Urban area change visualization and analysis using high density spatial data from time series aerial images

IF 0.3 Q4 REMOTE SENSING
C. Altuntas
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引用次数: 3

Abstract

Abstract Urban changes occur as a result of new constructions or destructions of buildings, extensions, excavation works and earth fill arising from urbanization or disasters. The fast and efficient detection of urban changes enables us to update geo-databases and allows effective planning and disaster management. This study concerns the visualization and analysis of urban changes using multi-period point clouds from aerial images. The urban changes in the city centre of the Konya Metropolitan area within arbitrary periods between the years 1951, 1975, 1998 and 2010 were estimated after comparing the point clouds by using the iterative closest point (ICP) algorithm. The changes were detected with the point-to-surface distances between the point clouds. The degrees of the changes were expressed with the RMSEs of these point-to-surface distances. In addition, the change size and proportion during the historical periods were analysed. The proposed multi-period change visualization and analysis method ensures strict management against unauthorized building or excavation and more operative urban planning.
基于时间序列航空影像高密度空间数据的城市面积变化可视化与分析
城市变化是由于城市化或灾害引起的新建或破坏建筑物、扩建、开挖和填土而产生的。快速有效地发现城市变化使我们能够更新地理数据库,并实现有效的规划和灾害管理。本研究利用航空影像的多时期点云对城市变化进行可视化和分析。利用迭代最近点(ICP)算法对1951年、1975年、1998年和2010年任意时间段的点云进行比较,估算了科尼亚市区中心的城市变化。这些变化是通过点云之间点到表面的距离来检测的。变化的程度用这些点面距离的均方根值表示。此外,还分析了各历史时期的变化规模和比例。提出的多周期变化可视化分析方法,确保了对违章建筑或挖掘的严格管理和更可操作的城市规划。
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
自引率
28.60%
发文量
5
审稿时长
12 weeks
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