High-resolution monitoring of landslides with UAS photogrammetry and digital image correlation

IF 3.7 4区 地球科学 Q2 REMOTE SENSING
F. Mugnai, A. Masiero, Riccardo Angelini, I. Cortesi
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引用次数: 1

Abstract

Periodically monitoring landslides is a key factor for supporting the realisation of hazard warning systems and risk reduction in the corresponding neighbourhood areas. Although satellite remote sensing solutions can be considered for low spatial resolution monitoring, this approach is still inappropriate for high spatial resolution investigations. Ground-based Radar Interferometry is also a widely used technique that allows for working at a proper spatial resolution, but it can often be an overbudget solution for most applications. Instead, photogrammetric surveys based on Unmanned Aerial System (UAS) imagery appear as a very interesting approach in terms of both spatial resolution and flexibility in temporally repeating the survey. Motivated by this observation, this work investigates the use of multi-temporal UAS surveys for landslide monitoring. To be more precise, Digital Image Correlation (DIC) has been applied to orthomosaics generated from different UAS photogrammetry surveys to compute the area’s deformation map. Compared with a reference GNSS survey, the results obtained using NHAZCA IRIS software and an in-house DIC approach show a deformation estimation accuracy of approximately 0.1 m, a reasonable accuracy for landslides moving at moderate velocity.
利用无人机摄影测量和数字图像相关技术对滑坡进行高分辨率监测
定期监测山体滑坡是支持在相应邻近地区实现危险预警系统和降低风险的关键因素。尽管卫星遥感解决方案可以考虑用于低空间分辨率监测,但这种方法仍然不适用于高空间分辨率调查。地面雷达干涉测量也是一种广泛使用的技术,可以在适当的空间分辨率下工作,但对于大多数应用来说,它往往是一种预算过高的解决方案。相反,基于无人机系统(UAS)图像的摄影测量测量在空间分辨率和时间重复测量的灵活性方面似乎是一种非常有趣的方法。基于这一观察结果,本工作调查了多时相无人机调查在滑坡监测中的应用。更准确地说,数字图像相关(DIC)已被应用于不同无人机摄影测量测量生成的正交镶嵌图,以计算该地区的变形图。与参考GNSS调查相比,使用NHAZCA IRIS软件和内部DIC方法获得的结果显示,变形估计精度约为0.1 m,对于以中等速度移动的滑坡来说,这是一个合理的精度。
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来源期刊
CiteScore
7.00
自引率
2.50%
发文量
51
审稿时长
>12 weeks
期刊介绍: European Journal of Remote Sensing publishes research papers and review articles related to the use of remote sensing technologies. The Journal welcomes submissions on all applications related to the use of active or passive remote sensing to terrestrial, oceanic, and atmospheric environments. The most common thematic areas covered by the Journal include: -land use/land cover -geology, earth and geoscience -agriculture and forestry -geography and landscape -ecology and environmental science -support to land management -hydrology and water resources -atmosphere and meteorology -oceanography -new sensor systems, missions and software/algorithms -pre processing/calibration -classifications -time series/change analysis -data integration/merging/fusion -image processing and analysis -modelling European Journal of Remote Sensing is a fully open access journal. This means all submitted articles will, if accepted, be available for anyone to read anywhere, at any time, immediately on publication. There are no charges for submission to this journal.
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