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Coastal habitat mapping in the Aegean Sea using high resolution orthophoto maps

机译:使用高分辨率正射影像图绘制爱琴海沿海生境图

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The significance of coastal habitat mapping lies in the need to prevent from anthropogenic interventions and other factors. Until 2015, Landsat-8 (30m) imagery were used as medium spatial resolution satellite imagery. So far, Sentinel-2 satellite imagery is very useful for more detailed regional scale mapping. However, the use of high resolution orthophoto maps, which are determined from UAV data, is expected to improve the mapping accuracy. This is due to small spatial resolution of the orthophoto maps (30 cm). This paper outlines the integration of UAS for data acquisition and Structure from Motion (SfM) pipeline for the visualization of selected coastal areas in the Aegean Sea. Additionally, the produced orthophoto maps analyzed through an object-based image analysis (OBIA) and nearest-neighbor classification for mapping the coastal habitats. Classification classes included the main general habitat types, i.e. seagrass, soft bottom, and hard bottom The developed methodology applied at the Koumbara beach (Ios Island - Greece). Results showed that UAS's data revealed the sub-bottom complexity in large shallow areas since they provide such information in the spatial resolution that permits the mapping of seagrass meadows with extreme detail. The produced habitat vectors are ideal as reference data for studies with satellite data of lower spatial resolution.
机译:沿海栖息地测绘的重要性在于需要防止人为干预和其他因素。直到2015年,Landsat-8(30m)影像都被用作中等空间分辨率的卫星影像。到目前为止,Sentinel-2卫星图像对于更详细的区域比例尺地图非常有用。但是,使用从无人机数据确定的高分辨率正射影像图有望改善测绘精度。这是由于正射影像图的空间分辨率较小(30厘米)。本文概述了用于数据采集的UAS的集成以及通过Motion(SfM)管道进行的结构化,以可视化爱琴海中选定的沿海地区。此外,通过基于对象的图像分析(OBIA)和最近邻分类法对生成的正射影像图进行了分析,以绘制沿海生境。分类类别包括主要的一般栖息地类型,即海草,软底和硬底。在Koumbara海滩(爱奥斯岛-希腊)采用了发达的方法。结果表明,UAS的数据揭示了大片浅层区域的亚底复杂性,因为它们以空间分辨率提供了此类信息,从而可以绘制海草草甸的极端细节。产生的栖息地矢量非常适合作为研究具有较低空间分辨率的卫星数据的参考数据。

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