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Automatic generation of frequently updated land cover products at national level using COSMO-SkyMed SAR imagery

机译:使用COSMO-SkyMed SAR影像在国家级别自动生成频繁更新的土地覆盖产品

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SAR images from Italian COSMO-SkyMed mission can have a significant impact on the production and updates of land cover maps. However, for the full exploitation of the data and their application to nationwide extensions, robust automatic procedures need to be designed. In this paper we present the preliminary results obtained by the implementation of a processing scheme using COSMO-SkyMed images to provide, and regularly update every six months, land cover maps for the whole Italian territory. Most of the automatic processing is based on Neural Networks (NN) algorithms. In particular PCNN (Pulse Coupled NN) have been considered for change detection purposes while Multi-Layer Perceptrons (MLP) have been used for classifying the pixels belonging to a detected changed area.
机译:来自意大利COSMO-SkyMed任务的SAR图像可能会对土地覆盖图的制作和更新产生重大影响。但是,为了充分利用数据并将其应用于全国范围的扩展,需要设计可靠的自动过程。在本文中,我们介绍了通过使用COSMO-SkyMed图像实施处理方案来提供的初步结果,该图像可提供并每六个月定期更新整个意大利领土的土地覆盖图。大多数自动处理都基于神经网络(NN)算法。特别地,已经考虑将PCNN(脉冲耦合NN)用于变化检测,而将多层感知器(MLP)用于对属于检测到的变化区域的像素进行分类。

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