院报 ›› 2017, Vol. 34 ›› Issue (4): 144-150.DOI: 10.11988/ckyyb.20160051

• 信息技术应用 • 上一篇    

基于遥感和GIS的江苏滨海地区湿地信息提取及动态变化分析

张 健1,何祺胜2a,崔 同2b,师鹏飞2b,杨 涛2b   

  1. 1.太湖流域管理局 水文局,上海 200000;
    2.河海大学 a.地球科学与工程学院;
    b.水文水资源学院,南京 210098
  • 收稿日期:2016-01-18 出版日期:2017-04-01 发布日期:2017-04-10
  • 作者简介:张 健(1963-),男,安徽滁州人,高级工程师,主要从事水利信息化、水文水资源监测站网规划设计、建设管理工作,(电话)13816137585(电子信箱)zhangjiansdny@163.com。

Information Extraction and Dynamic Changes ofWetland in Jiangsu Coastal Area Based on RS and GIS

ZHANG Jian1, HE Qi-sheng2, CUI Tong3, SHI Peng-fei3, YANG Tao3   

  1. 1.Hydrology Bureau,Taihu River Basin Management Bureau,Shanghai 200000,China;
    2. School of Earth Sciences and Engineering,Hohai University,Nanjing 210098,China;
    3.College of Hydrology and Water Resources,Hohai University,Nanjing 210098,China
  • Received:2016-01-18 Online:2017-04-01 Published:2017-04-10

摘要: 掌握湿地分布及动态变化特征能够为更好地保护湿地提供科学依据。以江苏省滨海湿地为研究对象,对研究区1992年、2002年、2012年3个时期的遥感数据进行处理,利用最大似然法分类提取湿地信息,研究滨海地区的湿地信息、动态变化并对驱动因子进行分析。结果表明江苏滨海湿地总面积呈减少趋势,其中人工湿地所占比重增加了22.43%,自然湿地所占比重则相应减少,此外自然湿地呈现以獐茅、盐蒿群落大幅度减少以及米草先大范围扩散后相对稳定的趋势;在转移过程中,转入面积最高的是人工养殖塘,而转出率由光滩变成了浅海水域;滨海湿地变化驱动因素主要是人类活动影响。

关键词: 江苏滨海地区, 湿地, 信息提取, 动态变化, 遥感, GIS, 驱动因子

Abstract: Mastering the distribution and dynamic change characteristics of wetland could provide scientific basis for better protection of wetland. In this research we processed the remote sensing data of Jiangsu coastal wetlands in 1999, 2002, 2012 and employed maximum likelihood method to extract wetland information. On this basis we investigated the dynamic change of coastal wetland and analyzed the driving factors. Results showed that the total area of wetland in Jiangsu coastal area presented a declining trend. The proportion of artificial wetlands increased by 22.43%, and the proportion of natural wetlands decreased, accordingly. In addition, natural wetland presented a tendency that communities of Aeluropus littoralis and Artemisia halodendron reduced greatly, and Spartina experienced the process from widespread diffusion to relative stabilization. During the process of transfer, the biggest transfer-in area was artificial breeding pond, while the biggest transfer-out ratio changed from barren wetland to shallow waters. The main driving factor of coastal wetland change was the influence of human activities.

Key words: Jiangsu coastal area, wetland, information extraction, dynamic change, remote sensing, GIS(Geographic Information System), driving factors

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