2012
DOI: 10.1111/gcb.12077
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Changes in satellite‐derived spring vegetation green‐up date and its linkage to climate in China from 1982 to 2010: a multimethod analysis

Abstract: The change in spring phenology is recognized to exert a major influence on carbon balance dynamics in temperate ecosystems. Over the past several decades, several studies focused on shifts in spring phenology; however, large uncertainties still exist, and one understudied source could be the method implemented in retrieving satellite-derived spring phenology. To account for this potential uncertainty, we conducted a multimethod investigation to quantify changes in vegetation green-up date from 1982 to 2010 ove… Show more

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Cited by 288 publications
(262 citation statements)
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“…Climate warming has greatly affected vegetation growth in China over the past three decades (Zhou et al, 2001;McMahon et al, 2010;Mao et al, 2012;Cong et al, 2013;Xu et al, 2014). According to this study, the positive relationship between temperature and NDVI became negative over the course of the study period, although this result was not statistically significant.…”
Section: Discussionmentioning
confidence: 63%
“…Climate warming has greatly affected vegetation growth in China over the past three decades (Zhou et al, 2001;McMahon et al, 2010;Mao et al, 2012;Cong et al, 2013;Xu et al, 2014). According to this study, the positive relationship between temperature and NDVI became negative over the course of the study period, although this result was not statistically significant.…”
Section: Discussionmentioning
confidence: 63%
“…The warming-induced earlier onset of springtime carbon uptake is also supported by observed increases in vegetation greenness described by NDVI inferred from space-borne sensors (Gong and Shi, 2003;Mao et al, 2012;Cong et al, 2013). Increases in autumn NDVI have also been observed and while this is indicative of increased photosynthetic activity it is not necessarily inconsistent with the observed early onset of net carbon release.…”
Section: Appendix E: Analysis Of Ancillary Data E1 Surface Temperaturmentioning
confidence: 60%
“…Many studies use data from AVHRR sensor to study leaf/surface phenology, for example [19,27,28], probably because of a longer time series spanning over three decades thus providing a long record of vegetation conditions ideal to study the long-term effect of climate variability on vegetation phenology. However, for highly fragmented ecosystems/landscapes, i.e., in Western Europe, vegetation type-specific studies are generally challenging to undertake when using data from AVHRR sensor because the pixel is always likely to be composed of more than one landcover type.…”
Section: Discussionmentioning
confidence: 99%
“…In some parts of USA, temporal trends (negative and positive) were only found in the satellite derived SOS ensemble metrics from two methods (HANTS and Midpoint pixel ) that produced relatively more accurate SOS metrics, but no trend was found in the ground observations [19]. Of recent, temporal trends were detected over China in the satellite SOS estimates [27,28], but no results were reported in regard to ground observations. However, a study focusing on leaf unfolding dates of broadleaf deciduous forest in Northern China found significant spatial and temporal correlations between ground observations and satellite SOS estimates [29], but temporal trend analysis on SOS was not done.…”
Section: Introductionmentioning
confidence: 95%
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