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Detecting changes on coastal primary sand dunes using multi-temporal Landsat Imagery

机译:使用多时态Landsat影像检测沿海原始沙丘的变化

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Due to both natural and anthropogenic causes the coastal primary sand dunes, keeps changing dynamically and continuously their shape, position and extend over time. In this paper we use a case study to show how we monitor the Portuguese coast, between the period 2000 to 2014, using free available multi-temporal Landsat imagery (ETM+ and OLI sensors). First, all the multispectral images are panshaperned to meet the 15 meters spatial resolution of the panchromatic images. Second, using the Modification of Normalized Difference Water Index (MNDWI) and kmeans clustering method we extract the raster shoreline for each image acquisition time. Third, each raster shoreline is smoothed and vectorized using a penalized least square method. Fourth, using an image composed by five synthetic bands and an unsupervised classification method we extract the primary sand dunes. Finally, the visual comparison of the thematic primary sand dunes maps shows that an effective monitoring system can be implemented easily using free available remote sensing imagery data and open source software (QGIS and Orfeo toolbox).
机译:由于自然和人为原因,沿海初级沙丘不断变化,其形状,位置和时间不断变化。在本文中,我们将通过一个案例研究来说明如何使用免费的多时态Landsat影像(ETM +和OLI传感器)监测2000年至2014年之间的葡萄牙海岸。首先,对所有多光谱图像进行全形处理,以满足全色图像15米的空间分辨率。其次,使用归一化差异水指数(MNDWI)的修改和kmeans聚类方法,我们为每个图像采集时间提取了栅格海岸线。第三,使用惩罚最小二乘法对每个栅格海岸线进行平滑和矢量化处理。第四,使用由五个合成波段组成的图像和无监督分类方法,我们提取了原始沙丘。最后,主题沙丘专题图的视觉比较表明,使用免费的可用遥感影像数据和开源软件(QGIS和Orfeo工具箱),可以轻松实现有效的监视系统。

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