Long Range Scanning
Introduction | Long Range Scanning | Short Range Scanning
Long range data collection using the Optech ILRIS - 3D scan system took place during both the 2005 and 2006 field seasons. The scan objectives in 2005 focused on the collection of high density survey data for the Kalasasaya, the Putuni, and the Templeté monuments as well as for the Poncé and Puerta del Sol  monoliths, all located in the Monumental Core of Tiwanaku. The 2006 project team scanned areas of the Monumental Core that were not acquired during the previous year's survey and also scanned newly excavated stone architecture around the base of the Akapana Pyramid.
Akapana
The primary targets of interest with respect to the Akapana area were the newly excavated trenches around the base of the pyramid. These trenches were located on the east, north and west sides of the Akapana and exhibit some of the only remaining architecture undisturbed by colonial period occupation of the area. The areas exposed by recent excavation exhibit the nature of Tiwanaku construction which is characterized by revetments and buttressing, yielding the stepped pyramidal form of the Akapana. These trenches were scanned at a resolution of one centimeter in an attempt to resolve individual stones used in the construction of the structure. These data collected at the Akapana document some of the only remaining undisturbed architecture existing at the site.
Kalasasaya
The Kalasasaya is the largest of the stone monuments in the Monumental Core area measuring approximately 120 X 130 meters. The outer retaining walls of the monument average three to four meters in height and consist of large andesite pillars separated by smaller rectangular stones. There are also a series of inner walls within the temple structure. Given the monement's size and structural complexity, the Kalasasaya was scanned at resolution of three centimeters. The resulting data set is largely complete for the stone architecture of the structure. However a large portion of the ground area in the northeast corner of the monument is not present in the final data set to due limited availability of adequate scan locations. Methods are currently being tested to supplement these areas with topographic information obtained from the Mapping section of the project.
Putuni
Given the nature of the Putuni ruins, this monument was scanned from numerous locations around its perimeter in close proximity to the structure. A total of 88 scans were necessary to document the outside and inside walls.
Templeté
The semi-subterranean Templeté
Data Processing Summary
The majority of the scan data for each large monument were quickly processed in the field to ensure adequate overlap between scans and the completeness of each dataset. Upon returning from the field, the data were processed in full detail. The individual scans have been parsed, cleaned, segmented, assembled, aligned, and meshed to create accurate 3D models of the structures scanned. The parsing process converts the data from the proprietary format of the Optech scanner during data collection. Cleaning removes extraneous data, such as that from vegetation, areas scanned beyond the monuments, etc. The scans of large areas are then segmented into smaller sub-scans for the purpose of importing into the processing software. Processing was conducted using InnovMetric's Polyworks software suite. This software utilizes advanced algorithms for all stages of processing 3D scan data. Segmenting the large scans enables the operator to tailor each algorithm's parameters to better fit the parameters of the data. Most importantly, scan segmentation allows for the compensation of beam divergence, the property of the laser beam that is measuring the 3D survey points to spread as it travels across large distances. By segmenting the scans, a better quality surface can be derived from the 3D survey points. Assembling the scans entails manually positioning scans to the same relative orientation and matching common points between each of the individual scans. These points bring the two scans into relative alignment based on the common points chosen. This is followed by the application of complex computer algorithms that consider all points in the scan and 'fits' the scans together very precisely. While the shift made between the scans is minute in the area of overlap, the effect of this shift on survey data scanned meters or tens of meters away is considerable. After the individual scans were assembled and precisely aligned, the process of overlap reduction was undertaken. Overlap reduction serves to eliminate redundant data between scans. While overlapping areas are necessary to match the individual scans together as demonstrated above, this data can be removed once the scans are assembled. Care was taken during the overlap reduction process to retain the most accurate data possible.
Data Distribution
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