Impervious surface mapping with Quickbird imagery.

Impervious surface mapping with Quickbird imagery.
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DOI:
10.1080/01431161003698393
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发表时间:
2011
影响因子:
3.4
通讯作者:
Moran E
Moran E
中科院分区:
工程技术3区
文献类型:
--
作者:
Lu D;Hetrick S;Moran E

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本研究选取两个不同城市发展、规模与空间型态的研究区域,探讨利用Quickbird影像绘制不透水面分布的适当方法。所选择的方法包括基于每像素的监督分类,基于分割的分类,和混合方法。结果的比较分析表明,基于每像素的监督分类产生了大量的“盐和胡椒”的像素,和基于分割的方法可以显着减少这个问题。然而,这两种方法都不能有效地解决不透水表面与水/湿地和裸露土壤的光谱混淆以及阴影的影响。为了从Quickbird图像中准确地绘制不透水面分布图,人工编辑是必要的,并且可能是从混乱的土地覆盖和阴影问题中提取不透水面的唯一方法。研究表明,阈值技术,无监督分类和有限的人工编辑的混合方法提供了最好的性能。
This research selects two study areas with different urban developments, sizes, and spatial patterns to explore the suitable methods for mapping impervious surface distribution using Quickbird imagery. The selected methods include per-pixel based supervised classification, segmentation-based classification, and a hybrid method. A comparative analysis of the results indicates that per-pixel based supervised classification produces a large number of “salt-and-pepper” pixels, and segmentation based methods can significantly reduce this problem. However, neither method can effectively solve the spectral confusion of impervious surfaces with water/wetland and bare soils and the impacts of shadows. In order to accurately map impervious surface distribution from Quickbird images, manual editing is necessary and may be the only way to extract impervious surfaces from the confused land covers and the shadow problem. This research indicates that the hybrid method consisting of thresholding techniques, unsupervised classification and limited manual editing provides the best performance.
DOI: 10.1007/978-1-4020-2560-0_12
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