The archaeology of Amerindian settlements in the Caribbean has mostly been identified through scatters of artefacts; predominantly conglomerations of shells, ceramics and lithics. While archaeological material may not always be visible on the surface, particular settlement patterns may be identifiable by a topography created through cultural action: earthen mounds interchanging with mostly circular flattened areas. In northern Hispaniola, recent foot surveys have identified more than 200 pre-colonial sites of which several have been mapped in high resolution. In addition, three settlements with topographical characteristics have been extensively excavated, confirming that the mounds and flattened areas may have had a cultural connotation in this region. Without the availability of high resolution LiDAR (Light Detection and Ranging) data, a photogrammetric approach using UAS (unmanned aircraft system, commonly known as drones) can fill the knowledge gap on a local scale, providing fast and reliable data collection and precise results. After photogrammetric processing, digital clearance of vegetation, and extraction of the georeferenced DEM (digital elevation model) and orthophoto, filters and enhancements provide an opportunity to visualize the results in GIS. The outcome provides an overview of site size, and distribution of mounds and flattened areas. Measurement of the topographic changes in a variety of past settlements defines likely zones of habitat, and provides clues on the actual dimensions and density of living space. Understanding the relation of the mounds and adjacent flat areas within their environment allows a discussion on how, and for what purpose, the settlement was founded at a particular location, and provides clues about its spatial organization.
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Παρασκευή 23 Σεπτεμβρίου 2016
Remote Sensing, Vol. 8, Pages 791: Mapping Indigenous Settlement Topography in the Caribbean Using Drones
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Αλέξανδρος Γ. Σφακιανάκης Medicine by Alexandros G. Sfakianakis,Anapafseos 5 Agios Nikolaos 72100 Crete Greece,00302841026182,0030693260717...
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heory of COVID-19 pathogenesis Publication date: November 2020Source: Medical Hypotheses, Volume 144Author(s): Yuichiro J. Suzuki ScienceD...
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