Abstract
Mapping cave passages using modern techniques such as Light Detection and Ranging (LiDAR) and photogrammetry are still in the juvenile stages. Newer technologies such as Simultaneous Location and Mapping (SLAM) LiDAR and faster computers have enabled speleologists to map caves much faster than traditional methods. From a land management perspective, the ability to efficiently collect detailed cave maps with reasonable precision quickly is crucial for decision making. The ongoing challenge with digital cave mapping using mobile LiDAR and photogrammetry techniques is geolocating the point-cloud underground. Mobile scanning methods can be tied to ground control points on the surface using high precision Global Navigation Satellite System (GNSS) receivers. By starting scans at the surface, entering, and then exiting the cave, the control points at the surface allow the SLAM algorithm to locate voids in space. This method only works so far, roughly 20 to 30 minutes, before the SLAM algorithm and Inertial Measurement Unit (IMU) start to iteratively collect errors and wander. Within GNSS denied environments, other methods must be employed to geolocate LiDAR data deeper into cave passages. Traditional cave surveying methods are geolocated by successively surveying and tying underground points to a control point near the cave entrance. We propose to marry digital cave mapping techniques with more traditional methods. Together, modern and traditional cave survey methods can tie in control points within caves to quickly produce geolocated cave maps within a Geographical Information System (GIS) because extensive measurements and sketches are not needed at each station. A visual comparison of point-cloud data to a line plot from a traditional survey confirms that the combination of these methods can efficiently produce geolocated cave maps, however the accuracy of these data are not well established. We propose that this technique can then be used by land management agencies to quickly gather cave data that will inform decisions about land use and placement of infrastructure.
Rights Information
DOI
https://doi.org/10.5038/9781967518012.1018
General Overview Map
Salaz-fig.2.tif (147 kB)
Sketch of control points in cave
Salaz-fig.3.tif (159 kB)
Sketch of walking control points
Salaz-fig.4.tif (1849 kB)
ArcScene of cave
Salaz-fig.5.tif (1197 kB)
Revised-Different ArcScene views of cave
Salaz-fig.6.tif (313 kB)
Revised-CloudComopare of scans map/profile view
Salaz-fig.7.tif (124 kB)
Revised-CloudComopare of scans with measurements
Salaz-fig.8.jpg (5267 kB)
Photo of scanner and control point
Mobile LIDAR Scans of Caves: Methods for Tying in Ground Control Points
Mapping cave passages using modern techniques such as Light Detection and Ranging (LiDAR) and photogrammetry are still in the juvenile stages. Newer technologies such as Simultaneous Location and Mapping (SLAM) LiDAR and faster computers have enabled speleologists to map caves much faster than traditional methods. From a land management perspective, the ability to efficiently collect detailed cave maps with reasonable precision quickly is crucial for decision making. The ongoing challenge with digital cave mapping using mobile LiDAR and photogrammetry techniques is geolocating the point-cloud underground. Mobile scanning methods can be tied to ground control points on the surface using high precision Global Navigation Satellite System (GNSS) receivers. By starting scans at the surface, entering, and then exiting the cave, the control points at the surface allow the SLAM algorithm to locate voids in space. This method only works so far, roughly 20 to 30 minutes, before the SLAM algorithm and Inertial Measurement Unit (IMU) start to iteratively collect errors and wander. Within GNSS denied environments, other methods must be employed to geolocate LiDAR data deeper into cave passages. Traditional cave surveying methods are geolocated by successively surveying and tying underground points to a control point near the cave entrance. We propose to marry digital cave mapping techniques with more traditional methods. Together, modern and traditional cave survey methods can tie in control points within caves to quickly produce geolocated cave maps within a Geographical Information System (GIS) because extensive measurements and sketches are not needed at each station. A visual comparison of point-cloud data to a line plot from a traditional survey confirms that the combination of these methods can efficiently produce geolocated cave maps, however the accuracy of these data are not well established. We propose that this technique can then be used by land management agencies to quickly gather cave data that will inform decisions about land use and placement of infrastructure.