当前位置: X-MOL 学术J. Indian Soc. Remote Sens. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Utilizing Advance Texture Features for Rapid Damage Detection of Built Heritage Using High-Resolution Space Borne Data: A Case Study of UNESCO Heritage Site at Bagan, Myanmar
Journal of the Indian Society of Remote Sensing ( IF 2.5 ) Pub Date : 2020-10-01 , DOI: 10.1007/s12524-020-01190-9
Navneet Kaur , Poonam S. Tiwari , Hina Pande , Shefali Agrawal

Heritage sites are vulnerable to damage due to social, anthropological and environmental factors. Major Earthquakes are followed by damage to cultural heritage buildings. The assessment of such building damage is a critical problem. Earth Observation data, owing to its property of being non-contact, cost effective, synoptic view and high repeatability, has a significant role to play in estimation of damage in the earthquake affected areas. Currently, several and varied types of remote sensing data have become available, and therefore, appropriate methods for rapid assessment and analysis of the data need to be developed. Rapid damage assessment is critical to minimize loss in terms of life and property. In case of cultural monuments, rapid assessment can minimize damage and help in the conservation of monument. This research focuses on evolving a robust method for rapid identification and extraction of damaged heritage building structures, especially those affected by disasters such as earthquakes. In this study, we propose to examine the utility of advance texture algorithms such as Gabor, fractal and semi-variogram for rapid damage detection in heritage building structures. The methodology attempts to automatically highlight damaged portions of the structure through a knowledge driven rule set. The technique was able to extract the damaged area from the heritage building structure with the use of high-resolution space borne data. It is observed that feature extraction algorithms based on fractal and variogram provide better results than the Gabor based textures and are very useful in the case of high-resolution satellite imagery. Both the methods are able to extract damaged features in both shadowed and non-shadowed regions of the image. Hence the problems posed by shadowed dead grounds on EO data can be effectively resolved. However, it is also observed that the advance texture feature extraction algorithms are useful only in case of high-spatial resolution dataset and has limited use for rapid damage assessment from medium and low resolution datasets.

中文翻译:

利用先进的纹理特征,使用高分辨率太空传播数据对建筑遗产进行快速损坏检测:缅甸蒲甘联合国教科文组织遗产地案例研究

由于社会、人类学和环境因素,遗产地很容易受到破坏。大地震之后,文化遗产建筑遭到破坏。对此类建筑物损坏的评估是一个关键问题。地球观测数据由于其非接触性、成本效益、天气视图和高可重复性的特性,在估计地震灾区的损害方面发挥着重要作用。目前,已有几种不同类型的遥感数据可用,因此需要开发适当的方法来快速评估和分析数据。快速的损坏评估对于最大限度地减少生命和财产方面的损失至关重要。在文化古迹的情况下,快速评估可以最大限度地减少损坏并有助于保护古迹。这项研究的重点是发展一种稳健的方法来快速识别和提取受损的遗产建筑结构,尤其是那些受地震等灾害影响的建筑结构。在这项研究中,我们建议检查 Gabor、分形和半变异函数等高级纹理算法在遗产建筑结构中快速损伤检测的效用。该方法试图通过知识驱动的规则集自动突出显示结构的损坏部分。该技术能够利用高分辨率星载数据从遗产建筑结构中提取受损区域。据观察,基于分形和变异函数的特征提取算法比基于 Gabor 的纹理提供更好的结果,并且在高分辨率卫星图像的情况下非常有用。这两种方法都能够在图像的阴影和非阴影区域中提取损坏的特征。因此,可以有效地解决由 EO 数据上的阴影死区带来的问题。然而,还观察到高级纹理特征提取算法仅在高空间分辨率数据集的情况下有用,并且在中低分辨率数据集的快速损伤评估中使用有限。
更新日期:2020-10-01
down
wechat
bug