地球信息科学学报 ›› 2015, Vol. 17 ›› Issue (3): 361-368.doi: 10.3724/SP.J.1047.2015.00361

• • 上一篇    下一篇

天绘一号卫星影像的平原绿化提取方法

尚珂1(), 于信芳2,*(), 岳彩荣1, 王乾坤1, 王正兴2   

  1. 1. 西南林业大学林学院,昆明 650224
    2. 中国科学院地理科学与资源研究所 资源与环境信息系统国家重点实验室,北京 100101
  • 收稿日期:2014-07-09 修回日期:2014-09-10 出版日期:2015-03-10 发布日期:2015-03-17
  • 通讯作者: 于信芳 E-mail:shang_ke@sina.cn;yuxf@igsnrr.ac.cn
  • 作者简介:

    作者简介:尚 珂(1988-),女,硕士生,研究方向为资源环境遥感。E-mail:shang_ke@sina.cn

  • 基金资助:
    中国科学院战略性先导科技专项“应对气候变化的碳收支认证及相关问题”(XDA05050102)

Study on Plain Afforestation Area Extraction with Mapping Satellite-1 Imagery

SHANG Ke1(), YU Xinfang2,*(), YUE Cairong1, WANG Qiankun1, WANG Zhengxing2   

  1. 1. The College of Forestry, Southwest Forestry University, Kunming 650224, China
    2. Institute of Geographic Science and Natural Resources Research, State Key Lab of Resources and Environmental Information System, Beijing 100101, China
  • Received:2014-07-09 Revised:2014-09-10 Online:2015-03-10 Published:2015-03-17
  • Contact: YU Xinfang E-mail:shang_ke@sina.cn;yuxf@igsnrr.ac.cn
  • About author:

    *The author: SHEN Jingwei, E-mail:jingweigis@163.com

摘要:

平原绿化是我国平原地区森林植被的主体,为生态环境建设提供了有力保障。但平原绿化分布零散,斑块面积小,不易被准确提取。本文以河南省封丘县为例,利用天绘一号卫星影像面向对象分类技术提取了平原绿化。在面向对象分类过程中,针对不同平原绿化信息选取不同的分割尺度和参数,建立影像对象的分割层次结构,确保农田林网、通道防护林、四旁防护林等平原绿化信息能够被准确分割。分类时通过构建隶属度函数,利用层与层之间的关系,子类继承父类的分类特征,在此基础上增加自己的特征,建立分类规则集,逐层提取绿化信息。本文共获取封丘县平原绿化面积152.51 km2,其中,农田林网36.09 km2,通道防护林21.29 km2,四旁防护林71.56 km2,片林23.57 km2。利用验证点数据,对分类结果进行精度评价,总体分类精度为93.50%,Kappa系数达到0.92。

关键词: 平原绿化, 天绘一号卫星, 多尺度分割, 面向对象

Abstract:

Plain afforestation refers to the non-crop vegetation in crop-dominated plain area. As the main forest vegetation it has provided favorable conditions for ecological environment construction. The plain afforestation in this paper mainly includes farmland shelterbelt, road shelterbelt, residence shelterbelt and wasteland shelterbelt. But due to their small patches, getting the information of plain afforestation requires high spatial resolution remote sensing imagery. And the different sizes of kinds of afforestation patches make it difficult to extract all of them at once. In addition, it is a problem, if they could be extracted all, to distinguish themselves from one another. Based on this point, the paper explores a more accurate object-oriented classification method based on Mapping Satellite-1 (MS1) imagery in Fengqiu County, Henan province, China. The innovation of this method lies in the selection of proper segmentation scale according to different kinds of plain afforestation. Build optimal segmentation levels to insure the farmland shelterbelt, road shelterbelt, residence shelterbelt and wasteland shelterbelt could be segmented from their background imagery completely. Then contrast and analyze the spectral and spatial characteristics of different afforestation to develop classification rule sets. The classification rule sets could be conveyed between levels and current class could inherit them from parent class. Then build membership function to extract the plain afforestation area hierarchically. The results showed that the plain afforestation area of Fengqiu is 152.51 km2. More specifically, the farmland shelterbelt area is 36.09 km2, the road shelterbelt area is 21.29 km2, the residence shelterbelt area is 71.56 km2, and the wasteland shelterbelt area is 23.57 km2. The classification accuracy is 93.50% and the Kappa coefficient is 0.92. It showed that the study have achieved fine classification results. And the results also verified the potential of object-oriented plain afforestation information extraction based on Mapping Satellite-1 (MS1) imagery. This method can provide a technical support for the area accurate estimation of plain afforestadion.

Key words: plain afforestation, Mapping Satellite-1, multi-scale segmentation, object-oriented