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

Authors

Alexandria G. McCombs, University of South CarolinaFollow
Cuizhen Wang, University of South Carolina
Ankur Desai, University of Wisconsin–Madison
Andrew E. Suyker, University of Nebraska-LincolnFollow
Sebastien C. Bird, Lawrence Berkley National Laboratory, Berkeley

Document Type

Article

Date of this Version

2017

Citation

JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY VOLUME 35 pg. 877-892

DOI: 10.1175/JTECH-D-17-0004.1

Comments

2018 American Meteorological Society.

Abstract

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 here 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. 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.