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草业学报 ›› 2013, Vol. 22 ›› Issue (4): 239-246.DOI: 10.11686/cyxb20130429

• 研究论文 • 上一篇    下一篇

基于CSCS方法的甘南自然植被NDVI时空分布特征研究

修丽娜,冯琦胜,梁天刚*   

  1. 草地农业生态系统国家重点实验室 兰州大学草地农业科技学院,甘肃 兰州 730020
  • 出版日期:2013-08-20 发布日期:2013-08-20
  • 通讯作者: E-mail:tgliang@lzu.edu.cn
  • 作者简介:修丽娜(1988-),女,山东海阳人, 在读硕士。E-mail:xiuln11@lzu.edu.cn
  • 基金资助:
    国家自然科学基金项目(30972135),教育部高等学校科技创新工程重大项目培育资金项目(708089),公益性行业(农业)科研专项(201203006-8)和兰州大学中央高校基本科研业务费专项资金(lzujbky-2013-201)资助。

A study on spatial and temporal distribution characteristics of NDVI
for natural vegetation in Gannan based on CSCS

XIU Li-na, FENG Qi-sheng, LIANG Tian-gang   

  1. State Key Laboratory of Grassland Agro-ecosystems, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730020, China
  • Online:2013-08-20 Published:2013-08-20

摘要: 基于综合顺序分类系统(CSCS)模型,利用地理信息系统技术手段,模拟出甘南潜在自然植被类型图,并且结合国际地圈生物圈计划(IGBP)土地覆盖数据集,制作出甘南残存潜在自然植被分布图和残存潜在自然植被典型区分布图。在此基础上,利用2001-2010年MODIS数据分别研究了残存潜在自然植被分布区及其典型区的NDVI年度和月度变化特征。研究结果表明,1) 甘南残存潜在自然植被分布区面积达33 940 km2,占甘南总土地面积的92.53%;2) 残存潜在自然植被典型区主要分布在玛曲县、碌曲县及迭部县部分地区和夏河县北部,在舟曲、卓尼和临潭县分布较少;3) 甘南地区NDVI在2001-2010年期间都呈现出上升趋势,7种植被类型的月最大值出现在7-9月。

Abstract: Based on the comprehensive and sequential classification system (CSCS) model and geographic information systems approach, a potential natural vegetation (PNV) type map was simulated, and the remaining PNV with their typical area distribution maps in Gannan were made from a combination of land cover data sets from the International Geosphere-Biosphere Programme (IGBP). The monthly and yearly changes of the NDVI (normalized different vegetation index) values in the remaining PNV and their typical areas were analyzed using remote sensing data of MODIS. 1) The remaining PNV distribution covers an area of 33 940 km2, accounting for 92.53% of the total land area in Gannan; 2) The typical areas are located in parts of Maqu, Luqu, Diebu Counties, and the northern Xiahe County, while the remainder have a scattered distribution in Zhouqu, Zhuoni, and Lintan Counties; 3) NDVI values of the seven natural vegetation types showed increasing trends with the maximum NDVI values from July to September.

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