Federal Institute of Education, Science, and Technology Baiano (IF Baiano), Guanambi, BA, Brazil; Department of Cartographic Engineering, Federal University of Pernambuco (UFPE), Geodetic Science and Technology of Geoinformation Post Graduation Program, Recife, PE, Brazil.
Department of Cartographic Engineering, Federal University of Pernambuco (UFPE), Geodetic Science and Technology of Geoinformation Post Graduation Program, Recife, PE, Brazil.
Sci Total Environ. 2022 Apr 15;817:152849. doi: 10.1016/j.scitotenv.2021.152849. Epub 2022 Jan 10.
The detection of coastal vulnerability to erosion is crucial for decision-making regarding the economy, ecology, health, security, among other issues. Most of the studies gather a large data set about physical and anthropogenic interference's on the vulnerability of coastal erosion regions around the world. However, for developing nations like Brazil, with extensive shoreline, it is challenging to develop and maintain an in situ infrastructure to offer a systematical scientific data set. In this context, several methods like Coastal Vulnerability Index (CVI) for monitoring the dynamic behavior of coastal systems require in situ collected data. Therefore, this contribution explores the use of global open source satellite-based indicators to assess coastal vulnerability to erosion at a regional level adopting an uncorrelated orthogonal basis set of Principal Component Analysis (PCA). For this, the data set covers many spheres of the environment like biophysical and social factors, adopting the Pernambuco State's coast, Brazil, as a case study. The results showed the direct relationship between a high level of urbanization and low vegetation with the high coastal vulnerability to erosion. PC1 revealed built-up and surface temperature vary inversely to the soil organic carbon and vegetation cover along about 20 km (≈10% of the shoreline extension). The hotspots were in the urban cluster (Paulista, Olinda, Recife, and Jaboatao dos Guararapes), combined with high shoreline change around -2 m/yr. PC2 showed the natural action of wind on wave heights combined with sediment removal and the backshore settlement along 10 km of extension (≈5.5% of the shoreline), with the highly vulnerable sites concentrated in Itamaraca Island and C. S. Agostinho. This approach benefits from the multi-satellite and multi-resolution data sets integration to unravel the statistical influence of each variable able to guide stakeholders.
海岸侵蚀脆弱性的检测对于经济、生态、健康、安全等方面的决策至关重要。大多数研究都收集了大量关于世界各地海岸侵蚀地区物理和人为干扰对脆弱性影响的数据。然而，对于像巴西这样拥有广阔海岸线的发展中国家来说，开发和维护现场基础设施以提供系统科学数据集是具有挑战性的。在这种情况下，像海岸脆弱性指数 (CVI) 这样的几种方法用于监测海岸系统的动态行为，需要现场收集数据。因此，本研究探讨了使用全球开源卫星基指标来评估采用主成分分析 (PCA) 不相关正交基集的区域水平的海岸侵蚀脆弱性。为此，该数据集涵盖了环境的许多领域，如生物物理和社会因素，采用巴西伯南布哥州的海岸作为案例研究。结果表明，城市化水平高和植被覆盖率低与海岸侵蚀高脆弱性之间存在直接关系。PC1 显示，建成区和地表温度与土壤有机碳和植被覆盖呈反比变化，沿约 20 公里（约海岸线延伸的 10%）。热点在城市集群（保利斯塔、奥林达、累西腓和雅博阿唐斯），加上海岸线变化率约为-2 米/年。PC2 显示了风对波高的自然作用，加上沉积物的去除和后滨沉降，沿 10 公里延伸（约海岸线的 5.5%），高度脆弱的地点集中在伊塔马拉卡岛和 C. S. 阿戈斯蒂尼奥。这种方法受益于多卫星和多分辨率数据集的集成，以揭示每个变量的统计影响，从而为利益相关者提供指导。
