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Fast and Efficient Urban Extent Extraction Using ASAR Wide Swath Mode Data

机译:使用ASAR宽幅模式数据快速高效地提取城市范围

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This paper aims at introducing a fast and efficient approach able to extract human settlement extents using ASAR Wide Swath Mode data. The proposed approach exploits the spatial features characterizing human settlements in SAR data at a spatial resolution around 100 m, i.e., long term coherence and large backscattered power values. The joint use of multi-temporal filtering and averaging and the homogeneously high SAR return from built-up structures is the key to extract quickly and robustly human settlement extents. Although prone to commission errors in mountainous areas, the procedure proposed in this paper proved to be able to extract consistently more accurate results than existing global data sets including Globcover 2009. This was assessed by running a series of tests in different geographical areas and comparing the new and the existing products with independently extracted “urban” and “non-urban” points. The results show that ASAR data have no fewer potential than optical ones for global mapping of human settlements. Properly processed, instead, SAR data are able to provide an effective solution to the need of a global map of human settlement, useful for risk computations, climate change model inputs and population mapping, among other applications.
机译:本文旨在介绍一种快速有效的方法,该方法能够使用ASAR宽幅模式数据提取人类住区范围。所提出的方法利用了以约100 m的空间分辨率(即长期相干性和较大的反向散射功率值)表征SAR数据中人类居住的空间特征。结合使用多时相滤波和平均以及来自已建成结构的均匀高SAR回报,是快速,稳健地提取人类住区范围的关键。尽管在山区容易出现佣金错误,但与现有的全球数据集(包括Globcover 2009)相比,本文提出的程序证明能够始终如一地提取出更准确的结果。通过在不同地理区域进行一系列测试并比较具有独立提取的“城市”和“非城市”点的新产品和现有产品。结果表明,ASAR数据在人类住区的全球制图方面的潜力不亚于光学数据。相反,经过正确处理的SAR数据能够为全球人类住区图的需求提供有效的解决方案,可用于风险计算,气候变化模型输入和人口图以及其他应用。

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