Diverse Responses of Multiple Satellite‐Derived Vegetation Greenup Onsets to Dry Periods in the Amazon

Diverse Responses of Multiple Satellite‐Derived Vegetation Greenup Onsets to Dry Periods in the Amazon
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亚马逊地区多个卫星衍生的植被返绿起始对干旱期的不同反应

DOI:
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发表时间:
2022
影响因子:
5.2
通讯作者:
C. Schaaf
C. Schaaf
中科院分区:
地球科学1区
文献类型:
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作者:
Xiaoyang Zhang;Yu Shen;Shuai Gao;Weile Wang;C. Schaaf

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在过去的二十年里,卫星观测到的亚马逊植被绿度和季节动态引起了相当多的学术争论。尽管如此,人们对亚马逊森林的物候时间,特别是它们对干旱期的反应仍然知之甚少。在这里,我们从 10 分钟的对地静止卫星观测中明确识别了植被冠层绿化开始的不同时间,并根据每日降水数据计算了干旱期开始和结束的时间。我们首次揭示亚马逊植被冠层在一年内定期经历两个返绿周期。从干旱期开始到结束,返绿开始的发生情况各不相同,但在局部地区表现出有规律的变化,尽管整个地区的变化不规则。多次绿化爆发显示出复杂的空间变化,这与干旱期的空间运动密切相关。这些结果为我们对干旱时期亚马逊植被冠层动态的复杂性的理解提供了新的见解,这可以显着改善碳和水循环的模拟。
Satellite‐derived vegetation greenness and seasonal dynamics in the Amazon have generated considerable academic debate over the past two decades. Despite this, the phenological timing of Amazon forests and, in particular their responses to dry periods, remain poorly understood. Here we explicitly identify the diverse timing of vegetation canopy greenup onsets from 10‐min geostationary satellite observations, and compute the timing of both the start and end of dry periods from daily precipitation data. We, for the first time, reveal that the Amazon vegetation canopy regularly experiences two cycles of greenup onsets during a year. The occurrence of greenup onset varies diversely from the start to end of the dry periods, but demonstrates regular shifts in local areas, although irregular shifts across the region. The multiple greenup onsets show complex spatial shifts, which closely follow the spatial movement of dry periods. The results provide a new insight into our understanding of the complexity of Amazonian vegetation canopy dynamics during dry periods, which could significantly improve the simulation of carbon and water cycles.
DOI: 10.1016/j.agrformet.2018.03.003
发表时间: 2018-06
影响因子: 6.2
作者:
Xiaoyang Zhang;Senthilnath Jayavelu;Lingling Liu;M. Friedl;G. Henebry;Yan Liu;C. Schaaf;A. Richardson;Joshua Gray
通讯作者: Xiaoyang Zhang;Senthilnath Jayavelu;Lingling Liu;M. Friedl;G. Henebry;Yan Liu;C. Schaaf;A. Richardson;Joshua Gray