{"title":"Comparative analysis of surface deformation monitoring in a mining area based on UAV‐lidar and UAV photogrammetry","authors":"Xilin Zhan, Xingzhong Zhang, Xiao Wang, Xinpeng Diao, Lizhuan Qi","doi":"10.1111/phor.12490","DOIUrl":null,"url":null,"abstract":"Unmanned aerial vehicle light detection and ranging (UAV‐lidar) and unmanned aerial vehicle (UAV) photogrammetry are currently commonly used surface monitoring technologies. Previous studies have used the two technologies interchangeably and ignored their correlation, or only compared them on a single product. However, there are few quantitative assessments of the differences between these two techniques in monitoring surface deformation and prediction of their application prospects. Therefore, the paper compared the differences between the digital elevation model (DEM) and subsidence basins obtained by the two techniques using Gaussian analysis. The results indicate that the surface DEMs obtained by both the techniques exhibit a high degree of similarity. The statistical analysis of the difference values in the <jats:italic>z</jats:italic> direction between the two DEMs follows a Gaussian distribution with a standard deviation of less than 0.36 m. When comparing the surface subsidence values monitored by the two techniques, it was found that UAV‐lidar was more sensitive to small‐scale deformation, with a difference range of 0.23–0.44 m compared to photogrammetry. The conclusion provides valuable information regarding the utilisation of multisource monitoring data.","PeriodicalId":22881,"journal":{"name":"The Photogrammetric Record","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Photogrammetric Record","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1111/phor.12490","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Unmanned aerial vehicle light detection and ranging (UAV‐lidar) and unmanned aerial vehicle (UAV) photogrammetry are currently commonly used surface monitoring technologies. Previous studies have used the two technologies interchangeably and ignored their correlation, or only compared them on a single product. However, there are few quantitative assessments of the differences between these two techniques in monitoring surface deformation and prediction of their application prospects. Therefore, the paper compared the differences between the digital elevation model (DEM) and subsidence basins obtained by the two techniques using Gaussian analysis. The results indicate that the surface DEMs obtained by both the techniques exhibit a high degree of similarity. The statistical analysis of the difference values in the z direction between the two DEMs follows a Gaussian distribution with a standard deviation of less than 0.36 m. When comparing the surface subsidence values monitored by the two techniques, it was found that UAV‐lidar was more sensitive to small‐scale deformation, with a difference range of 0.23–0.44 m compared to photogrammetry. The conclusion provides valuable information regarding the utilisation of multisource monitoring data.
无人飞行器光探测与测距(UAV-lidar)和无人飞行器摄影测量是目前常用的地表监测技术。以往的研究将这两种技术交替使用,忽略了它们之间的相关性,或者只在单一产品上对它们进行比较。然而,对于这两种技术在监测地表变形方面的差异和应用前景的预测,却鲜有定量评估。因此,本文利用高斯分析法比较了两种技术获得的数字高程模型(DEM)和沉降盆地之间的差异。结果表明,两种技术获得的地表 DEM 具有高度相似性。在对两种技术监测到的地表沉降值进行比较时发现,与摄影测量法相比,无人机激光雷达对小尺度变形更为敏感,差值范围为 0.23-0.44 米。这一结论为利用多源监测数据提供了有价值的信息。