Evaluation of SWIR crop residue bands for the landsat next mission

Authors: HIVELY, W.D. - Us Geological Survey (USGS); LAMB, B.T. - City University Of New York; Daughtry, Craig; SERBIN, G. - Collaborator; DENNISON, P. - University Of Utah; KOKALY, R. - Us Geological Survey (USGS); WU, Z. - Us Geological Survey (USGS); MASEK, J. - National Aeronautics And Space Administration (NASA)

Submitted to: Remote Sensing
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/30/2021
Publication Date: 9/17/2021
Citation: Hively, W., Lamb, B., Daughtry, C.S., Serbin, G., Dennison, P., Kokaly, R., Wu, Z., Masek, J. 2021. Evaluation of SWIR crop residue bands for the landsat next mission. Remote Sensing. 13(18). https://doi.org/10.3390/rs13183718.
DOI: https://doi.org/10.3390/rs13183718

Interpretive Summary: Crop residues are non-photosynthetic vegetation (NPV) that remains on the soil surface after the crop is harvested. Soil tillage practices, crop rotations, and harvest methods affect crop residue cover which, in turn, impacts soil erosion, soil organic matter, and soil health. Traditional methods of measuring crop residue cover are labor intensive and impractical for assessing large areas in a timely manner. Current remote sensing satellites with broad spectral bands and global coverage, such as Landsat, can readily assess crop growth and development, but cannot reliably distinguish crop residues and soils. Current satellites with appropriate narrow spectral bands to distinguish crop residues and soils cannot provide timely global coverage. This research reports the findings of a review panel that evaluated methods for measuring crop residue cover and the adoption of conservation tillage practices within agricultural landscapes. Results could also apply to detection of NPV in pasture, grazing lands, and non-agricultural settings. Four viable options with trade-offs are presented for the selection of optimal spectral bands for the Landsat Next mission.

Technical Abstract: This research reports the findings of a Landsat Next expert review panel that evaluated the use of narrowband shortwave infrared (SWIR) reflectance bands to measure ligno-cellulose absorption features centered near 2100 and 2300 nm, with the objective of measuring and mapping non-photosynthetic vegetation (NPV), crop residue cover, and the adoption of conservation tillage practices within agricultural landscapes. Results could also apply to detection of NPV in pasture, grazing lands, and non-agricultural settings. Currently, there are no satellite data sources that provide narrowband or hyperspectral SWIR data at sufficient volume to map NPV at a regional scale. The Landsat Next mission, currently under design and expected to launch in late 2020s, provides the opportunity for achieving increased SWIR sampling and spectral resolution with the adoption of new sensor technology. This study employed hyperspectral data collected from 916 agricultural field locations with varying fractional NPV, fractional green vegetation, and surface moisture contents. These spectra were process to generate narrow multispectral bands with centers at 2040, 2100, 2210, 2260, and 2230 nm, and with varying bandwidths, that were subsequently used to derive 12 NPV spectral indices from each individual spectrum. For crop residues with low fraction of green vegetation cover (NDVI < 0.3), two-band indices derived from 2210 and 2260 nm bands, were top performers for measuring NPV (R2 = 0.81, RMSE = 0.13) using bandwidths of 30 to 50 nm, and the addition of a third band at 2100nm increased resistance to atmospheric artefacts and improved mission continuity with Landsat 8 Operational Land Imager Band 7. For prediction of NPV over a full range of green vegetation cover (NDVI < 1.0), the Cellulose Absorption Index, derived from 2040, 2100, and 2210 nm bands, was top performer (R2=0.77, RMSE = 0.17)., but required a narrow (<=20nm) bandwidth at 2040 to avoid interference from atmospheric carbon dioxide absorbance. In comparison, broadband NPV indices utilizing Landsat 8 bands centered at 1610 and 2200 nm performed poorly in measuring fractional NPV (R2 = 0.44), with significantly increased interference from green vegetation.