基于国产GF-2遥感影像的大麻地块提取方法研究——以安徽省六安市苏埠镇为例  

Study on the extraction method of cannabis plot based on China-made GF-2 remote sensing image-taking Subu town in Anhui Province as an example

作　　者：张飞飞[1] 杨光[1] 田亦陈[1] 

机构地区：[1]中国科学院遥感与数字地球研究所,北京100101

出　　处：《安徽农业大学学报》2016年第4期582-586,共5页Journal of Anhui Agricultural University

基　　金：高分公安重要地区遥感应用示范系统(一期)项目(01-Y30B16-9001-14/16)资助

摘　　要：针对传统的基于像元的分类方法提取大麻地块结果存在较为破碎、精度较低的问题,以国产"高分二号"(GF-2)4m的多光谱遥感影像为数据源,在安徽省六安市苏埠镇选取了一个研究区,使用基于规则集的面向对象的方法实现了大麻地块的精确提取。首先,对研究区预处理过的GF-2遥感影像进行多尺度分割,在多尺度分割结果的基础上,确定提取大麻地块的最优分割尺度。其次,针对不同地物类型选取样本对象生成光谱曲线,分析大麻地块与其他地物类型的异同点,并基于光谱分析结果构建规则集最终实现大麻地块的提取。最后,将基于规则集的面向对象分类结果和基于像元分类(监督分类)的结果进行对比分析。结果表明,基于规则集的面向对象方法可以有效的提取出研究区内的大麻地块,精度可以达到91.09%,解决了传统基于像元分类方法提取大麻地块结果较为破碎的问题。In this study, the object-oriented classification method was used to extract cannabis plot so as to resolve the broken problem of the traditional classification method based on pixel. China-made GF-2 remote sensing images with a 4x4 m resolution were obtained in Subu town of Anhui Province. Firstly, multi-scale seg- mentation of GF-2 remote sensing image in the study area was made, and the optimal segmentation scale was de- termined on the basis of multi-scale segmentation results. Secondly, a spectral curve according to the different feature type samples was generated. The similarities and differences between cannabis plot and other types Of sur- face features were analyzed, and a rule set based on the results of spectral analysis was established to achieve the final extraction. Finally, the classification results of object-oriented classification method based on rule set and traditional method based on pixel were compared. The experimental results showed that the object-oriented classi- fication method based on rule set can extract cannabis plots effectively and solve the broken problem of traditional classification method based on pixel. The accuracy can be reached to 91.09%.

关 键 词：高分二号 大麻 最优分割尺度 监督分类 面向对象分类 

分 类 号：TP79[自动化与计算机技术—检测技术与自动化装置]