SIF and Vegetation Indices in the US Midwestern Agroecosystems, 2016-2021

Themes: Sustainability

Keywords: Field Data, Remote Sensing


Wu, G., Guan, K., Kimm, H., Miao, G., and Jiang, C. March 17, 2023. “SIF and Vegetation Indices in the US Midwestern Agroecosystems, 2016-2021.” ORNL DAAC. DOI: 10.3334/ORNLDAAC/2136.


Ground sites in US Midwestern agroecosystems, and data processing protocol.

This dataset contains half-hourly ground solar-induced chlorophyll fluorescence (SIF) and vegetation indices including NDVI, EVI, Red edge chlorophyll index, green chlorophyll index, and photochemical reflectance index at seven crop sites in Nebraska and Illinois for the period 2016-2021. Four sites were located at Eddy Covariance (EC) tower sites (sites US-Ne2, US-Ne3, US-UiB, and US-UiC), and three sites were located on private farms (sites Reifsteck, Rund, and Reinhart). The sites were either miscanthus, corn-soybean rotation or corn-corn-soybean rotation. The spectral data for SIF retrieval and hyperspectral reflectance for vegetation index calculation were collected by the FluoSpec2 system, installed near planting, and uninstalled after harvest to collect whole growing-season data. Raw nadir SIF at 760 nm from different algorithms (sFLD, 3FLD, iFLD, SFM) are included. SFM_nonlinear and SFM_linear represent the Spectral fitting method (SFM) with the assumption that fluorescence and reflectance change with wavelength non-linearly and linearly, respectively. Additional data include two SIF correction factors including calibration coefficient adjustment factor (f_cal_corr_QEPRO) and upscaling nadir SIF to eddy covariance footprint factor (ratio_EC footprint, SIF pixel), and measured FPAR from quantum sensors and Rededge NDVI calculated FPAR. The data are provided in comma-separated values (CSV) format.



GitHub – Process functions for half-hourly SIF/VIs retrieval

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