地理科学进展 ›› 2016, Vol. 35 ›› Issue (10): 1269-1278.doi: 10.18306/dlkxjz.2016.10.010

• 研究论文 • 上一篇    下一篇

长白山自然保护区生态环境质量的遥感评价

王士远(), 张学霞*(), 朱彤, 杨维, 赵静瑶   

  1. 北京林业大学水土保持学院,北京 100083
  • 出版日期:2016-10-28 发布日期:2016-10-26
  • 通讯作者: 张学霞 E-mail:wangyuanhpu@163.com;xuexiazh@yeah.net
  • 作者简介:

    作者简介:王士远(1990-),男,河南驻马店人,硕士生,研究方向为3S技术集成开发与应用,E-mail: wangyuanhpu@163.com

  • 基金资助:
    国家科技支撑计划项目(2015BAD07B03);国家重点研究基础发展计划973项目(2012CB955403);国家自然科学基金项目(41571154)

Assessment of ecological environment quality in the Changbai Mountain Nature Reserve based on remote sensing technology

Shiyuan WANG(), Xuexia ZHANG*(), Tong ZHU, Wei YANG, Jingyao ZHAO   

  1. School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China
  • Online:2016-10-28 Published:2016-10-26
  • Contact: Xuexia ZHANG E-mail:wangyuanhpu@163.com;xuexiazh@yeah.net
  • Supported by:
    National Science and Technology Support Program of China, No.2015BAD07B03;National Basic Research Program of China (973 Program), No.2012CB955403;National Natural Science Foundation of China, No.41571154

摘要:

人类的生存质量与生态环境密切相关,利用遥感技术可快速地进行生态环境质量评价,为区域生态环境的治理、改善以及发展规划提供重要参考。本文以长白山自然保护区为例,选取1995、2007年Landsat5 TM影像和2015年Landsat8 OLI影像,反演得到能反映生态环境的绿度、湿度、热度和干度等指标,利用主成分分析法,依据新型遥感生态指数RSEI对长白山自然保护区1995-2015年的生态环境进行评价,结果表明:①绿度、湿度指标对区域生态环境起正向作用,热度、干度指标对区域生态环境起负向作用,且湿度对生态环境影响较大;②该区域1995、2007、2015年生态指数优良等级所占比例依次为49.520%、66.508%、76.189%,同时RSEI等级变差、不变、变好的比例分别为3.945%、55.598%、40.457%。生态环境质量整体不断改善,说明长白山自然保护区的天然林资源保护工程以及一系列生态保育措施起到了一定作用;而天池周边生态环境质量有所下降可能与旅游活动的快速发展有关;③逐步回归分析的结果表明,所选的各指标均为指示生态环境质量的关键指标;而裸露、干化地表的治理则是改善生态环境质量的关键。

关键词: 生态环境质量, 遥感生态指数, 主成分分析, 长白山自然保护区

Abstract:

The well-being of the human race is closely related to the ecological environment. In the past few decades, indicators retrieved from remote sensing data have been increasingly more widely applied to ecological environment evaluation for their advantages of spatial visualization, and remote sensing technology offers important reference to regional ecological environment management, improvement, and development planning by quickly assessing regional ecological environment quality. Remote sensing ecological index (RSEI), constructed by four indicators including green degree, humidity degree, heat degree, and dry degree retrieved from remote sensing images, can reflect ecological environment status. RSEI is based on real-time remote sensing images and accordingly more capable of quick evaluation of temporal and spatial changes of ecological environment quality. In this article, Landsat5 TM images from 1995 and 2007 and Landsat8 OLI images from 2015 were used as data source to retrieve values of the four indicators to construct the RSEI by the principal component analysis method, and Changbai Mountain Nature Reserve ecological environment quality from 1995 to 2015 was evaluated using the RSEI. The result shows: (1) The green degree and humidity degree have an positive effect on promoting the ecological environment quality of the region while the heat degree and dry degree have a restraining effect on the regional ecological environment quality, and the humidity degree is more significant than the other three indicators. (2) In this region, the proportion of excellent and good RSEI classes accounted for 49.5%, 66.5%, and 76.2% of the total area in 1995, 2007, and 2015. Meanwhile, the degenerated, unchanged, and improved RSEI classes were 3.9%, 55.6%, and 40.5% of the total area respectively, indicating that the overall ecological environment quality has gradually improved. To some extent this is attributed to the Natural Forest Resources Protection Project and a series of ecological conservation measures taken in the Changbai Mountain Nature Reserve area. Although the overall ecological environment quality of the study area has gradually improved, the ecological environment quality around Tianchi has declined. This area has a relatively fragile ecological environment and suffers from high intensity of tourism activities. The decline in ecological environment quality may be attributed to the increasingly intense tourism activities. (3) The stepwise regression analysis results show that each of the selected indicators is key to indicating the ecological environment quality, and the model prediction result reveals that the control of barren and dry surfaces is a critical step for improving the ecological environment quality.

Key words: ecological environment quality, remote sensing ecological index, principal component analysis, Changbai Mountain Nature Reserve