| 基于高分六号红边特征的面向对象桉树人工林信息提取 |
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| 引用本文： | 王子彦,任超,梁月吉,施亚杰,李现广,张胜国.基于高分六号红边特征的面向对象桉树人工林信息提取[J].测绘通报,2021,0(6):6-11. |
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| 作者姓名： | 王子彦 任超 梁月吉 施亚杰 李现广 张胜国 |
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| 作者单位： | 1. 桂林理工大学测绘地理信息学院, 广西 桂林 541004;2. 广西空间信息与测绘重点实验室, 广西 桂林 541004 |
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| 基金项目： | 国家自然科学基金（42064003）；广西中青年教师基础能力提升项目（2020KY06031） |
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| 摘 要： | 有效监测桉树林空间分布对区域生态环境保护及有关部门的统筹决策具有重要指导意义。本文在现有研究的基础上，以国内首个提供红边波段的多光谱高分六号（GF-6）卫星影像为数据源，选取广西鹿寨县为典型研究区域，结合光谱特征、植被指数特征和红边特征，设计不同特征组合分类方案，采用面向对象多尺度分割方法，对不同尺度层分别构建隶属度函数和CART决策树模型以进行分类提取桉树人工林信息。试验结果表明，红边特征在CART决策树模型构建中具有重要影响，融入GF-6红边特征能有效提高桉树人工林分类提取精度，总体精度达到91.75%，相比仅采用传统波段和植被指数的分类方案，精度提高了11.25%。本文研究结果在利用国产卫星红边波段识别提取桉树人工林方面具有重要的理论意义和实用价值。
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| 关 键 词： | 高分六号卫星 红边波段 桉树人工林 CART决策树 精度评价 |
| 收稿时间： | 2021-01-25 |
Object-oriented eucalyptus plantation forest information extraction based on the red-edge feature of GF-6 |
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| WANG Ziyan,REN Chao,LIANG Yueji,SHI Yajie,LI Xianguang,ZHANG Shengguo.Object-oriented eucalyptus plantation forest information extraction based on the red-edge feature of GF-6[J].Bulletin of Surveying and Mapping,2021,0(6):6-11. |
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| Authors: | WANG Ziyan REN Chao LIANG Yueji SHI Yajie LI Xianguang ZHANG Shengguo |
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| Institution: | 1. College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China;2. Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin 541004, China |
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| Abstract: | It’s very important to monitor the spatial distribution of eucalyptus forests, especially for regional ecological environment protection and the government’s decision-making. Based on existing research, this paper uses multispectral GF-6 image as the data source, the first satellite in China to provide red-edge bands. In this paper, selecting Luzhai county in Guangxi as a typical research area, combines spectral characteristics, vegetation index characteristics and red-edge characteristics to design different classification schemes. A class hierarchy is established by object-oriented multi-scale segmentation method. According to the different scale levels, membership functions and CART decision tree models are used to classify eucalyptus plantation information. The experiment results shows that the red-edge feature had a significant influence on the construction of the CART decision tree model. The integration of the GF-6 red-edge features could effectively improve eucalyptus plantations’ classification accuracy, with an overall accuracy of 91.75%. Comparing with the classification scheme that only using the traditional bands and vegetation indexs, the classification accuracy has been improved by 11.25%. The research results have important theoretical significance and practical value in the identification of eucalyptus plantations using red-edge bands of Chinese satellite. |
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| Keywords: | GF-6 satellite red-edge bands eucalyptus plantation forest CART decision tree accuracy evaluation |
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