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中国农学通报 ›› 2019, Vol. 35 ›› Issue (15): 85-90.doi: 10.11924/j.issn.1000-6850.casb18030027

所属专题: 农业气象

• 资源 环境 生态 土壤 气象 • 上一篇    下一篇

张掖市归一化植被指数与气候变化的相关性研究

王锦波1,杨晓玲2,张义海2,王小伟1   

  1. 1.甘肃省陇南市气象局;2.甘肃省武威市气象局
  • 收稿日期:2018-03-06 修回日期:2018-05-17 接受日期:2018-06-22 出版日期:2019-05-28 发布日期:2019-05-28
  • 通讯作者: 杨晓玲
  • 基金资助:
    国家自然基金“半干旱区春小麦农田干旱解除的降雨过程调控机制”(41775107),“气温升高和降水波动对半干旱区春小麦协同影响” (41305134)。

Correlation Between NDVI and Meteorological Factors in Zhangye

  • Received:2018-03-06 Revised:2018-05-17 Accepted:2018-06-22 Online:2019-05-28 Published:2019-05-28

摘要: 为了研究张掖市气候变化与植被覆盖关系,选择张掖市1982—2015年逐月NASA GIMMS归一化植被指数(NDVI)与气温、降水资料,运用统计学方法和Pearson相关系数法,分析了NDVI与气温、降水的年、季节变化趋势以及NDVI与气候因子气温、降水的相关性。结果表明:年、各季节NDVI呈增长趋势,夏季增长最快;年、各季节气温呈上升趋势,夏季上升最快;年降水量呈增长趋势,春、夏季降水量呈减少趋势,秋、冬季降水量呈增加趋势,秋季增多最大。年和春、夏、秋三季气温与年NDVI显著相关,相关系数通过了?=0.01的显著性水平检验,冬季气温与NDVI呈弱负相关。年、各季节降水量与NDVI相关性都不显著。植被生长对气候变化存在滞后效应,春、夏、秋三季气温与下一季NDVI的相关性显著,冬季相关性不显著。各季节降水量与下一季NDVI相关性不显著。

关键词: 硝酸铵磷, 硝酸铵磷, 黄瓜幼苗, 生长, 养分吸收

Abstract: The aim is to research the correlation between climate change and vegetation cover. Based on the data of monthly NASA GIMMS normalized difference vegetation index(NDVI), temperature and precipitation of Zhangye from 1982 to 2015, annual and seasonal variation trend of NDVI, temperature and precipitation and correlation between NDVI and climatic factors including temperature and precipitation were analyzed by using statistical methods and Pearson correlation coefficient method. The results showed that the yearly and seasonal NDVI revealed an increasing tendency, and the growth was the fastest in summer. Yearly and seasonal temperature showed a rising tendency, and the rise was the fastest in summer. Yearly precipitation revealed an increasing tendency, the precipitation in spring and summer showed a decreasing trend, and the precipitation in autumn and winter showed an increasing trend, and the growth was the largest in autumn. Annual, spring, summer and autumn temperature presented significant correlations with yearly NDVI, and the correlation coefficients passed α = 0.01 significance test. Winter temperature showed a weak negative correlation with NDVI. There were no significant correlations between annual and seasonal precipitation and NDVI. The climate change had a lagging effect on vegetation growth. Three seasons’(spring, summer and autumn) temperature had significant correlations with the next seasonal NDVI, and the correlation was not significant in winter. There was no significant correlation between seasonal precipitation and the next seasonal NDVI.