摘要
遥感影像高精度自动分类方法的实现是制约遥感数据应用的瓶颈之一。以知识和地理信息系统为支撑,进行湿地遥感影像的分类,并对各项分类方法的精度进行比较评价,从而为湿地遥感的分类方法提供依据。实验结果表明经辐射增强降噪处理后湿地边界更加明晰;而对于处于生长期的湿地影像,经过光谱增强缨帽处理后,明显提高了区分湿地亚类的精度。结合以上两种分类方法的优势,利用GIS技术对二者进行空间处理,取长补短,生成了湿地遥感影像分类图。实验证明基于3S技术的分类方法精度更高,是一种较好的湿地影像自动分类方法。
How to get high accuracy of classification by remote sensing image processing technology is one of the difficulties in applications of wetland data. The paper discusses the methods to enhance the accuracy of classification for the wetland of Zhalong. First we can noise reductions enhance and tasseled cap enhance to improve its accuracy. Then compare the classification results of original image with those of the other two enhance methods. The results are very similar, i.e., 83.91% of original image, 78.88% of noise reduction and 90.13% of tasseled cap respectively, checked by GPS sample points gained from fields, land cover data of 2000 and Kappa accuracy assessment. Each method has its own advantage in differentiating the classes, especially the accuracy in the wetland boundary after noise reduction enhance and the accuracy in the sub classes of wetland after tasseled cap enhance. But none of them is very satisfied. So based on knowledge and the technique of GIS, we can put the advantages of each methods together to gain an excellent result. The new method is the kernel of this paper, using spatial algebra, which combines the technique of RS and GIS together, and it can greatly improve the accuracy and reflect the actual land types better in classification of wetland. Its accuracy can get to 96% after checked by GPS sample points,land cover data of 2000 and visual interpretation. Then we can draw a conclusion that as far as wetland classification is concerted, the image enhance before classification can improve its accuracy in some parts, but using spatial algebra based on GIS technology can put the advantage together and get the best result.
出处
《遥感技术与应用》
CSCD
2004年第4期244-248,共5页
Remote Sensing Technology and Application
基金
国家自然科学基金重点项目(50139020-5-2)资助。
关键词
遥感
湿地
分类
分类精度
Remote sensing, Wetland, Classification, Accuracy of classification
