Connor McAnuff, C. Samson, D. Melanson, C. Polowick, E. Bethell
{"title":"用安装在无人驾驶飞机系统上的激光雷达成像的岩壁结构图","authors":"Connor McAnuff, C. Samson, D. Melanson, C. Polowick, E. Bethell","doi":"10.1139/JUVS-2018-0015","DOIUrl":null,"url":null,"abstract":"Structural mapping of rock walls to determine fracture orientation provides critical geological information in support of mining operations. A helicopter-style UAS (rotor diameter 2 m; take-off mass 35 kg; payload mass 11 kg) instrumented with a high-resolution LiDAR imaged a 75 m long and 10–15 m high series of four adjacent rock walls at the Canadian Wollastonite mine. A point cloud with a density of 484 point/m2 acquired at an angle of incidence of ∼41.7° from a flight altitude of 41.7 m above ground level was selected for structural mapping. The point cloud was first meshed using the Poisson surface reconstruction method and then remeshed to achieve an even element size distribution. Visualization of the remeshed Poisson mesh using a 360° hue–saturation–lightness colour wheel highlighted areas of higher fracture density, whereas visualization using a 180° colour wheel accentuated sliver-like geological features. Two joint sets were identified at 156/82 and 241/86 (strike/dip in degrees). A total of 18 virtual strike measurements and 13 virtual dip measurements were within 10% of manual compass measurements. This study demonstrated that the task of structural mapping of large rock walls can be automated by processing 3D images acquired with a LiDAR mounted on a UAS.","PeriodicalId":45619,"journal":{"name":"Journal of Unmanned Vehicle Systems","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1139/JUVS-2018-0015","citationCount":"2","resultStr":"{\"title\":\"Structural mapping of rock walls imaged with a LiDAR mounted on an unmanned aircraft system\",\"authors\":\"Connor McAnuff, C. Samson, D. Melanson, C. Polowick, E. Bethell\",\"doi\":\"10.1139/JUVS-2018-0015\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Structural mapping of rock walls to determine fracture orientation provides critical geological information in support of mining operations. A helicopter-style UAS (rotor diameter 2 m; take-off mass 35 kg; payload mass 11 kg) instrumented with a high-resolution LiDAR imaged a 75 m long and 10–15 m high series of four adjacent rock walls at the Canadian Wollastonite mine. A point cloud with a density of 484 point/m2 acquired at an angle of incidence of ∼41.7° from a flight altitude of 41.7 m above ground level was selected for structural mapping. The point cloud was first meshed using the Poisson surface reconstruction method and then remeshed to achieve an even element size distribution. Visualization of the remeshed Poisson mesh using a 360° hue–saturation–lightness colour wheel highlighted areas of higher fracture density, whereas visualization using a 180° colour wheel accentuated sliver-like geological features. Two joint sets were identified at 156/82 and 241/86 (strike/dip in degrees). A total of 18 virtual strike measurements and 13 virtual dip measurements were within 10% of manual compass measurements. This study demonstrated that the task of structural mapping of large rock walls can be automated by processing 3D images acquired with a LiDAR mounted on a UAS.\",\"PeriodicalId\":45619,\"journal\":{\"name\":\"Journal of Unmanned Vehicle Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2019-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1139/JUVS-2018-0015\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Unmanned Vehicle Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1139/JUVS-2018-0015\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"REMOTE SENSING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Unmanned Vehicle Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1139/JUVS-2018-0015","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"REMOTE SENSING","Score":null,"Total":0}
Structural mapping of rock walls imaged with a LiDAR mounted on an unmanned aircraft system
Structural mapping of rock walls to determine fracture orientation provides critical geological information in support of mining operations. A helicopter-style UAS (rotor diameter 2 m; take-off mass 35 kg; payload mass 11 kg) instrumented with a high-resolution LiDAR imaged a 75 m long and 10–15 m high series of four adjacent rock walls at the Canadian Wollastonite mine. A point cloud with a density of 484 point/m2 acquired at an angle of incidence of ∼41.7° from a flight altitude of 41.7 m above ground level was selected for structural mapping. The point cloud was first meshed using the Poisson surface reconstruction method and then remeshed to achieve an even element size distribution. Visualization of the remeshed Poisson mesh using a 360° hue–saturation–lightness colour wheel highlighted areas of higher fracture density, whereas visualization using a 180° colour wheel accentuated sliver-like geological features. Two joint sets were identified at 156/82 and 241/86 (strike/dip in degrees). A total of 18 virtual strike measurements and 13 virtual dip measurements were within 10% of manual compass measurements. This study demonstrated that the task of structural mapping of large rock walls can be automated by processing 3D images acquired with a LiDAR mounted on a UAS.