Coastal migration via satellite data

The shoreline is a highly dynamic land-sea interface that provides important services such as ecology, floodprotection and recreation. It is constantly modified by wind, waves and tides, and impacted by human activity.Hence, the decadal change of shorelines reflect natural processes as well as human influence, whether positiveor negative. Climatic-driven changes such as sea level rise, higher waves and changes in wind direction putincreasing pressure on many of Europe's shorelines.Knowing how, and at what rate, our coasts are changing is the first step to successfully managing them. Thenew EMODnet Geology shoreline-migration map, released today, allows users to visualise pan-European coastalbehaviour for 2007-2017 at different spatial scales. A built-in search and zoom functionality allows online usersto distinguish areas of landward migration (erosion or submergence), stability, and seaward migration (accretionor emergence). The underlying, downloadable satellite-based dataset offers additional information on annualvalues and uncertainty.With the new map, international policy makers can determine large-scale coastal vulnerability while nationaland regional coastal managers are able to fill existing gaps in field-monitoring data and to identify potentialareas of rapid change. The map also provides the general public with a useful insight into one of Europe's mostobvious climate-change effects. Most importantly, scientists may explain spatial patterns and provide feedbackon methodological advantages as well as shortcomings, thus helping to optimise the big-data methodology used.

海岸线作为陆地与海洋交界的极为动态的界面，提供了诸如生态、防洪和休闲等重要服务。它不断受到风、浪和潮汐的塑造，并受到人类活动的深远影响。因此，海岸线的十年变化不仅反映了自然过程，也体现了正面或负面的人类影响。由气候变化驱动的变化，如海平面上升、波浪增强以及风向变化，对欧洲众多海岸线施加了日益增加的压力。了解海岸线如何以及以何种速度变化，是成功管理海岸线的第一步。今日发布的EMODnet地质海岸线迁移地图，允许用户以不同的空间尺度可视化2007-2017年泛欧洲海岸行为。内置的搜索和缩放功能使得在线用户能够区分向陆迁移（侵蚀或淹没）区域、稳定区域以及向海迁移（堆积或浮现）区域。基础的可下载卫星数据集提供了关于年度值和不确定性的额外信息。借助新地图，国际政策制定者可以确定大规模海岸脆弱性，而国家和地区的海岸管理者能够填补现有实地监测数据的空白，并识别潜在快速变化的区域。该地图还为公众提供了对欧洲最明显的气候变化效应的有益洞察。最重要的是，科学家可以解释空间模式，并对方法论的优势与不足提供反馈，从而帮助优化使用的大数据分析方法。