The Use of Lidar Data to Identify Ancient and Modern Structures in the Teotihuacan Valley



Bonomo, Kira A

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Archaeologists spend considerable time and effort manually identifying landscape features on maps. This thesis explores the analysis of lidar data by developing and applying automated methods of feature identification and classification, which could ease and hasten the current process. Lidar data of an approximately 170 km2 area of the Teotihuacan Valley, northeast of Mexico City, Mexico, were used. Features for identification were field system terrace edges, springs, and structures. Spatial analysis and filtering of the lidar imagery was pursued predominantly using ArcGIS and Matlab. The automated identification of the feature types was inconclusive because of the complexities of the landscapes and the limitations of the available methodologies. Current methodologies remain suitable for enhancing the manual classification of landscapes using remote sensing data.


This thesis has been embargoed for 2 years and will not be available until May 2020 at the earliest.


Teotihuacan, Archaeology, Spatial filters, Lidar, GIS, Feature recognition