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东洞庭湖湿地生态系统健康状态与水位关系研究
引用本文:杨波,廖丹霞,李京,蒋卫国,Claudia Kuenzer,周斌.东洞庭湖湿地生态系统健康状态与水位关系研究[J].长江流域资源与环境,2014,23(8):1145.
作者姓名:杨波  廖丹霞  李京  蒋卫国  Claudia Kuenzer  周斌
作者单位:(1. 湖南师范大学资源与环境科学学院,湖南 长沙 410081;2. 北京师范大学民政部/教育部减灾与应急管理研究院,北京 100875;3. 德国宇航中心遥感数据中心,巴伐利亚,韦斯林,德国 82234;4. 杭州师范大学遥感与地球科学研究院,浙江 杭州 310000
基金项目:国家自然科学基金项目(41171342);湖南省高校创新平台开放基金项目(10K042);湖南省自然科学基金项目(10JJ3022);杭州师范大学遥感与地球科学研究院开放基金资助项目(PDKF2010YG08)
摘    要:基于CBERS卫星遥感影像数据,以东洞庭湖国家级自然保护区为研究区,通过光谱特征分析建立决策树分类模型,提取东洞庭湖湿地的地物类型。以生态系统健康理论为基础,依据东洞庭湖湿地的特点,综合湿地生产力、组织结构、弹性和功能4个方面,建立湿地生态系统健康状态评价指标体系和评价模型,利用GIS技术,分析东洞庭湖湿地在2000~2006年10个时相的生态系统健康状态。结合城陵矶水文站的水位数据,探讨了东洞庭湖湿地健康状态与城陵矶水位之间的相关性,并利用2007年两个时相的数据进行检验。研究结果表明:东洞庭湖湿地健康状态与城陵矶水位之间存在着较大的相关性,当城陵矶水位达到30 m左右时,东洞庭湖湿地健康状态达到最佳值

关 键 词:东洞庭湖湿地  生态系统  健康状态评价  水位

RELATIONSHIP BETWEEN WATER LEVEL AND WETLAND ECOSYSTEM HEALTH STATE IN EAST DONGTING LAKE
YANG Bo,LIAO Dan xia,LI Jing,,JIANG Wei guo,Claudia Kuenzer,ZHOU Bin.RELATIONSHIP BETWEEN WATER LEVEL AND WETLAND ECOSYSTEM HEALTH STATE IN EAST DONGTING LAKE[J].Resources and Environment in the Yangtza Basin,2014,23(8):1145.
Authors:YANG Bo  LIAO Dan xia  LI Jing    JIANG Wei guo  Claudia Kuenzer  ZHOU Bin
Institution:(1.College of Resource and Environment Science,Hunan Normal University,Changsha 410081,China;2.Academy of Disaster Reduction and Emergency Management,the Ministry of Civil Affairs and the Ministry of Education,Beijing 100875,China;; 3.German Remote Sensing Data Center,Oberpfaffenhofen 82234,Wessling,Germany;; 4.Institute of Remote Sensing and Earth Sciences,Hangzhou Normal University,Hangzhou 310000,China)
Abstract:Taking East Dongting Lake National Nature Reserve as the research region, this paper was purposed to explore the correlation between the wetland ecosystem health state in East Dongting Lake and the water level of Chenglingji Hydrometric station. By analyzing the spectral features of remotely sensed images such as the normalized differential vegetation index, band reflectance, the brightness and wetness after ENVI Tasseled Cap Transform, the model of decision tree for classification was built. And the distribution area of different features in East Dongting Lake including water, mudbank, reed, poplar, shrubland and field were extracted out, based on CBERS remotely sensed images of 12 phases. Then, as the wetland ecosystem has productivity, stability and ability of self adjusting, the wetland ecosystem health state evaluation model was established by integrating productivity, structure, elasticity with function, in which the productivity element reflects the primary vegetation productivity of wetland, the structure element reflects the structural integrity and landscape diversity of the wetland system, the elasticity element reflects the stability and self regulation of the wetland, and the function element reflects the water storage capacity of wetland. On the basis of the theory of ecosystem health and the characteristics of East Dongting Lake wetland, the average normalized differential vegetation index was chosen as the index of wetland productivity, the wetland structure element was measured by landscape diversity index, landscape shape index and patch density index,and the average elasticity was chosen as the index of wetland elasticity, as well as the water area was chosen as the index of wetland function. So the evaluation indexes system of wetland ecosystem health state was established. By combining remote sensing and GIS technology, special information of each wetland ecosystem health evaluation index was extracted from different data, and the standardization value of evaluation indexes were obtained through standardized analysis. Then, based on the standardization value of each evaluation index, the wetland ecosystem health state evaluation model was used to analyze the ecosystem health state of 10 phases from 2000 to 2006 in East Dongting Lake wetland. 〖JP2〗Subsequently, the water level data of Chenglingji Hydrometric station was integrated into the study, and the correlation between the wetland ecosystem health state in East Dongting Lake and the water level was discussed. The results show that the wetland productivity was negatively correlated with water level, the correlation between the wetland structure and water level was indistinctive, and the wetland elasticity was positively correlated with water level, as well as the wetland function. By integrating productivity, structure, elasticity and function of wetland, we came to the conclusion that the relationship between wetland ecosystem health state of East Dongting Lake and water level of Chenglingji Hydrometric station tended to be quadratic polynomial, and the East Dongting Lake wetland ecosystem health state would be the best when Chenglingji water level was about 30 meters deep. Finally, the data of East Dongting Lake wetland of two phases in 2007 was used to inspect the correlation between wetland ecosystem health state and water level, and the inspection result showed that the correlation was considerably accurate
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