Testing a Multi-Modal Remote Sensing Approach for Detecting Ancient Maya Sites With Low-Resolution Data

Summary

In the absence of LiDAR and similar high-resolution data products, an alternative approach was developed to model and predict site location information from low-resolution, publicly available datasets such as ASTER, LANDSAT, and aerial photographs. Manipulating and combining the analyses of multiple datasets permits refinement of modeling and detection capabilities. A large database of known sites, in assorted topographic and vegetative conditions and degrees of exposure, was used as a training model to test and improve the accuracy of the method, followed by ground truthing of initial results and subsequent model refinement. In addition to use of this model for detection on its own, the method results could also be used for quickly identifying and targeting areas of interest in higher resolution products such as LiDAR, if and when they become available.

This Resource is Part of the Following Collections

• Society for American Archaeology 83rd Annual Meeting, Washington, DC (2018)

Keywords

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Record Identifiers

Abstract Id(s): 21922