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VHR satellite imagery for humanitarian crisis management: a case study

机译:人道主义危机管理的VHR卫星图像:一个案例研究

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During the last years, remote sensing data along with GIS have been largely employed for supporting emergency management activities. In this context, the use of satellite images and derived map products has become more common also in the different phases of humanitarian crisis response. In this work very high resolution satellite imagery was processed to assess the evolution of Za'atari Refugee Camp, built in Jordan in 2012 by the UN Refugee Agency to host Syrian refugees. Multispectral satellite scenes of the Za'atari area were processed by means of object-based classifications. The main aim of the present work is the development of a semi-automated procedure for multi-temporal camp monitoring with particular reference to the dwellings detection. Whilst in the emergency mapping domain automation of feature extraction is widely investigated, in the field of humanitarian missions the information is often extracted by means of photointerpretation of the satellite data. This approach requires time for the interpretation; moreover, it is not reliable enough in complex situations, where features of interest are often small, heterogeneous and inconsistent. Therefore, the present paper discusses a methodology to obtain information for assisting humanitarian crisis management, using a semi-automatic classification approach applied to satellite imagery.
机译:在过去几年中,遥感数据以及GIS主要用于支持应急管理活动。在这种情况下,使用卫星图像和衍生地图产品也在人道主义危机反应的不同阶段变得更加常见。在这项工作中,加工了高分辨率的卫星图像,以评估Za'atari难民营的演变,于2012年由联合国难民局举办叙利亚难民。通过基于对象的分类处理Za'atari区域的多光谱卫星场景。本作工作的主要目的是开发多时间营地监测的半自动程序,特别是居住检测。虽然在紧急映射域自动化的特征提取的自动化被广泛研究,但在人道主义任务领域中,常常通过卫星数据的光接合来提取信息。这种方法需要时间来解释;此外,在复杂情况下不够可靠,其中感兴趣的特征通常很小,异构和不一致。因此,本文讨论了利用适用于卫星图像的半自动分类方法来获得辅助人道主义危机管理的信息的方法。

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