• 研究论文 •

### 豫西山地植被NDVI及其气候响应的多维变化

1. 河南大学环境与规划学院,开封 475004
• 收稿日期:2016-10-23 修回日期:2017-01-24 出版日期:2017-04-20 发布日期:2017-05-04
• 作者简介:

作者简介：张静静（1991- ）,女,河南柘城人,博士研究生,主要从事山地资源与环境研究。E-mail:zhang1126@henu.edu.cn

• 基金资助:
国家自然科学基金项目（41671090,41401504）;国家重点基础研究发展计划项目（973计划）（2015CB452702）

### Multi-dimensional changes of vegetation NDVI and its response to climate in Western Henan Mountains

Jingjing ZHANG(), Hui ZHENG, Lianqi ZHU(), Yaoping CUI, Xiaodong ZHANG, Lupei YE

1. College of Environment and Planning, Henan University, Kaifeng 475004, Henan, China
• Received:2016-10-23 Revised:2017-01-24 Online:2017-04-20 Published:2017-05-04

Abstract:

Western Henan Mountains, the extent of Qinling Mountains in Henan province and the transition from subtropical to warm temperate zone, are sensitive to climate change. This study sought to analyze vegetation NDVI change and its response to climate change in this sensitive area in multi-dimensions because the multi-dimensional ecological unit analysis is conducive to vegetation protection and ecology restoration in mountain ecosystems. We firstly used S-G filtering algorithm to reconstruct the MODIS-NDVI time-series data from 2000 to 2013 and combined DEM, temperature and precipitation data in the study area; then we used statistical analyses (i.e., linear regression, correlation analysis, and so on) to study vegetation NDVI change and its response to climate variables (temperature and precipitation) in different terrain factors (elevation, slope, and aspect). The results showed that: (1) in 2000-2013, there was a significant growth of vegetation NDVI in the study area, and the growth rate was 0.041/10a. The finding suggested that, in general, the vegetation in the Western Henan Mountains was positively developed in this area. Meanwhile, the mean NDVI value increased with the increase of elevation, and then the trend became decreased; while it gradually increased as the slope increased. The mean NDVI value, however, had no significant differences in each aspect. (2) The recovery probability of vegetation in <1100 m regions was the highest, whereas the degradation probability in >1700 m regions was the highest. Regarding the slope, the recovery probability of vegetation in 10°~20° regions was the highest, while the degradation probability in 0°~5° regions was the highest. The variation of recovery (or degradation) probability of the aspect was not obvious somehow. (3) Vegetation in different terrains was affected by distinctive climate factors. Specifically, vegetation NDVI change at high elevations had stronger correlation with precipitation than with temperature, which indicated that the vegetation dynamics in this range was mainly affected by precipitation change. Inversely, vegetation NDVI change on different slopes had closer relationship with temperature than with precipitation. Not surprisingly, in different aspects there was little difference in terms of the response of vegetation NDVI to climate variables. (4) NDVI growth rates on the north slopes of sub-mountains, such as Xiaoshan, Xionger, and Funiu, were much higher than those on the south slopes. Moreover, the vegetation on the north slopes was more sensitive to precipitation change, whereas on the south slopes it was more sensitive to temperature change. All this echoes the importance of studying the response of local ecological environment to mountain ecosystems in transition zone under the background of global climate change.