Built-up area analysis using Sentinel data in metropolitan areas of Transylvania, Romania

IF 1.4 Q2 GEOGRAPHY
Constantin Oșlobanu, M. Alexe
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引用次数: 6

Abstract

The anthropic and natural elements have become more closely monitored and analysed through the use of remote sensing and GIS applications. In this regard, the study aims to feature a different approach to produce more and more thematic information, focusing on the development of built-up areas. In this paper, multispectral images and Synthetic Aperture Radar (SAR) images were the basis of a wide range of proximity analyses. These allow the extraction of data about the distribution of built-up space on the areas with potential for economic and social development. Application of interferometric coherence and supervised classifications have been accomplished on various territories, such as metropolitan areas of the most developed region of Romania, more specifically Transylvania. The results indicate accuracy values, which can reach 94 per cent for multispectral datasets and 93 per cent for SAR datasets. The accuracy of resulted data will reveal a variety of city patterns, depending mainly on local features regarding natural and administrative environments. In this way, a comparison will be made between the accuracy of both datasets to provide an analysis of the manner of built-up areas distribution to assess the expansion of the studied metropolitan areas. Therefore, this study aims to apply well-established methods from the remote sensing field to enhance the information and datasets in some areas lacking recent research.
使用Sentinel数据对罗马尼亚特兰西瓦尼亚大都市地区的建成区进行分析
通过遥感和地理信息系统的应用,人类和自然因素得到了更密切的监测和分析。在这方面,该研究旨在采用不同的方法,以产生越来越多的主题信息,重点关注建成区的发展。在本文中,多光谱图像和合成孔径雷达(SAR)图像是广泛的邻近度分析的基础。这些可以提取具有经济和社会发展潜力的地区的建成空间分布数据。干涉相干性和监督分类的应用已经在各个地区完成,例如罗马尼亚最发达地区的大都市地区,更具体地说是特兰西瓦尼亚。结果表明,多光谱数据集和合成孔径雷达数据集的准确率分别可达94%和93%。所得数据的准确性将揭示各种城市模式,主要取决于自然和行政环境方面的当地特征。通过这种方式,将在两个数据集的准确性之间进行比较,以提供对建成区分布方式的分析,从而评估所研究的大都市地区的扩张。因此,本研究旨在应用遥感领域的成熟方法,在一些缺乏近期研究的领域增强信息和数据集。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Hungarian Geographical Bulletin
Hungarian Geographical Bulletin Social Sciences-Geography, Planning and Development
CiteScore
3.20
自引率
0.00%
发文量
24
审稿时长
24 weeks
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