Testing Web Mapping and Active Learning to Approach Lidar Data

Abstract

ABSTRACTAfter acquiring 91 km2 of lidar data from the Zacapu region, West Mexico, we confronted a series of issues that most archaeologists using this technology face. These include the large volume of data available, the limited training of potential “analysts,” the difficult development of a collective mapping tool and protocol, and the reliability of desk-based interpretation of archaeological features. In this article, we present an initiative conducted in 2015 and 2017 as an attempt to answer these methodological and pedagogical issues. We developed a web mapping platform to collectively interpret archaeological features using lidar-derived imagery and to train volunteer students to participate in this desk-based web mapping within a crowdsourcing framework. After evaluating the results of this initiative, we discuss the potential and limitations of this method for both lidar-based research and future training.