H. Lozano Bravo, E. Lo, H. Moyes, D. Rissolo, S. Montgomery, F. Kuester
{"title":"从点云数据合成洞穴底图的方法:以伯利兹拉斯奎瓦斯的激光雷达为例","authors":"H. Lozano Bravo, E. Lo, H. Moyes, D. Rissolo, S. Montgomery, F. Kuester","doi":"10.5194/isprs-annals-x-m-1-2023-179-2023","DOIUrl":null,"url":null,"abstract":"Abstract. Creating cave maps is an essential part of cave research. Traditional cartographic efforts are extremely time consuming and subjective, motivating the development of new techniques using terrestrial lidar scanners and mobile lidar systems. However, processing the large point clouds from these scanners to produce detailed, yet manageable “maps” remains a challenge. In this work, we present a methodology for synthesizing a basemap representing the cave floor from large scale point clouds, based on a case study of a SLAM-based lidar data acquisition from a cave system in the archaeological site of Las Cuevas, Belize. In 4 days of fieldwork, the 335 m length of the cave system was scanned, resulting in a point cloud of 4.1 billion points, with 1.6 billion points classified as part of the cave floor. This point cloud was processed to produce a basemap that can be used in GIS, where natural and anthropogenic features are clearly visible and can be traced to create accurate 2D maps similar to traditional cartography.\n","PeriodicalId":30633,"journal":{"name":"ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences","volume":"17 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A METHODOLOGY FOR CAVE FLOOR BASEMAP SYNTHESIS FROM POINT CLOUD DATA: A CASE STUDY OF SLAM-BASED LIDAR AT LAS CUEVAS, BELIZE\",\"authors\":\"H. Lozano Bravo, E. Lo, H. Moyes, D. Rissolo, S. Montgomery, F. Kuester\",\"doi\":\"10.5194/isprs-annals-x-m-1-2023-179-2023\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract. Creating cave maps is an essential part of cave research. Traditional cartographic efforts are extremely time consuming and subjective, motivating the development of new techniques using terrestrial lidar scanners and mobile lidar systems. However, processing the large point clouds from these scanners to produce detailed, yet manageable “maps” remains a challenge. In this work, we present a methodology for synthesizing a basemap representing the cave floor from large scale point clouds, based on a case study of a SLAM-based lidar data acquisition from a cave system in the archaeological site of Las Cuevas, Belize. In 4 days of fieldwork, the 335 m length of the cave system was scanned, resulting in a point cloud of 4.1 billion points, with 1.6 billion points classified as part of the cave floor. This point cloud was processed to produce a basemap that can be used in GIS, where natural and anthropogenic features are clearly visible and can be traced to create accurate 2D maps similar to traditional cartography.\\n\",\"PeriodicalId\":30633,\"journal\":{\"name\":\"ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences\",\"volume\":\"17 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5194/isprs-annals-x-m-1-2023-179-2023\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Environmental Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5194/isprs-annals-x-m-1-2023-179-2023","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Environmental Science","Score":null,"Total":0}
A METHODOLOGY FOR CAVE FLOOR BASEMAP SYNTHESIS FROM POINT CLOUD DATA: A CASE STUDY OF SLAM-BASED LIDAR AT LAS CUEVAS, BELIZE
Abstract. Creating cave maps is an essential part of cave research. Traditional cartographic efforts are extremely time consuming and subjective, motivating the development of new techniques using terrestrial lidar scanners and mobile lidar systems. However, processing the large point clouds from these scanners to produce detailed, yet manageable “maps” remains a challenge. In this work, we present a methodology for synthesizing a basemap representing the cave floor from large scale point clouds, based on a case study of a SLAM-based lidar data acquisition from a cave system in the archaeological site of Las Cuevas, Belize. In 4 days of fieldwork, the 335 m length of the cave system was scanned, resulting in a point cloud of 4.1 billion points, with 1.6 billion points classified as part of the cave floor. This point cloud was processed to produce a basemap that can be used in GIS, where natural and anthropogenic features are clearly visible and can be traced to create accurate 2D maps similar to traditional cartography.