TY - JOUR
T1 - Carbon flux phenology from the sky
T2 - Evaluation for maize and soybean
AU - Mccombs, Alexandria G.
AU - Hiscox, April L.
AU - Wang, Cuizhen
AU - Desai, Ankur R.
AU - Suyker, Andrew E.
AU - Biraud, Sebastien C.
N1 - Funding Information:
Acknowledgments. The authors thank undergraduate research assistants Benjamin Marosites and Jenna Lew for their assistance preparing and processing remote sensing data. This work was partially supported by a SPARC Graduate Research Grant from the Office of the Vice President for Research at the University of South Carolina. This work used data acquired and shared by the FLUXNET community. The FLUXNET eddy covariance data processing and harmonization were carried out by the ICOS Ecosystem Thematic Center, the AmeriFlux Management Project, and the Fluxdata project of FLUXNET, with the support of CDIAC, and the OzFlux, ChinaFlux, and AsiaFlux offices. Landsat surface reflectance products were courtesy of the U.S. Geological Survey Earth Resources Observation and Science Center. The Terra/MODIS Surface Reflectance 8-Day L3 Global 500 m dataset was acquired from the Level 1 and Atmosphere Archive and Distribution System (LAADS) Distributed Active Archive Center (DAAC), located in the Goddard Space Flight Center in Greenbelt, Maryland (http://ladsweb.nascom.nasa.gov).
Publisher Copyright:
© 2018 American Meteorological Society.
PY - 2018/4/1
Y1 - 2018/4/1
N2 - 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 cropspecific measurement tool.
AB - 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 cropspecific measurement tool.
UR - http://www.scopus.com/inward/record.url?scp=85047222174&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85047222174&partnerID=8YFLogxK
U2 - 10.1175/JTECH-D-17-0004.1
DO - 10.1175/JTECH-D-17-0004.1
M3 - Article
AN - SCOPUS:85047222174
VL - 35
SP - 877
EP - 892
JO - Journal of Atmospheric and Oceanic Technology
JF - Journal of Atmospheric and Oceanic Technology
SN - 0739-0572
IS - 4
ER -