Evaluation of SWIR Crop Residue Bands for the Landsat Next Mission

Remote Sensing

Craig S. T. Daughtry¹  Philip Dennison²  Guy Serbin³  Jeffery G. Masek⁴  Raymond F. Kokaly⁵  Wells Dean Hively⁶  Brian T. Lamb⁷  Zhuoting Wu⁸ 

[1] Agricultural Research Service, Hydrology and Remote Sensing Laboratory, U.S. Department of Agriculture, Beltsville, MD 20705, USA;Department of Geography, University of Utah, Salt Lake City, UT 84112, USA;EOanalytics Ltd., D11 YNR2 Dublin, Ireland;NASA Goddard Space Flight Center, Biospheric Sciences Laboratory, 8800 Greenbelt Road, Greenbelt, MD 20771, USA;U.S. Geological Survey, Geology, Geophysics, and Geochemistry Science Center, Lakewood, CO 80225, USA;U.S. Geological Survey, Lower Mississippi-Gulf Water Science Center, Beltsville, MD 20705, USA;U.S. Geological Survey, Lower Mississippi-Gulf Water Science Center, Coram, NY 11727, USA;U.S. Geological Survey, National Land Imaging Program, Flagstaff, AZ 86001, USA;

关键词: Landsat;    Landsat Next;    non-photosynthetic vegetation;    crop residue;    tillage;    SWIR;   

DOI  :  10.3390/rs13183718

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown