean reflectance for five SWIR bands (2040, 2100, 2210, 2260, and 2330 nm) at varying bandwidths ranging from 10 to 50 nm. These band centers were chosen based on demonstrated NPV characterization performance from previous missions like ASTER, WorldView-3, and Hyperion. Using these band centers to calculate 13 NPV indices, the study evaluated the effects of bandwidths, atmospheric impacts, sensor signal-to-noise ratios, fractional green vegetative cover, and background soil reflectance on the ability of SWIR-derived indices to measure fractional NPV on agricultural fields, and assessed spectral continuity with the existing Landsat 8 Operational Land Imager band 7. Several options, including the best 4-band, 3-band, and 2-band solutions, were described for possible inclusion on the Landsat Next mission.

Any of these narrow-band SWIR solutions would provide a greatly improved capability for detecting crop residue cover based on characterization of ligno-cellulose absorption features. The resulting tools will enable managers to monitor the adoption of conservation tillage practices, as well as the effects of grassland management, through accurate global characterization of NPV.


Example spectra for crop residue (NPV), soil, and green vegetation as surface reflectance for a) 400–2500 nanometer wavelength range, and b) 1950–2450 nanometer wavelength range for the same spectra, showing the five shortwave infrared bands under consideration at 10, 30, and 50 nanometer bandwidths (grey bars) as well as current Landsat Operational Land Imager (OLI) bands (tan bars). Note the decreased crop residue reflectance at 2100 nanometer and 2300 nanometer due to ligno-cellulose absorption. The supporting journal publication is available online (https://doi.org/10.3390/rs13183718).


Author Name
W. Dean Hively
Author Email