粗糙集理论进行遥感图像监督分类的样本质量评价的研究(英文)     

Yong Ge  Hexiang Bai  Sanping Li  Deyu Li 《地球空间信息科学学报》2008,11(2):95-102

In the supervised classification process of remotely sensed imagery, the quantity of samples is one of the important factors affecting the accuracy of the image classification as well as the keys used to evaluate the image classification. In general, the samples are acquired on the basis of prior knowledge, experience and higher resolution images. With the same size of samples and the same sampling model, several sets of training sample data can be obtained. In such sets, which set reflects perfect spectral characteristics and ensure the accuracy of the classification can be known only after the accuracy of the classification has been assessed. So, before classification, it would be a meaningful research to measure and assess the quality of samples for guiding and optimizing the consequent classification process. Then, based on the rough set, a new measuring index for the sample quality is proposed. The experiment data is the Landsat TM imagery of the Chinese Yellow River Delta on August 8th, 1999. The experiment compares the Bhattacharrya distance matrices and purity index zl and △x based on rough set theory of 5 sample data and also analyzes its effect on sample quality.  相似文献   

黄土滑坡研究现状与设想   总被引：6，自引：0，他引：6  

许领  戴福初  闵弘 《地球科学进展》2008,23(3):236-242

黄土滑坡因其危害大、分布广成为近年工程地质研究热点问题。首先对黄土滑坡类型划分进行了讨论,基于滑坡物质组成及主滑面发育位置的黄土滑坡分类方案反映了我国黄土滑坡的主控因素,各类滑坡活动特征明确,建议将其作为黄土滑坡分类的首选方案。对黄土滑坡的发生、滑动机制以及滑坡液化机制进行了评述,并就两类典型液化型黄土滑坡滑动模式、进一步研究思路进行了讨论。对地震诱发黄土滑坡进行了专门的述评。最后,对今后黄土滑坡研究提出了几点设想。  相似文献   

“深空大地测量导论”课程建设和教材编写的思考     

魏二虎  程晓晖  易慧  严韦 《测绘信息与工程》2008,33(5)

介绍了"深空大地测量学导论"课程教材编写的背景、阐述了"深空大地测量学导论"教材编写的基本思路、总结了"深空大地测量学导论"教材的编写的特色.  相似文献   

基于蚁群智能的遥感影像分类新方法   总被引：5，自引：0，他引：5  

刘小平  黎夏  何晋强  艾彬  彭晓鹃 《遥感学报》2008,12(2):253-262

智能式遥感分类是遥感研究的新热点.提出了一种基于蚁群智能规则挖掘(ant-miner)的遥感影像分类新方法.遥感数据各波段之间存在较强的相关性,这种相关性往往会导致分类产生误差.而ant-miner算法中的信息素是基于规则整体性能的,信息素的动态更新能有效地处理相关性较强的数据,所提供的正反馈信息能纠正启发式函数缺陷所造成的错误.因此,蚁群智能算法应用于遥感分类具有一定的优势.将该方法用于广州市地区的遥感影像,取得了较好的分类结果.并与See5.0决策树方法及最大似然方法(MLH)进行了对比研究,实验结果表明,蚁群智能算法分类精度比后两者的分类精度更高.  相似文献   

基于语义的地理信息分类体系对比分析     

张雪英  闾国年 《遥感学报》2008,12(1):9-14

地理信息分类体系之间的语义不一致性,被认为是影响地理信息系统实现在语义层次上信息共享的最大障碍.首先,本文在阐述中国地理信息分类体系之间参照模式的基础上,提出了一种基于语义的地理信息分类体系对比分析方法.其次,对中国现行的几种地理信息标准分类体系进行了详细的对比分析.最后,为中国地理信息分类体系的编制和修订提出了一些建议.  相似文献   

遥感影像特征提取与选择及在影像分类中的应用     

秦永  宋伟东 《测绘科学》2008,33(1):176-178,199

利用模式识别中特征提取和特征选择的相关理论对遥感影像的纹理特征进行遴选和变换处理,得到描述纹理的二次特征。实验证明这些新特征能够提高影像分类精度和分类效率。  相似文献   

史前连续文化聚落的决策树分类挖掘研究——以郑州-洛阳地区为例     

毕硕本  闾国年  陈济民 《测绘科学》2008,33(2):161-164

利用C4.5决策树分类算法和GIS组件Super Map Objects,开发实现了基于连续文化序列的空间数据挖掘系统,运用此系统对郑州-洛阳地区史前四个连续文化时期的聚落进行了数据挖掘,提取了聚落遗址面积的分类规则,并根据这些分类规则和聚落的空间分布情况对四个文化时期的I级聚落进行对比分析,得出了I级聚落的空间分布特点,即I级聚落中的一些特大面积的聚落朝着中心聚落的方向发展。  相似文献   

基于LBV变换的遥感影像多步骤分类法研究   总被引：1，自引：0，他引：1  

彭笃明  张安定  李德一  米姗姗 《测绘科学》2008,33(3):56-58

面对与日俱增的遥感数据,如何快速准确地进行影像分类成为遥感领域亟待解决的问题。本文在前人的基础上提出了一种基于LBV变换的遥感影像多步骤分类方法。L:地物的总辐射水平,集中反映了裸地的信息;B:地物的可见-红外光辐射平衡,是地面水分状况和水体存在的一个良好指标;V:地物辐射随波段变化的方向和速度向量,能集中反映地面植被状况。多步骤分类法遵循由易到难的原则,能克服类别之间的互相影响,从而提高分类精度。文章结合LBV变换和多步骤分类法的优点对影像进行了分类,结果表明该方法简单易行,且能达到良好的分类精度。  相似文献   

遥感图像线性影纹理解专家系统设计与实现     

李百寿  秦其明  许军强  张万峰  姚云军 《测绘科学》2008,33(2):167-169,109

线性影纹信息是遥感图像中的一类重要信息,线性影纹信息自动提取是遥感图像智能解译的重要研究领域。笔者采用基于特征对象的专家系统技术来完成线性影纹信息的简单类别提取,设计并实现了线性影纹理解专家系统;阐明了系统结构,解译规则获取、表达,基于消息的不确定性推理机及解释机的设计;最后利用系统做了线性影纹类别提取实验,结果表明基于特征对象的专家系统用于线性影纹类别自动提取是切实可行的,并具有较高的提取精度。  相似文献   

A framework of region-based spatial relations for non-overlapping features and its application in object based image analysis   总被引：2，自引：0，他引：2  

Yu Liu  Qinghua Guo  Maggi Kelly   《ISPRS Journal of Photogrammetry and Remote Sensing》2008,63(4):461-475

Object based image analysis (OBIA) is an approach increasingly used in classifying high spatial resolution remote sensing images. Object based image classifiers first segment an image into objects (or image segments), and then classify these objects based on their attributes and spatial relations. Numerous algorithms exist for the first step of the OBIA process, i.e. image segmentation. However, less research has been conducted on the object classification part of OBIA, in particular the spatial relations between objects that are commonly used to construct rules for classifying image objects and refining classification results. In this paper, we establish a context where objects are areal (not points or lines) and non-overlapping (we call this “single-valued” space), and propose a framework of binary spatial relations between segmented objects to aid in object classification. In this framework, scale-dependent “line-like objects” and “point-like objects” are identified from areal objects based on their shapes. Generally, disjoint and meet are the only two possible topological relations between two non-overlapping areal objects. However, a number of quasi- topological relations can be defined when the shapes of the objects involved are considered. Some of these relations are fuzzy and thus quantitatively defined. In addition, we define the concepts of line-like objects (e.g. roads) and point-like objects (e.g. wells), and develop the relations between two line-like objects or two point-like objects. For completeness, cardinal direction relations and distance relations are also introduced in the proposed context. Finally, we implement the framework to extract roads and moving vehicles from an aerial photo. The promising results suggest that our methods can be a valuable tool in defining rules for object based image analysis.  相似文献