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Regional evaluation of satellite-based methods for identifying leaf unfolding date

机译:基于卫星的识别叶片展开日期的区域评价

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摘要

Satellite-based methods have been widely used to identify the critical phenophases of terrestrial vegetation and detect responses of phenophases to climate change. However, few studies have been conducted to evaluate the performance of satellite-based methods for identifying the spatial and temporal changes of phenophases based on site-based phenophase observations. This study used the ground observations of leaf unfolding date (LUD) of woody and herbaceous plants over 31 sites in China to evaluate the accuracy of LUDs modeled by eight satellite-based methods using Moderate resolution imaging spectroradiometer (MODIS) vegetation index product. Our results showed an observed 2.62 and 2.45 days advance of LUD over the spatial scale with an increased mean annual temperature of 1 degrees C over the forest and grassland ecosystems respectively, but almost all eight methods underestimated the advance rates. In addition, the trends for the observed LUD varied from site to site, and the eight methods showed the poor performance in capturing the long-term trends, mostly because low temporal resolution of satellite data. Most methods tended to overestimate the trend of LUD over more than 40% forest sites. Our results highlight that there is a need for further improvements in the methods and satellite datasets used for identifying LUD.
机译:基于卫星的方法被广泛用于鉴定陆地植被的临界磷酸酶,并检测苯酚对气候变化的反应。然而,已经进行了很少的研究来评估基于卫星的方法的性能,以确定基于基于位点的苯相酪磷酶观察的磷酸胞菌的空间和时间变化。本研究采用木本和草本植物的叶展开日(LUD)的地面观测过在中国的31个站点,以评估使用中分辨率成像光谱仪(MODIS)植被指数产品8基于卫星的方法建模LUDs的准确性。我们的研究结果显示,观察到2.62 2.45两天前路德人在空间尺度与森林密布增加1摄氏度,年均气温和草原生态系统分别,但几乎所有的八种方法低估了前进速度。此外,观察LUD的趋势从现场变化,八种方法在捕获长期趋势方面表现出差的性能,主要是因为卫星数据的低时间分辨率。大多数方法倾向于高估超过40%以上的森林网站的趋势。我们的结果强调,需要进一步改进用于识别LUD的方法和卫星数据集。

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    Sun Yat Sen Univ Sch Atmospher Sci Southern Marine Sci & Engn Guangdong Lab Zhuhai Zhuhai 519082 Guangdong Peoples R China|Minist Educ Key Lab Trop Atmosphere Ocean Syst Zhuhai 519082 Peoples R China;

    Sun Yat Sen Univ Sch Atmospher Sci Southern Marine Sci & Engn Guangdong Lab Zhuhai Zhuhai 519082 Guangdong Peoples R China|Minist Educ Key Lab Trop Atmosphere Ocean Syst Zhuhai 519082 Peoples R China;

    Sichuan Univ Coll Life Sci Minist Educ Key Lab Bioresource & Ecoenvironm Chengdu 610065 Peoples R China;

    Beijing Normal Univ Coll Global Change & Earth Syst Sci Beijing 100038 Peoples R China;

    Sun Yat Sen Univ Sch Atmospher Sci Southern Marine Sci & Engn Guangdong Lab Zhuhai Zhuhai 519082 Guangdong Peoples R China|Minist Educ Key Lab Trop Atmosphere Ocean Syst Zhuhai 519082 Peoples R China;

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  • 正文语种 eng
  • 中图分类
  • 关键词

    Phenology; Leaf unfolding date; Remote sensing; Vegetation index; Forest; Grassland;

    机译:候选;叶展示日期;遥感;植被指数;森林;草原;

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