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Monitoring vegetation change and their potential drivers in Yangtze River Basin of China from 1982 to 2015

机译:1982年至2015年,监测中国长江流域植被变化及其潜在司机

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摘要

Monitoring vegetation change and their potential drivers are important to environmental management. Previous studies on vegetation change detection and driver discrimination were two independent fields. Specifically, change detection methods focus on nonlinear and linear change behaviors, i.e., abrupt change (AC) and gradual change (GC). But driver discrimination studies mainly used linear coupling models which rarely concerned the nonlinear behaviors of vegetation. The two diagnoses need be treated as sequential flow because they have inner causality mechanisms. Furthermore, ACs concealed in time series may induce over/under-estimate contributions from human. We chose the Yangtze River Basin of China (YRB) as a study area, first separated ACs from GCs using breaks for additive and seasonal trend method, then discriminated drivers of GCs using optimized Restrend method. Results showed that (1) 2.83% of YRB were ACs with hotspots in 1998 (30.2%), 2003 (10.4%), and 2002 (7.6%); 66.7% of YRB experienced GC with 94.8% of which were positive; and (2) climate induced more area but less dramatic GCs than human activities. Further analysis showed that temperature was the main climate driver to GCs, while human-induced GCs were related to local eco-policies. The widely occurring ACs in 1998 were related to the flooding catastrophe, while the dramatic ACs in sub-basin 12 in 2003 may result from urbanization. This paper provides clear insights on the vegetation changes and their drivers at a relatively long perspective (i.e., 34 years). Sequential combination of specifying different vegetation behaviors with driver analysis could improve driver characterizations, which is key to environmental assessment and management in YRB.
机译:监测植被变化及其潜在司机对环境管理很重要。以前关于植被变更检测和驾驶员歧视的研究是两个独立的领域。具体地,改变检测方法侧重于非线性和线性变化行为,即突然变化(AC)和逐渐变化(GC)。但驾驶员歧视研究主要使用线性耦合模型,这很少涉及植被的非线性行为。两种诊断需要被视为连续流量,因为它们具有内部因果机制。此外,在时间序列中隐藏的AC可以诱导人类的估计/不受估计的贡献。我们选择了中国(YRB)的长江流域作为一家学习区,首先使用Active和季节性趋势方法的休息分离GCS,然后使用优化的restend方法对GCS的判断驱动程序进行区分。结果表明,(1)中的2.83%的YRB是1998年与热点的ACS(30.2%),2003年(10.4%),2002年(7.6%); 66.7%的YRB经历过GC,其中94.8%是积极的; (2)气候诱导更多地区但比人类活动更少戏剧性的GCS。进一步的分析表明,温度是GCS的主要气候驱动器,而人类诱导的GCS与当地生态政策有关。 1998年的广泛发生的AC与洪水灾难有关,而2003年副盆地12中的戏剧性ACS可能导致城市化可能导致。本文在相对较长的角度(即34岁)上,对植被变化及其司机提供了清晰的见解。用驾驶员分析指定不同植被行为的顺序组合可以改善驾驶特性,这是YRB中环境评估和管理的关键。

著录项

  • 来源
    《Environmental Monitoring and Assessment》 |2020年第10期|642.1-642.18|共18页
  • 作者单位

    Cent China Normal Univ Key Lab Geog Proc Anal & Simulat Hubei Prov Wuhan 430079 Peoples R China|Cent China Normal Univ Coll Urban & Environm Sci Wuhan 430079 Peoples R China;

    Cent China Normal Univ Key Lab Geog Proc Anal & Simulat Hubei Prov Wuhan 430079 Peoples R China|Cent China Normal Univ Coll Urban & Environm Sci Wuhan 430079 Peoples R China;

    Cent China Normal Univ Key Lab Geog Proc Anal & Simulat Hubei Prov Wuhan 430079 Peoples R China|Cent China Normal Univ Coll Urban & Environm Sci Wuhan 430079 Peoples R China;

    Cent China Normal Univ Key Lab Geog Proc Anal & Simulat Hubei Prov Wuhan 430079 Peoples R China|Cent China Normal Univ Coll Urban & Environm Sci Wuhan 430079 Peoples R China;

    Wageningen Univ & Res Lab Geoinformat Sci & Remote Sensing Droevendaalsesteeg 3 NL-6708 PB Wageningen Netherlands;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Abrupt change; Gradual change; Restrend; Naturogenic and anthropogenic drivers;

    机译:突然变化;逐渐变化;restend;Naturogenic和人为司机;

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