Carbon Flux Phenology from the Sky: Evaluation for Maize and Soybean

Journal Article · 24 April 2018 · Journal of Atmospheric and Oceanic Technology

DOI: https://doi.org/10.1175/JTECH-D-17-0004.1 · OSTI ID:1477273

McCombs, Alexandria G. ^[1]; Hiscox, April L. ^[1]; Wang, Cuizhen ^[1]; Desai, Ankur R. ^[2]; Suyker, Andrew E. ^[3]; Biraud, Sebastien C. ^[4]

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1. Univ. of South Carolina, Columbia, SC (United States). Department of Geography
2. Univ. of Wisconsin, Madison, WI (United States). Department of Atmospheric and Oceanic Sciences
3. Univ. of Nebraska, Lincoln, NE (United States). School of Natural Resources
4. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Climate Sciences Department

Carbon flux phenology is widely used to understand carbon flux dynamics and surface exchange processes. Vegetation phenology has been widely evaluated by remote sensors; however, very few studies have evaluated the use of vegetation phenology for identifying carbon flux phenology. Currently available techniques to derive net ecosystem exchange (NEE) from a satellite image use a single generic modeling subgroup for agricultural crops. But, carbon flux phenological processes vary highly with crop types and land management practices; this paper reexamines this assumption. Presented in this paper are an evaluation of ground-truth remotely sensed vegetation indices with in situ NEE measurements and an identification of vegetation indices for estimating carbon flux phenology metrics by crop type. Results show that the performance of different vegetation indices as an indicator of phenology varies with crop type, particularly when identifying the start of a season and the peak of a season. Finally, maize fields require vegetation indices that make use of the near-infrared and red reflectance bands, while soybean fields require those making use of the shortwave infrared (IR) and near-IR bands. In summary, the study identifies how to best utilize remote sensing technology as a crop specific measurement tool.

• Research Organization: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
• Sponsoring Organization: USDOE Office of Science (SC)
• Grant/Contract Number: AC02-05CH11231
• OSTI ID: 1477273
• Journal Information: Journal of Atmospheric and Oceanic Technology, Vol. 35, Issue 4; ISSN 0739-0572
• Publisher: American Meteorological SocietyCopyright Statement
• Country of Publication: United States
• Language: English