测绘通报 ›› 2019, Vol. 0 ›› Issue (8): 130-134,157.doi: 10.13474/j.cnki.11-2246.2019.0267

• 自然资源监测 • 上一篇    下一篇

草原矿区长时序植被覆盖度变化趋势对比分析

李晶1, 崔绿园1, 闫萧萧1, 杨震1, 董金玮2, 邓晓娟1   

  1. 1. 中国矿业大学(北京)地球科学与测绘工程学院, 北京 100083;
    2. 中国科学院地理科学与资源研究所, 北京 100101
  • 收稿日期:2018-12-24 出版日期:2019-08-25 发布日期:2019-09-06
  • 作者简介:李晶(1975-),女,博士,教授,主要从事3S应用、土地利用与土地复垦、土地资源管理等方面的研究。E-mail:lijing@cumtb.edu.cn
  • 基金资助:
    中国科学院战略性先导科技专项(A类)(XDA19040301);"十三五"国家重点研发计划(2016YFC0501101-4);国家自然科学基金(41501564)

Comparative analysis of long-term trends on fraction of vegetation coverage in grassland mining area

LI Jing1, CUI Lüyuan1, YAN Xiaoxiao1, YANG Zhen1, DONG Jinwei2, DENG Xiaojuan1   

  1. 1. School of Geoscience and Surveying Engineering, China University of Mining and Technology(Beijing), Beijing 100083, China;
    2. Institute of Geographical Sciences and Resources, Chinese Academy of Sciences, Beijing 100101, China
  • Received:2018-12-24 Online:2019-08-25 Published:2019-09-06

摘要: 呼伦贝尔草原区生态脆弱,在人类活动和气候等因素影响下草原生态变化备受关注。本文以宝日希勒矿区及周边为研究区,应用1985-2015年Landsat年度最大合成NDVI数据,采用像元二分模型反演植被覆盖度;分别利用一元线性回归法和Sen+Mann-Kendall法对研究区植被覆盖度趋势和空间差异进行了对比分析。结果表明:两种方法得到的植被变化趋势基本一致,Sen+Mann-Kendall方法相较于一元线性回归法对植被覆盖度改善和退化反应更为敏感。研究结果有助于科学评价长时序煤炭开发活动对地表生态的影响并为长时序植被变化监测提供方法参考。

关键词: 植被覆盖度, 像元二分模型, 一元线性回归, Sen+Mann-Kendall, 草原矿区

Abstract: The Hulunbeier area is a famous grassland area in the world. The fragile ecology there has attracted much attention for the influence of human activities and climate factors. This paper takes the Baorixile coal mine area in the heart of Hulunbeier as the study area to analyze the long-term trends on fraction of vegetation coverage(FVC) by maximum value composite method based on NDVI data from 1985 to 2015. The two methods, linear regression and Sen+Mann-Kendall trend, are used to monitor the long-term tendency on FVC spatial and temporal variation. The results show that FVC change trends obtained by the two methods are basically the same. The Sen+Mann-Kendall method is comparatively more sensitive to the improvement and degradation of vegetation coverage than the one-dimensional linear regression method. The study and its results will do help on scientifically evaluating the impact of long-term coal mining and other human activities on land ecology and provide a reference for method choosing on long-term vegetation change monitoring.

Key words: fraction of vegetation coverage, pixel decomposition model, linear regression, Sen+Mann-Kendall, grassland mining area

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