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Remote sensing-based mapping of the destruction to Aleppo during the Syrian Civil War between 2011 and 2017

机译:2011年至2017年叙利亚内战期间,遥感基于毁灭的毁灭映射

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Accurate assessment of damage caused by conflict can be difficult to determine from ground-based surveys, particularly in the context of violence and unsafe conditions. Earth Observation data provides a non-invasive method for rapid damage assessment over wide geographic areas. In this study we use Landsat Imagery captured between 2011 and 2017 to assess the damage in Aleppo, Syria caused by conflict during the Syrian Civil War. Extracting temporal changes in urban environments is complex and the capabilities of traditional spectral-based methodologies are limited. We examined the effectiveness of the Gray-Level Co-Occurrence Matrix (GLCM) and two texture-based metrics (correlation and homogeneity) at classifying changes in reflectance characteristics within urban environments caused by building damage and consequent changes in surface orientation. Homogeneity was a more effective texture measure than correlation (overall accuracy of 79% vs 50%). Results indicated that between 45% and 57% of Aleppo was damaged during the study period, including up to 57% of former rebel held areas and between 34% and 46% of government areas and their surrounds. We used SPOT-6 imagery for accuracy assessment. Damage to Aleppo has yet to be fully quantified and several parts of the city remain unsafe and inaccessible. The results of this study highlight the potential offered by texture analysis for mapping damage to urban areas with freely available imagery and can be readily applied to natural disasters such as earthquakes and the aftermath of extreme weather events.
机译:精确评估冲突造成的损坏可能难以从基于地面的调查中确定,特别是在暴力和不安全的情况下。地球观测数据为广泛的地理区域提供了快速损害评估的非侵入性方法。在这项研究中,我们在2011年和2017年间捕获的Landsat Imagery来评估叙利亚内战期间由冲突造成的Aleppo造成的害怕。提取城市环境中的时间变化复杂,传统的基于光谱的方法的能力有限。我们研究了灰度共发生矩阵(GLCM)和两个基于纹理的度量(相关性和同质性)的有效性,在通过建立损坏和随后的表面方向变化引起的城市环境中的反射特性变化。均匀性是比相关性更有效的纹理测量(总精度为79%Vs 50%)。结果表明,在研究期间,45%和57%的Aleppo受损,包括高达57%的前反叛持有地区,占政府地区及其环绕物的34%至46%。我们使用Spot-6图像进行准确性评估。对Aleppo的损害尚未完全量化,这座城市的几个部分仍然不安全和无法进入。本研究的结果突出了纹理分析所提供的潜力,以便使用自由的意象造成对城市地区的损坏,并且可以容易地应用于地震等自然灾害和极端天气事件的后果。

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