植被(病理学)
绿化
归一化差异植被指数
蒸散量
环境科学
降水
增强植被指数
经验正交函数
自然地理学
气候变化
地理
气候学
生长季节
大气科学
植被指数
地质学
生态学
气象学
病理
海洋学
生物
医学
作者
Hao Zhang,Zengyun Hu,Zhuo Zhang,Yaoming Li,Shuling Song,Xi Chen
出处
期刊:International journal of applied earth observation and geoinformation
日期:2024-03-01
卷期号:127: 103664-103664
被引量:1
标识
DOI:10.1016/j.jag.2024.103664
摘要
Recently, the warm–wet tendency in northwestern China has become a hot research topic. How does vegetation change under this tendency, and what are the impacts of climate change on vegetation? To address these questions, the dynamic variations in vegetation and their relationships with five climate factors (i.e., Pre: precipitation, Tmp: temperature, SM: root zone soil moisture, Vap: vapor pressure, and Pet: potential evapotranspiration) across Xinjiang are comprehensively analyzed during the period of 1982–2021. The spatiotemporal variations in vegetation are analyzed using the normalized difference vegetation index (NDVI) and leaf area index (LAI), employing the Mann–Kendall (M−K) and empirical orthogonal function (EOF) approaches. The key findings indicate that a significant greening trend is observed, with a value of 0.00226 m2m-2year−1 according to the annual LAI. For the seasonal variations, the vegetation had the largest increasing trend in summer (JJA: June, July, August) compared with the other seasons, with significant values of 0.000876 year−1 and 0.00382 m2m-2year−1 for the NDVI and LAI, respectively (p < 0.05). The spring (MAM: March, April, May) and the growing season (GS) also have significant increasing trends based on the LAI. Spatially, approximately 40 % of the areas have an increasing trend, indicating greening variations, which are mainly distributed in the mountainous area of northwestern Xinjiang. The EOF results also suggest that the vegetation in the mountainous area of northwestern Xinjiang has a greening trend. The vegetation is significantly positively correlated with the five climate factors, which illustrates their positive influence on the vegetation. Our study helps to better understand the long-term vegetation variations under the warm–wet tendency, which provides an important scientific basis for net primary production (NPP) variations and the carbon cycle in Xinjiang.
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