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草业学报 ›› 2021, Vol. 30 ›› Issue (9): 1-14.DOI: 10.11686/cyxb2020398

• 研究论文 •    

基于近20年MODIS NDVI日数据的青海省草地资源动态监测及其对环境因子的响应

杨鑫1(), 曹文侠1, 鱼小军1, 汪海斌2, 郝媛媛1()   

  1. 1.甘肃农业大学草业学院,草业生态系统教育部重点实验室,甘肃 兰州 730070
    2.三江源国家公园黄河源园区国家公园管理委员会,青海 果洛 813599
  • 收稿日期:2020-08-24 修回日期:2020-12-14 出版日期:2021-08-30 发布日期:2021-08-30
  • 通讯作者: 郝媛媛
  • 作者简介:Corresponding author. E-mail: haoyy@gsau.edu.cn
    杨鑫(1996-),男,甘肃定西人,在读硕士。E-mail: yangxin163yx@163.com
  • 基金资助:
    国家自然科学基金青年基金项目(41907406);国家重点研发计划(2016YFC0501904);甘肃农业大学科技创新基金(GAU-KYQD-2018-23)

Dynamic monitoring of grassland resources and their responses to environmental factors in Qinghai Province based on analyses of daily MODIS NDVI data from the past 20 years

Xin YANG1(), Wen-xia CAO1, Xiao-jun YU1, Hai-bin WANG2, Yuan-yuan HAO1()   

  1. 1.College of Pratacultural Science,Gansu Agricultural University,Key Laboratory of Grassland Ecosystem,Ministry of Education,Lanzhou 730070,China
    2.The Administration Committee of Yellow River Source National Park,Three-river-source National Park,Guoluo 813599,China
  • Received:2020-08-24 Revised:2020-12-14 Online:2021-08-30 Published:2021-08-30
  • Contact: Yuan-yuan HAO

摘要:

草地植被遥感动态监测是明晰草地植被时空动态变化过程的重要手段,是探索植被对环境因子响应规律的有效依据。以MOD09GA为数据源,采用最大值合成、一元回归趋势分析、相关性分析等方法,分别从日、旬、月和年尺度探究了2000-2019年青海省草地植被归一化植被指数(NDVI)时空动态变化过程及其与环境因子(海拔、坡度、坡向、气温和降水)的响应关系,以期为黄河流域源头生态保护和高质量发展提供理论依据。结果表明:1)草地植被NDVI逐日变化趋势稳定;旬际波动以2010年为顶点,先增后减但整体向好,且返青期提前、最大值日期集中且推后;草地植被长势变好,生长期延长;多年平均NDVI从西北向东南逐渐升高。2)草地质量自东南向西北递减,优质草地以4500~5000 m为中心向两侧递减,普通草地随海拔增高先减后增再减,退化草地随海拔升高逐渐减少;各级草地面积随坡度增大及阴坡→阳坡→半阴半阳的坡向逐渐减小。3)2000-2015年降水及气温均上升,且气温上升更明显;降水和气温分别呈现自东南向西北递减和南北低中部高的格局;NDVI与降水相关性高于气温6.76%。

关键词: NDVI, MODIS, 时空动态变化, 环境因子, 青海省

Abstract:

Dynamic monitoring using remote sensing technologies is an important means to clarify the spatio-temporal dynamic changes in grassland vegetation, and an effective basis to explore the responses of grassland vegetation to environmental factors. Using MOD09GA data, we explored the spatio-temporal dynamic changes in grassland vegetation NDVI (normalized difference vegetation index) in Qinghai Province from 2000 to 2019 on various time-scales (e.g., daily, ten-day, monthly, annual) by conducting qualitative and quantitative analyses. The relationships between grassland vegetation and various environmental factors (elevation, slope, aspect, temperature and precipitation) were determined using the maximum value composite method, monadic regression trend analysis, and correlation analysis. The overall aim of this study was to provide a theoretical basis for ecological protection and the development of high-quality vegetation resources at the source of the Yellow River. The main results were as follows: 1) The daily change in the NDVI of grassland vegetation showed a stable trend. During the 20-year period, the 10-day fluctuation in NDVI increased, peaked in 2010, and then decreased, but the overall trend was an increase over time. In addition, the re-greening period became earlier and the peak date became concentrated and later, indicating that grassland grew better and its growth period was extended. The multi-year average NDVI gradually increased from northwest to southeast. 2) Grassland quality decreased from southeast to northwest. The area of high-quality grassland decreased at both sides of the study area, with the center at 4500-5000 m. The area of ordinary grassland decreased, then increased, then decreased with increasing elevation. The area of degraded grassland decreased with increasing elevation. The area of all types of grassland gradually decreased with increasing slope, and as the slope direction changed from shaded to sunny and to half-shaded and half-sunny. 3) From 2000 to 2015, both precipitation and temperature increased, with increases in temperature being more marked. Precipitation and temperature tended to decrease from southeast to northwest. Precipitation and temperature tended to be lower in the north and south and higher in the middle of the study area. The correlation between NDVI and precipitation was 6.76% higher than that between NDVI and temperature.

Key words: NDVI, MODIS, spatio-temporal dynamic changes, environmental factors, Qinghai Province