山东农业大学学报（自然科学版）2016，Vol.47Issue(5)：705-709,715,6.DOI:10.3969/j.issn.1000-2324.2016.05.013
基于面向对象的濒海湿地脆弱区土地利用/覆被信息精细提取
Precise Extraction of Land Use/Cover Information in the Fragile Coastal Wetland Based on Object-oriented Method
摘要
Abstract
Precise extraction of the land use/cover information is of great significance for the ecological stability and the economic sustainable development in the fragile coastal wetland region. This paper took the Yellow River Entrance as the study area to extract the land use/cover information accurately by Object-oriented technology based on the Landsat 8 image. Based on the establishment of the detailed land use/cover classification system, we got the preliminary land use/coverage classification results with the object-oriented method which was based on sample. However, the classification results showed this classification model could accurately extract all land types except paddy fields, lotus root pools and Medicago. To solve this problem, combining the rule-based and example-based object-oriented method was used to complete high accuracy extraction of land use/coverage information. Results indicated that the paddy fields and lotus root pools got more accurate by setting the area and rectangular attributes rules, at the same time, other land types precision also have been improved, this classification model produced an overall accuracy of 94.93% and a Kappa value of 0.94 which was 38.56%more than the maximum likelihood method. Therefore, the research demonstrated that this method combining the rule-based and example-based object-oriented methods could achieve high accuracy classification of the land use/coverage information in the wetland.关键词
湿地/Landsat 8影像/土地利用/覆被类型/精细提取Key words
Wetland/Landsat8 image/land use/land cover type/precise extraction分类
信息技术与安全科学引用本文复制引用
张贵花,王瑞燕..基于面向对象的濒海湿地脆弱区土地利用/覆被信息精细提取[J].山东农业大学学报（自然科学版）,2016,47(5):705-709,715,6.基金项目
山东省高等学校科技计划项目(J11LC11) （J11LC11）
山东省教育厅科学技术项目(J11LC19) （J11LC19）
山东省自然科学基金(ZR2009BQ017) （ZR2009BQ017）
山东省博士后创新项目专项资金资助(201003026) （201003026）
国家自然科学基金(41271235) （41271235）
山东省优秀青年科学家科研奖励基金项目(BS2013NY004) （BS2013NY004）
