期刊
REMOTE SENSING
卷 9, 期 7, 页码 -出版社
MDPI
DOI: 10.3390/rs9070653
关键词
high-resolution SAR imagery; TerraSAR-X; shoreline; beach nourishment; Sand Motor; coastal dynamics
类别
资金
- Netherlands America Foundation
- Fulbright U.S. Student Program
- ERC-Advanced [291206-NEMO]
- Province of South-Holland
- European Fund for Regional Development (EFRO)
- EcoShape/Building with Nature
- Dutch Ministry of Transport, Public Works and Water Management
- municipality of Dordrecht, EFRO
- EcoShape Foundation
- German Aerospace Center (DLR) [MTH0246, MTH1293]
This paper presents a semi-automated approach to detecting coastal shoreline change with high spatial-and temporal-resolution using X-band synthetic aperture radar (SAR) data. The method was applied at the Sand Motor, a mega-scale beach nourishment project in the Netherlands. Natural processes, like waves, wind, and tides, gradually distribute the highly concentrated sand to adjacent beaches. Currently, various in-situ techniques are used to monitor the Sand Motor on a monthly basis. Meanwhile, the TerraSAR-X satellite collects two high-resolution (3 x 3 m), cloud-penetrating SAR images every 11 days. This study investigates whether shorelines detected in TerraSAR-X imagery are accurate enough to monitor the shoreline dynamics of a project like the Sand Motor. The study proposes and implements a semi-automated workflow to extract shorelines from all 182 available TerraSAR-X images acquired between 2011 and 2014. The shorelines are validated using bi-monthly RTK-GPS topographic surveys and nearby wave and tide measurements. A valid shoreline could be extracted from 54% of the images. The horizontal accuracy of these shorelines is approximately 50 m, which is sufficient to assess the larger scale shoreline dynamics of the Sand Motor. The accuracy is affected strongly by sea state and partly by acquisition geometry. We conclude that using frequent, high-resolution TerraSAR-X imagery is a valid option for assessing coastal dynamics on the order of tens of meters at approximately monthly intervals.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据