首页 >  2003, Vol. 7, Issue (4) : 309-315

摘要

全文摘要次数: 3917 全文下载次数: 20
引用本文:

DOI:

10.11834/jrs.20030413

收稿日期:

2002-01-28

修改日期:

2002-04-22

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SPOT卫星影像居民地信息自动提取的决策树方法研究
南京大学 城市与资源学系,江苏 南京 210093
摘要:

以南京市江宁县为研究区域,首先分析了该区域居民地的影像特征,然后研究了居民地及其背景地物在SPOT—4(Ⅺ)卫星影像4个波段上的光谱特征,并由此探讨了它们在光谱特征上的可分性。研究发现,除道路在光谱特征上与居民地差异不大而难以完全分开外,其它背影地物均可以依据各波段亮度值的大小关系或适当的阈值与居民地分开。但道路和居民地在形状上存在明显差异,因此可以利用形状指数的差异加以去除。最后分析建立了基于光谱特征和形状特征的简单决策树模型,对研究区域居民地信息进行了提取并对结果进行了精度评价。结果表明,该方法的总体提取效果较好,特别是对于面积大于10000m^2的城镇和集村。其提取精度与通常的监督分类方法相比有了很大的提高,只是在水际交界处和道路两侧有误判现象。因此,利用该模型可以将背景地物类型复杂的江南地区的城镇和集村居民地自动提取出来,并且模型受时相影响较小,只是在域值大小上会存在一些差异。

The Decision Tree Algorithm of Automatically Extracting Residential Information from SPOT Images
Abstract:

Extracting residential information by remote sensing technology is significant for the loss estimation of natural disaster and the study of urban extension and environmental change.In this paper,taking Jiangning county of Nanjing as a case study area,the extraction of re sidential information from SPOT images is discussed.Firstly, the characteristics of residential areas in this area on this image are studied,secondly,spectral characteristics of residential areas and other land-use types on SPOT-4(XI) image are analyzed to find the possibility of extracting residential areas from the background according to spectral characteristics.Thirdly,a simple model of decision tree is proposed on the basis of spectral magnitude relations and some proper thresholds of residents and other land-use types.But some roads still cannot be separated from residential areas because their spectral characteristics are similar.Therefore,their shape characteristics are analyzed.The result is generalized and converted to vector coverage.Then the shape indexes of every spots are calculated and categorized choosing a threshold to remove the roads.Finally,the vector coverage of residential areas is overlaid on the original image to check the effectness of this model,and an accuracy assessment is given to the result by random samples.The results suggest that this model is simple and effective,especially for the residential areas over 10000 m2,and the analyzedfor is much higher than the supervised classification's,however,some pixels near the water-bodies and the roads are judged by mistakes.This problem can be solved by the rule judgment based on the knowledge of spatial relations.Therefore,the cities,towns and villages in the south of Yangze River where there are various types of land cover can be extracted from the images by this model,and the model is not limited by the time,only the thresholds will be changed.

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