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作 者:宋怀荣[1,2] 苏国辉 孙记红[1,2] 魏合龙 林文荣[1,2] SONG Huairong;SU Guohui;SUN Jihong;WEI Helong;LIN Wenrong(Qingdao Institute of Marine Geology,China Geological Survey,Qingdao 266071,China;Key Laboratory of Coastal Wetland Biogeosciences,China Geological Survey,Qingdao 266071,China)
机构地区:[1]中国地质调查局青岛海洋地质研究所,青岛266071 [2]中国地质调查局滨海湿地生物地质重点实验室,青岛266071
出 处:《海洋地质前沿》2021年第12期75-82,共8页Marine Geology Frontiers
基 金:中国地质调查局项目(DD20190214,DD20191008)。
摘 要:掌握湿地景观分类及其动态变化能够有效监测湿地生态系统格局变化。选取江苏盐城国家级珍禽自然保护区核心区湿地,采用最大似然、CART决策树和随机森林的方法分别对该核心区进行信息提取,分析发现,随机森林方法的精确度最高(总体分类精度达91.02%,Kappa系数为0.89)。进而采用该方法针对整个江苏盐城滨海湿地进行景观信息提取,得到了1995、2006、2016年度的江苏盐城湿地景观分类(共分为6种类型),并通过转移矩阵分析了各类型的每年度变化情况,结果发现,江苏盐城湿地面积总体呈增长趋势,主要表现在水产养殖区向浅海区不断扩张,1995-2006年期间植被、建筑区和农作物面积都有所增长,2006-2016年期间基本保持稳定。To study wetland landscape and its dynamic changes can effectively monitor the changes in wetland ecosystem. In this paper, we selected the core wetland of the Yancheng National Rare Birds Nature Reserve in Jiangsu Province as a research focus, and used the methods of maximum likelihood, CART decision tree and random forest to extract information from the core area of the wetland. Our results suggest that the method of random forest has the highest accuracy. The overall classification accuracy is 91.02% with a Kappa coefficient up to0.89. The method of random forest is adopted as the mean to extract landscape information from the entire coastal wetland of Yancheng and obtained are the six landscape categories of wetland in 1995, 2006, and 2016 respectively. The annual changes of the six types of landscapes are analyzed by transfer matrix. The results show that the area of Yancheng wetland is increasing in an overall trend and the aquaculture areas is continuously expanding to shallow waters. Although the vegetation, construction areas and crop areas were all increased during the period of1995-2006, they had basically remained stable during the latter period of 2006-2016, especially the areas of nature reserves were kept unchanged.
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