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Urban land-use, land-cover classification through watershed segmentation in the V-I-S feature space

机译:通过V-I-S特征空间中的分水岭分割对城市土地利用进行土地覆盖分类

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摘要

This article introduces an innovative approach using marker-controlled watershed segmentation (WS) in the Vegetation-Impervious Surface-Soil (V I S) feature space for urban land-use and land-cover (LULC) classification. The complement (e.g., the inverse) of the V-I-S feature space image shows depressions, which can be treated as topographic watersheds and they correspond to LULC classes. WS partitions the complement of V-I-S feature space image into LULC regions based on user-specified initial markers. These regions are then labelled with specific LULC classes, which lead to the subsequent LULC classification. The results showed that WS can achieve substantial classification accuracy. Compared to the traditional maximum likelihood classifier (MLC), our method requires less user input while improving the classification accuracy. A sensitivity test of the WS-based method on the location of the initial markers also is provided.
机译:本文介绍了一种在植被不可渗透的表层土壤(V I S)特征空间中使用标记控制的分水岭分割(WS)的创新方法,用于城市土地利用和土地覆盖(LULC)分类。 V-I-S特征空间图像的补码(例如反像)显示了洼地,可以将其视为地形分水岭,并且它们对应于LULC类。 WS根据用户指定的初始标记将V-I-S特征空间图像的补全划分为LULC区域。然后用特定的LULC分类标记这些区域,从而导致随后的LULC分类。结果表明,WS可以达到相当大的分类精度。与传统的最大似然分类器(MLC)相比,我们的方法所需的用户输入更少,同时提高了分类精度。还提供了基于WS的方法在初始标记位置上的敏感性测试。

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  • 来源
    《Remote sensing letters》 |2012年第8期|677-685|共9页
  • 作者

    QUAN TANG; LEI WANG;

  • 作者单位

    Department of Geography and Anthropology, Louisiana State University, Baton Rouge,LA 70803, USA;

    Department of Geography and Anthropology, Louisiana State University, Baton Rouge,LA 70803, USA;

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  • 原文格式 PDF
  • 正文语种 eng
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