پیش بینی جنگل های برگریز فنولوژی جذب کربن ارتقاء اندازه گیری FLUXNET با استفاده از داده های سنجش از دور
Predicting deciduous forest carbon uptake phenology by upscaling FLUXNET measurements using remote sensing data
نویسندگان |
این بخش تنها برای اعضا قابل مشاهده است ورودعضویت |
اطلاعات مجله |
Agricultural and Forest Meteorology,Volume 165 |
سال انتشار |
2012 |
فرمت فایل |
PDF |
کد مقاله |
17461 |
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چکیده (انگلیسی):
Terrestrial ecosystems are highly sensitive to climatic changes in early and late growing seasons. Land surface phenology (LSP), the study of the timing of recurring seasonal pattern of variation in vegetated land surfaces observed from synoptic sensors, has thus received much attention due to its role as a surrogate in detecting the impact of climate change. Although several studies have been conducted on the growing season LSP, studies on the net carbon uptake phenology (CUP) defined as the detrended zero-crossing timing of net ecosystem productivity from a source to a sink in spring and vice versa in autumn, have been scarce. Here we present a CUP determination approach using the commonly available remote sensing data in four selected temperate and boreal deciduous forest CO2 flux tower sites. We test a hypothesis that the mean monthly surface temperature and LSP derived from remote sensing observations explain the CUP both in spring and autumn seasons. Our approach predicts the observed CUP in spring and autumn within 8 day mean errors, equivalent to the temporal resolution of the 8-day composite remote sensing dataset used in this study for the four flux tower sites. The results from this study will have a large implication for global change studies with increasing amount of valuable remote sensing data to be used for monitoring CUP beyond the footprints of CO2 flux towers.
کلمات کلیدی مقاله (فارسی):
کربن فنولوژی جذب؛ بهره وری اکوسیستم ناخالص؛ زمین فنولوژی سطح؛ بهره وری اکوسیستم خالص؛ شاخص فنولوژی؛ سنجش از دور
کلمات کلیدی مقاله (انگلیسی):
Carbon uptake phenology; Gross ecosystem productivity; Land surface phenology; Net ecosystem productivity; Phenology index; Remote sensing
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