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URBAN MONITORING AT A REGIONAL SCALE BASED ON MERIS AND ASAR DATA

机译:基于Meris和Asar数据的区域规模的城市监测

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Monitoring urban areas at a regional scale, and even at a global scale, has become an increasingly important topic in the last decades. New Earth Observation (EO) platforms provide remotely-sensed imagery that allows the monitoring of urban expansion with the required spatial and temporal resolutions. Currently, we can take advantage of the combination of sensors present in the ESA ENVISAT platform, which offers simultaneous acquisition of MERIS (MEdium Resolution Imaging Spectrometer) and ASAR (Advanced Synthetic Aperture Radar) sensors. The aim of this work is to demonstrate the capabilities of MERIS and ASAR data to map urban areas at a regional scale. Since MERIS FR works with a 300 m pixel size, this application focuses on obtaining high accuracy at a regional scale, providing the basis for a low-cost highly automated pan-European service dedicated to identifying and monitoring urban areas, for instance, of EU25. For this purpose, a two-stage classification scheme based on an unsupervised approach is proposed, which allows us to introduce supervised information about the class of interest without an additional sample labelling.
机译:在区域规模监测城市地区,甚至在全球范围内,在过去几十年中已成为越来越重要的话题。新地球观测(EO)平台提供远程感知的图像,允许使用所需的空间和时间分辨率监测城市扩张。目前,我们可以利用ESA Envisat平台中存在的传感器的组合,该平台提供同时采集Meris(中分辨率成像光谱仪)和ASAR(高级合成孔径雷达)传感器。这项工作的目的是展示MERIS和ASAR数据以区域规模映射城市地区的能力。由于MERIS FR以300米的像素尺寸合理,因此该应用程序侧重于以区域规模获得高精度,为致力于识别和监测EU25的城市地区的低成本高度自动化泛欧服务提供基础。为此目的,提出了一种基于无监督方法的两级分类方案,这使我们能够在没有其他样本标签的情况下引入有关兴趣类的监督信息。

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