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Evaluation of SWIR Crop Residue Bands for the Landsat Next Mission

Remote Sensing · 17 Sept 2021 · 10.3390/rs13183718

Abstract

This research reports the findings of a Landsat Next expert review panel that evaluated the use of narrow 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 imagery at sufficient volume to map NPV at a regional scale. The Landsat Next mission, currently under design and expected to launch in the late 2020’s, 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 processed to generate narrow bands with centers at 2040, 2100, 2210, 2260, and 2230 nm, at various bandwidths, that were subsequently used to derive 13 NPV spectral indices from each spectrum. For crop residues with minimal green vegetation cover, 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 2100 nm increased resistance to atmospheric correction residuals and improved mission continuity with Landsat 8 Operational Land Imager Band 7. For prediction of NPV over a full range of green vegetation cover, 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 (≤20 nm) bandwidth at 2040 nm to avoid interference from atmospheric carbon dioxide absorption. 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.

Plant phenotyping relevance

SWIRバンドとスペクトル指数を用いて非光合植生・作物残渣被覆を測定する手法を開発・比較評価しており、植物状態の取得方法が研究の中心である。

abstractThis study employed hyperspectral data collected from 916 agricultural field locations with varying fractional NPV, fractional green vegetation, and surface moisture contents.
abstractFor crop residues with minimal green vegetation cover, two-band indices derived from 2210 and 2260 nm bands were top performers for measuring NPV (R2 = 0.81, RMSE = 0.13)
abstractIn comparison, broadband NPV indices utilizing Landsat 8 bands centered at 1610 and 2200 nm performed poorly in measuring fractional NPV (R2 = 0.44)

Code and data availability

The paper's core phenotyping input — the 916 agricultural field surface reflectance spectra used to derive NPV indices — is published as a USGS data release (reference 44) with a public DOI. No author analysis code or trained models are stated as available. Other URLs (Earth Explorer WV3 imagery, CTIC, NGAC, Auscope) p

Datasetpublic

Hively, W.D.; Lamb, B.T.; Daughtry, C.S.T.; Serbin, G.; Dennison, P. Reflectance Spectra of Agricultural Field Conditions Supporting Remote Sensing Evaluation of Non-Photosynthetic Vegetative Cover. 2021. (U.S. Geological Survey Data Release. Available online: https://doi.org/10.5066/P9XK3867 (accessed on 14 September 2021).

Open resource ↗U.S. Geological Survey Data Release · 10.5066/P9XK3867 · pdf-page:31 lines:1-53

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