测绘通报 ›› 2018, Vol. 0 ›› Issue (12): 109-113.doi: 10.13474/j.cnki.11-2246.2018.0394

• 技术交流 • 上一篇    下一篇

山东省近10年植被覆盖度变化与气候因子相关性分析

宋鹏飞, 季民, 李刚   

  1. 山东科技大学, 山东 青岛 266590
  • 收稿日期:2018-03-12 修回日期:2018-05-26 出版日期:2018-12-25 发布日期:2019-01-03
  • 作者简介:宋鹏飞(1995-),女,硕士生,主要研究方向为地理信息系统软件开发及应用。E-mail:17852023510@163.com
  • 基金资助:
    国家自然科学基金(41471330)

Correlation Analysis of Vegetation Coverage Change and Climatic Factors in Shandong Province

SONG Pengfei, JI Min, LI Gang   

  1. Shandong University of Science and Technology, Qingdao 266590, China
  • Received:2018-03-12 Revised:2018-05-26 Online:2018-12-25 Published:2019-01-03

摘要: 为了分析近10年山东省植被覆盖度时空变化格局及其与气候因子的相关性,利用2005-2015年的MODIS/NDVI数据及降水和温度数据,结合重心模型,实现近10年山东省植被变化空间格局分析,并且使用克里金法对降水和温度数据进行空间插值,然后对2005-2015年内降水和温度对植被覆盖度的影响进行相关系数分析,最后从滞后期分析植被对降水和温度的滞后反映。研究结果显示,近10年来山东省植被盖度总体有明显的增长,降水和温度对植被生长的影响呈现出不同程度的正相关,并且温度对植被的影响大于降水对植被的影响,植被生长对降水、温度的响应表现出明显的时滞效应。

关键词: 山东省, 植被覆盖度, 气候因子, 相关性分析, 动态监测

Abstract: In order to analyze the temporal and spatial pattern of vegetation coverage change and its correlation with climatic factors in Shandong province in recent ten years, this paper utilized MODIS/NDVI data, precipitation data and temperature data from 2005 to 2015, combined the model of center of gravity to realize the spatial pattern analysis of vegetation changes in Shandong province in last decade. Kriging was used to interpolate the precipitation and temperature data, then, the correlation coefficient analysis of the influence of precipitation and temperature on the vegetation cover during 2005 to 2015 was carried out. Finally, we analyzed the lagging response of vegetation to precipitation and temperature. The results show that there is a significant increase in vegetation coverage in Shandong province in recent ten years, precipitation and temperature have different degrees of positive correlation with vegetation growth, and the impact of temperature on vegetation is greater than the impact of precipitation on vegetation. Vegetation growth on the precipitation and temperature response showed significant lag effect.

Key words: Shandong province, vegetation coverage, climatic factor, correlation analysis, dynamic monitoring

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