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contributor authorMcCombs, Alexandria G.
contributor authorHiscox, April L.
contributor authorWang, Cuizhen
contributor authorDesai, Ankur R.
contributor authorSuyker, Andrew E.
contributor authorBiraud, Sebastien C.
date accessioned2019-09-19T10:03:10Z
date available2019-09-19T10:03:10Z
date copyright1/24/2018 12:00:00 AM
date issued2018
identifier otherjtech-d-17-0004.1.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4261004
description abstractAbstractCarbon 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.
publisherAmerican Meteorological Society
titleCarbon Flux Phenology from the Sky: Evaluation for Maize and Soybean
typeJournal Paper
journal volume35
journal issue4
journal titleJournal of Atmospheric and Oceanic Technology
identifier doi10.1175/JTECH-D-17-0004.1
journal fristpage877
journal lastpage892
treeJournal of Atmospheric and Oceanic Technology:;2018:;volume 035:;issue 004
contenttypeFulltext


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