辅助数据在面向对象分类方法中的应用——以密云水库上游为例  

Application of auxiliary data in the object-based classification method: a case study on the Miyun Reservoir area

作　　者：苑全治[1] 吴炳方[1] 张磊 李晓松[1] 曾源[1] 

机构地区：[1]中国科学院遥感与数字地球研究所数字地球重点实验室,北京100094

出　　处：《生态学报》2014年第24期7202-7209,共8页Acta Ecologica Sinica

基　　金：中国科学院战略性先导科技专项项目(XDA05050109);全国生态环境十年变化(2000-2010年)遥感调查与评估项目(STSN-01-00)

摘　　要：密云水库上游位于华北平原向蒙古高原的过渡带内,自然条件差异大,人类活动对该区域影响显著。因此,对该地区土地覆盖类型遥感监测方法的研究具有典型的指导意义。基于高分辨率遥感影像,着重探讨辅助数据在面向对象分类方法中的应用,对密云水库上游地区的土地覆盖进行分类提取。结果显示,研究区内共包含26类土地覆盖类型,其中落叶阔叶灌木林、落叶阔叶林、草丛以及旱地,这4种类型的面积占总面积的85%,是全区的主要土地覆盖类型。在分类时,采用多源异构辅助数据,研究了北方山区常绿针叶林、旱地等土地覆盖类型的识别方法,有效降低了"同物异谱"和"同谱异物"现象对分类精度的影响。The Miyun Reservoir area between the North China plain and the Mongolian plateau has various physical conditions and intensity of human disturbance. Thus,studying the method of monitoring the land cover of this area is important. On the basis of high-resolution remote sensing imagery,this article classified the land cover of the Miyun reservoir area and studied the application of auxiliary data in object-based classification method. The remote sensing data used were mainly high spatial-resolution images,including Rapid Eye and SPOT-5. Accurate geometric rectification was performed initially. To gain more object features for distinguishing the different classes more clearly,we referenced the digital elevation model and slope gradient data with spatial resolution of 25 m and the thematic map of the land use with a scale of 1∶10000. Multi-temporal HJ-1 imagery was added to separate the evergreen needle forests and the dry land. A total of 687 field samples were collected from the Miyun reservoir area for classification and precision testing. The e Cognition v8.7software was also used in this study. First,the images were segmented into different image objects according to the object features in the spectra,where several parameters are needed. In Rapid Eye,five bands with the same weight were used for segmentation. Choosing the segmentation scales and parameters of the shape and compactness is important. Through constant experiments,we found that the suitable segmentation scale was 45. The configuration of the shape parameter will determine the weight of the spectra in the segmentation. Given that the classification was mainly based on the spectral feature,we setthe shape parameter to 0.1; correspondingly,the spectra parameter was set to 0.9. The shape features of the image object included compactness and smoothness,which were both set to 0. 5 because of the complex shape of the land cover. The smoothness and compactness of the objects were almost equally important. We established the sample database after segmentat

关 键 词：面向对象 土地覆盖 密云水库上游 高分辨率 辅助数据 

分 类 号：P237[天文地球—摄影测量与遥感]