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Identification d'indicateurs de risque des populations victimes de conflits par imagerie satellitaire études de cas : le nord de l'Irak

机译:通过卫星图像案例研究确定受冲突影响人口的风险指标:伊拉克北部

摘要

Remote sensing and security, terms which are not usually associated, have found a common platform this decade with the conjuring of the GMOSS network (Global Monitoring for Security and Stability ), whose mandate is to discover new applications for satellite-derived imagery to security issues. This study focuses on human security, concentrating on the characterisation of vulnerable areas to conflict. A time-series of satellite imagery taken from Landsat sensors from 1987 to 2001 and the SRTM mission imagery are used for this purpose over a site in northern Iraq. Human security issues include the exposure to any type of hazard. The region of study is first characterised in order to understand which hazards are and were present in the past for the region of study. The principal hazard for the region of study is armed conflict and the relative field data was analysed to determine the links between geographical indicators and vulnerable areas. This is done through historical research and the study of open-sourced information about disease outbreaks; the movements of refugees and the internally displaced; and humanitarian aid and security issues. These open sources offer information which are not always consistent, objective, or normalized and are therefore difficult to quantify. A method for the rapid mapping and graphing and subsequent analysis of the situation in a region where limited information is available is developed. This information is coupled with population numbers to create a"risk map": A disaggregated matrix of areas most at risk during conflict situations. The results show that describing the risk factor for a population to the hazard conflict depends on three complex indicators: Population density, remoteness and economic diversity. Each of these complex indicators is then derived from Landsat and SRTM imagery and a satellite-driven model is formulated. This model based on satellite imagery is applied to the study site for a temporal study. The output are three 90 m × 90 m resolution grids which describe, at a pixel level, the risk level within the region for each of the dates studies, and the changes which occur in northern Iraq as the result of the Anfal Campaigns. Results show that satellite imagery, with a minimum of processing, can yield indicators for characterising risk in a region. Although by no means a replacement for field data, this technological source, in the absence of local knowledge, can provide users with a starting point in understanding which areas are most at risk within a region. If this data is coupled with open sourced information such as political and cultural discrimination, economy and agricultural practices, a fairly accurate risk map can be generated in the absence of field data.
机译:遥感和安全这两个通常不相关的术语在本十年中随着GMOSS网络(全球安全性和稳定性监控)的变幻而找到了一个通用平台,该网络的任务是发现针对安全问题的卫星图像的新应用。这项研究侧重于人类安全,着重于易受冲突影响地区的特征。为此,从1987年到2001年从Landsat传感器获取的时间序列卫星图像和SRTM任务图像被用于伊拉克北部的某个地点。人类安全问题包括暴露于任何类型的危害。首先对研究区域进行特征化,以了解过去该研究区域存在哪些危害。研究区域的主要危险是武装冲突,并分析了相关的野外数据,以确定地理指标与脆弱地区之间的联系。这是通过历史研究和有关疾病暴发的开源信息的研究来完成的;难民和国内流离失所者的流动;以及人道主义援助和安全问题。这些开源提供的信息并不总是一致,客观或标准化的,因此很难量化。开发了一种用于在信息有限的区域中快速绘制和绘制图形并随后分析情况的方法。该信息与人口数量相结合以创建“风险图”:在冲突情况下,最高风险区域的分解矩阵。结果表明,描述人口遭受危险冲突的危险因素取决于三个复杂的指标:人口密度,偏远性和经济多样性。然后,这些复杂指标中的每一个都从Landsat和SRTM影像中得出,并建立了卫星驱动模型。基于卫星图像的模型被应用到研究地点进行时间研究。输出是三个90 m×90 m分辨率的网格,这些像素以像素为单位描述了每个日期研究的区域内的风险等级,以及因Anfal运动而在伊拉克北部发生的变化。结果表明,只需最少的处理,卫星图像就可以提供用于表征区域风险的指标。尽管绝不能替代现场数据,但是在缺乏本地知识的情况下,这种技术资源可以为用户提供一个起点,让他们了解一个地区内哪些地区的风险最高。如果此数据与开放源信息(例如政治和文化歧视,经济和农业实践)结合在一起,则在没有现场数据的情况下可以生成相当准确的风险图。

著录项

  • 作者

    Mubareka Sarah Betoul;

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  • 年度 2008
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  • 原文格式 PDF
  • 正文语种 fre
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