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95 results for “prehistoric”
Anyskop Blowout Prehistoric Dataset, Western Cape, South Africa
<p>These Stone Age archaeological datasets were collected in 2001 and 2002 by a team from the Department of Early Prehistory and Quaternary Ecology of the University of Tübingen (Germany) headed by Nicholas J. Conard. Many South African researchers collaborated on this project, with Pippa Haarhoff, John Compton, Dave Roberts, and Stephan Woodborne deserving special mention.</p> <p>The field work took place at the Anyskop Blowout (ANY1) located within the West Coast Fossil Park near Langebaanweg, Western Cape, South Africa. The field work was conducted with the help of students from the universities of Tübingen and Cape Town. The datasets are predominantly in English (with some German as well) and include field data in the MAIN table. Further analytical data for many classes of artifacts include: LITHICS, FAUNA, POTTERY, MODERN, BUCKETS, REFITS.</p> <p>All collected materials are curated by the Iziko South African Museums in Cape Town under accession numbers SAM-AA-8903 (finds collected by other teams before 2001) and SAM-AA-9007 (finds from this study, 2001-2002). Some of the finds are exhibited in the museum at the West Coast Fossil Park.</p> <p>Funding for this research project came mainly from the German Research Foundation (DFG - CO 226/5-1, 5-2, 5-5 and 5-6) and the University of Tübingen. Significant support was provided by the Iziko South African Museums, the West Coast Fossil Park, and the University of Cape Town.</p>
ALS-based DEMs (100 cm): the dynamics of the prehistoric communities located in the Mostiștea Valley and Danube Plain (between Oltenița and Călărași)
<p>This dataset is part of a larger project on the dynamics of the prehistoric communities located in the Mostiștea Valley and Danube Plain (between Oltenița and Călărași), supervised by the ArchaeoSciences Division of the Research Institute of the University of Bucharest (ICUB) and Kiel University (Germany), in partnership with HOGENT, University of Applied Sciences and Arts (Belgium), Museum of Bucharest, Museum of the Lower Danube Călărași, Museum of Gumelnița Civilization Oltenița, and "Vasile Pârvan" Institute of Archaeology (Romania), under the "Sultana School of Archaeology" initiative.</p> <p>Spatial data play a crucial role in archaeological research, and orthophotos, digital elevation models, and 3D models are frequently used for the mapping, documentation, and monitoring of archaeological sites. Thanks to the availability of compact and low-cost uncrewed airborne vehicles, the use of UAV-based photogrammetry is well matured in this field over the last two decades. More recently, compact airborne systems are also available that allow the recording of thermal data, multispectral data, and airborne laser scanning. For this project, various platforms and sensors are applied at the Chalcolithic archaeological sites in the Mostiștea Basin and Danube Valley (Southern Romania). By analyzing the performance of the systems and the resulting data, insight is given into the selection of the appropriate system for the right application. This analysis requires thorough knowledge of data acquisition and data processing as well. As both laser scanning and photogrammetry typically result in very large amounts of data, a special focus is also required on the storage and publication of the data. Hence, the objective of this project is to provide a full overview of various aspects of 3D data acquisition for UAV-based mapping. Based on the conclusions drawn in our related publications, it is stated that photogrammetry and laser scanning can result in data with similar geometrical properties when acquisition parameters are appropriately set. On the one hand, however, the used ALS-based system outperforms the photogrammetric platforms in terms of operational time and the area covered. On the other hand, conventional photogrammetry provides flexibility that might be required for very low-altitude flights, or emergency mapping. Furthermore, as the used ALS sensor only provides a geometrical representation of the topography, photogrammetric sensors are still required to obtain true color- or false color composites of the surface. Lastly, the variety of data, like pre- and post-rendered raster data, 3D models, and point clouds, requires the implementation of multiple methods for the online publication of data. Various client-side and server-side solutions are presented to make the data available for other researchers.</p>
MS-based orthophotos (50 cm): the dynamics of the prehistoric communities located in the Mostiștea Valley and Danube Plain (between Oltenița and Călărași)
<p>This dataset is part of a larger project on the dynamics of the prehistoric communities located in the Mostiștea Valley and Danube Plain (between Oltenița and Călărași), supervised by the ArchaeoSciences Division of the Research Institute of the University of Bucharest (ICUB) and Kiel University (Germany), in partnership with HOGENT, University of Applied Sciences and Arts (Belgium), Museum of Bucharest, Museum of the Lower Danube Călărași, Museum of Gumelnița Civilization Oltenița, and "Vasile Pârvan" Institute of Archaeology (Romania), under the "Sultana School of Archaeology" initiative.</p> <p>Spatial data play a crucial role in archaeological research, and orthophotos, digital elevation models, and 3D models are frequently used for the mapping, documentation, and monitoring of archaeological sites. Thanks to the availability of compact and low-cost uncrewed airborne vehicles, the use of UAV-based photogrammetry is well matured in this field over the last two decades. More recently, compact airborne systems are also available that allow the recording of thermal data, multispectral data, and airborne laser scanning. For this project, various platforms and sensors are applied at the Chalcolithic archaeological sites in the Mostiștea Basin and Danube Valley (Southern Romania). By analyzing the performance of the systems and the resulting data, insight is given into the selection of the appropriate system for the right application. This analysis requires thorough knowledge of data acquisition and data processing as well. As both laser scanning and photogrammetry typically result in very large amounts of data, a special focus is also required on the storage and publication of the data. Hence, the objective of this project is to provide a full overview of various aspects of 3D data acquisition for UAV-based mapping. Based on the conclusions drawn in our related publications, it is stated that photogrammetry and laser scanning can result in data with similar geometrical properties when acquisition parameters are appropriately set. On the one hand, however, the used ALS-based system outperforms the photogrammetric platforms in terms of operational time and the area covered. On the other hand, conventional photogrammetry provides flexibility that might be required for very low-altitude flights, or emergency mapping. Furthermore, as the used ALS sensor only provides a geometrical representation of the topography, photogrammetric sensors are still required to obtain true color- or false color composites of the surface. Lastly, the variety of data, like pre- and post-rendered raster data, 3D models, and point clouds, requires the implementation of multiple methods for the online publication of data. Various client-side and server-side solutions are presented to make the data available for other researchers.</p>
ArcGIS Map Packages and GIS Data for: A Geospatial Method for Estimating Soil Moisture Variability in Prehistoric Agricultural Landscapes, Gillreath-Brown et al. (2019)
<p><strong>ArcGIS Map Packages and GIS Data for Gillreath-Brown, Nagaoka, and Wolverton (2019)</strong></p> <p>**When using the GIS data included in these map packages, please cite all of the following:</p> <blockquote> <p>Gillreath-Brown, Andrew, Lisa Nagaoka, and Steve Wolverton. A Geospatial Method for Estimating Soil Moisture Variability in Prehistoric Agricultural Landscapes, 2019. PLoSONE 14(8):e0220457. <a href="http://doi.org/10.1371/journal.pone.0220457">http://doi.org/10.1371/journal.pone.0220457</a></p> <p>Gillreath-Brown, Andrew, Lisa Nagaoka, and Steve Wolverton. ArcGIS Map Packages for: A Geospatial Method for Estimating Soil Moisture Variability in Prehistoric Agricultural Landscapes, Gillreath-Brown et al., 2019. Version 1. Zenodo. <a href="https://doi.org/10.5281/zenodo.2572018">https://doi.org/10.5281/zenodo.2572018</a></p> </blockquote> <p><strong>OVERVIEW OF CONTENTS</strong></p> <p>This repository contains map packages for Gillreath-Brown, Nagaoka, and Wolverton (2019), as well as the raw digital elevation model (DEM) and soils data, of which the analyses was based on. The map packages contain all GIS data associated with the analyses described and presented in the publication. The map packages were created in ArcGIS 10.2.2; however, the packages will work in recent versions of ArcGIS. (Note: I was able to open the packages in ArcGIS 10.6.1, when tested on February 17, 2019). The primary files contained in this repository are:</p> <ul> <li>Raw DEM and Soils data <ul> <li>Digital Elevation Model Data (Map services and data available from U.S. Geological Survey, National Geospatial Program, and can be downloaded from the <a href="https://viewer.nationalmap.gov/basic/">National Elevation Dataset</a>) <ul> <li><strong>DEM_Individual_Tiles</strong>: Individual DEM tiles prior to being merged (1/3 arc second) from USGS National Elevation Dataset.</li> <li><strong>DEMs_Merged</strong>: DEMs were combined into one layer. Individual watersheds (i.e., Goodman, Coffey, and Crow Canyon) were clipped from this combined DEM. </li> </ul> </li> <li> Soils Data (Map services and data available from <a href="https://data.nal.usda.gov/dataset/natural-resources-conservation-service-web-soil-survey">Natural Resources Conservation Service Web Soil Survey</a>, U.S. Department of Agriculture) <ul> <li><strong>Animas-Dolores_Area_Soils</strong>: Small portion of the soil mapunits cover the northeastern corner of the Coffey Watershed (CW).</li> <li><strong>Cortez_Area_Soils</strong>: Soils for Montezuma County, encompasses all of Goodman (GW) and Crow Canyon (CCW) watersheds, and a large portion of the Coffey watershed (CW).</li> </ul> </li> </ul> </li> <li>ArcGIS Map Packages <ul> <li><strong>Goodman_Watershed_Full_SMPM_Analysis</strong>: Map Package contains the necessary files to rerun the SMPM analysis on the full Goodman Watershed (GW).</li> <li><strong>Goodman_Watershed_Mesa-Only_SMPM_Analysis</strong>: Map Package contains the necessary files to rerun the SMPM analysis on the mesa-only Goodman Watershed.</li> <li><strong>Crow_Canyon_Watershed_SMPM_Analysis</strong>: Map Package contains the necessary files to rerun the SMPM analysis on the Crow Canyon Watershed (CCW).</li> <li><strong>Coffey_Watershed_SMPM_Analysis</strong>: Map Package contains the necessary files to rerun the SMPM analysis on the Coffey Watershed (CW).</li> </ul> </li> </ul> <p>For additional information on contents of the map packages, please see see "Map Packages Descriptions" or open a map package in ArcGIS and go to "properties" or "map document properties."</p> <p><strong>LICENSES</strong></p> <p>Code: <a href="http://opensource.org/licenses/MIT">MIT</a> year: 2019 <br> Copyright holders: Andrew Gillreath-Brown, Lisa Nagaoka, and Steve Wolverton</p> <p><strong>CONTACT</strong></p> <p><strong>Andrew Gillreath-Brown, PhD Candidate, RPA</strong><br> <a href="https://anthro.wsu.edu/">Department of Anthropology</a>, Washington State University<br> <a href="mailto:andrew.brown1234@gmail.com">andrew.brown1234@gmail.com</a> – Email<br> <a href="https://andrewgillreathbrown.wordpress.com/">andrewgillreathbrown.wordpress.com</a> – Web</p>
FIG. 5. — Undated female red deer upper left canine from Abri des Autours. A in The worked bone industry and intrusive fauna associated with the prehistoric cave burials of Abri des Autours (Belgium)
FIG. 5. — Undated female red deer upper left canine from Abri des Autours. A, general view; B, detail of perforation; C, detail of the crown with remaining traces of enamel (arrow). Scale bars: A, 10 mm; B, C, 1 mm.
FIG. 7 in The worked bone industry and intrusive fauna associated with the prehistoric cave burials of Abri des Autours (Belgium)
FIG. 7. — Needle made of a suid left fibula, from the Neolithic collective burial at Abri des Autours: A, general view; B, detail of the tip showing a smooth polish associated with fine and short striations; C, detail of the posterior edge near the point, showing fine parallel striations; D, detail of the posterior edge at the midpoint of the tool, showing smooth polish. Scale bars: A, 10 mm; B, C, D, 150 μm.
FIG. 2 in The worked bone industry and intrusive fauna associated with the prehistoric cave burials of Abri des Autours (Belgium)
FIG. 2. — Plan of Abri des Autours: A, circular depression; B, rubble of old (unpublished) excavations; C, crack in the rock; D, pit under low wall (from Polet & Cauwe 2007).
FIG. 6 in The worked bone industry and intrusive fauna associated with the prehistoric cave burials of Abri des Autours (Belgium)
FIG. 6. — Pointed rib of a large bovid, from the Neolithic collective burial at Abri des Autours: A, general view (from left to right: internal, centre and external views); B, detail of the tip (internal view) showing some polish; C, detail of the tip (internal view) showing fine perpendicular striations; D, detail of a lateral edge of the rib devoid of striations. Scale bars: A, 10 mm; B, 500 μm; C, D, 100 μm.
FIG. 3 in The worked bone industry and intrusive fauna associated with the prehistoric cave burials of Abri des Autours (Belgium)
FIG. 3. — Stratigraphy of Abri des Autours, east–west profile (modified from Cauwe 1994): 1a, b, clay, without pebbles; 2, as layer 6, but with more clay; 3a, brown, argillaceous deposit with small, densely dispersed pebbles; 3b, as layer 3a, but less humic. Contains the Neolithic multiple burial; 3c, as layer 3a, but strongly compacted by calcite precipitations; 4, clay with fine pebbles; 5a, b, cryoclastic deposit without humic or clayish fraction; layer 5b corresponds to very fine gravels, while layer 5a includes larger elements. The Mesolithic single burial extends through both of these layers; 6, brown-grey clayey deposit, strongly inclined. Contains the Mesolithic collective burial; 7, cryoclastic layer, included in clayey orange-brown sediment; 8, thin pebble deposit mixed with greyish sediment; 9, low wall constructed of unworked stone blocks.
Piburgersee core meta data repository for the publication "Seismic control of large prehistoric rockslides in the Eastern Alps"
<p>This dataset comprises the core meta data of Plansee, which is the basis for the publication Oswald et al. "Seismic control of large prehistoric rockslides in the Eastern Alps".</p> <p>The core meta data belongs to a 8m long sediment core composed of 12 individual core sections (see Plansee_core_data.xlsx). For each individual core section the core image (_coreimage.jpg), the CT data (_CT.rar), XRF data, (_XRF.txt) and multi-sensor core logging data (_MSCL.csv) are provided.</p>
Plansee seismic and core meta data repository for the publication "Seismic control of large prehistoric rockslides in the Eastern Alps"
<p>This dataset comprises the raw seismic data and core meta data of Plansee, which is the basis for the publication Oswald et al. "Seismic control of large prehistoric rockslides in the Eastern Alps".</p> <p>Seismic profiles are provided as .SGY files (Plansee_seismics_SGYfiles.rar)</p> <p>The core meta data belongs to a 7m long sediment core composed of 10 individual core sections (see Plansee_core_data.xlsx). For each individual core section the core image (_coreimage.jpg), the CT data (_CT.rar) and multi-sensor core logging data (_MSCL.csv) are provided.</p>
FIG. 10 in The biometry of prehistoric Alpine sheep: exploring four millennia of human-sheep interaction by means of osteometry
FIG. 10. — LSI of sheep bone width measurements in statistically meaningful Early/Middle Bronze Age find complexes. For Barche di Solferino, see Figure 7.
FIG. 5 in The biometry of prehistoric Alpine sheep: exploring four millennia of human-sheep interaction by means of osteometry
FIG. 5. — LSI of sheep bone width measurements in broad chronological subdivision. For the results of the significance test, see Table 3.
FIG. 4 in The biometry of prehistoric Alpine sheep: exploring four millennia of human-sheep interaction by means of osteometry
FIG. 4. — The LSI median values of width measurements compared with the shoulder height of sheep in individual find complexes. Furthermore, sample size in shoulder height values is considered. Abbreviations: BA, Bronze Age; EBA, Early Bronze Age; EIA, Early Iron Age; IA, Iron Age; LBA, Late Bronze Age; LIA, Late Iron Age; MBA, Middle Bronze Age; NCA, Neolithic/Copper Age. Site numbering, see Tables 1, 2.
FIG. 9 in The biometry of prehistoric Alpine sheep: exploring four millennia of human-sheep interaction by means of osteometry
FIG. 9. — LSI of sheep bone width measurements in Neolithic/Copper Age archaeofaunas. For the results of the significance test, see Table 3.
FIG. 6 in The biometry of prehistoric Alpine sheep: exploring four millennia of human-sheep interaction by means of osteometry
FIG. 6. — LSI of sheep bone width measurements in several micro-regions (for the results of the significance test see Table 3). The sites are arranged in chronological orders and numbering refers to Table 1. Abbreviations: a, Northern Pre-Alps and Limestone Alps; b, Inn Valley; BA, Bronze Age; c,Val Venosta; d, Isarco Valley; e, Adige Valley and surroundings; EBA, Early Bronze Age; EIA, Early Iron Age; ELT, Early La Tène Period; f, Southern drop of the Alps with Lessinian Mountains and Northern Padanian Plain;IA, Iron Age; LBA, Late Bronze Age; LIA, Late Iron Age; LLT, Late La Tène Period; MBA, Middle Bronze Age; MLT, Middle La Tène Period; NCA, Neolithic/Copper Age.
FIG. 1 in The biometry of prehistoric Alpine sheep: exploring four millennia of human-sheep interaction by means of osteometry
FIG. 1. — The percentage of the main livestock species animals in Prehistoric Alpine find complexes., Neolithic/Copper Age;, Bronze Age;, Iron Age. Site numbering, see Table 1.
FIG. 11 in The biometry of prehistoric Alpine sheep: exploring four millennia of human-sheep interaction by means of osteometry
FIG. 11. — The Bronze Age sheep populations of the Northern Alpine Foreland and the Inn Valley in LSI comparison. For the results of the significance test, see Table 3.
The transmission of pottery technology amongst prehistoric European hunter-gatherers: code and data
<p>Included in this paper are the data files which enable the main analytical findings of the paper to be reproduced. Some aspects of the spatial-temporal modelling will heavily depend on the user’s configuration and the digital elevation model available, so intermediate data that support the main conclusions of the paper have been included in the data repository. </p>
3D models: the dynamics of the prehistoric communities located in the Mostiștea Valley and Danube Plain (between Oltenița and Călărași)
<p>This dataset is part of a larger project on the dynamics of the prehistoric communities located in the Mostiștea Valley and Danube Plain (between Oltenița and Călărași), supervised by the ArchaeoSciences Division of the Research Institute of the University of Bucharest (ICUB) and Kiel University (Germany), in partnership with HOGENT, University of Applied Sciences and Arts (Belgium), Museum of Bucharest, Museum of the Lower Danube Călărași, Museum of Gumelnița Civilization Oltenița, and "Vasile Pârvan" Institute of Archaeology (Romania), under the "Sultana School of Archaeology" initiative.</p> <p>Spatial data play a crucial role in archaeological research, and orthophotos, digital elevation models, and 3D models are frequently used for the mapping, documentation, and monitoring of archaeological sites. Thanks to the availability of compact and low-cost uncrewed airborne vehicles, the use of UAV-based photogrammetry is well matured in this field over the last two decades. More recently, compact airborne systems are also available that allow the recording of thermal data, multispectral data, and airborne laser scanning. For this project, various platforms and sensors are applied at the Chalcolithic archaeological sites in the Mostiștea Basin and Danube Valley (Southern Romania). By analyzing the performance of the systems and the resulting data, insight is given into the selection of the appropriate system for the right application. This analysis requires thorough knowledge of data acquisition and data processing as well. As both laser scanning and photogrammetry typically result in very large amounts of data, a special focus is also required on the storage and publication of the data. Hence, the objective of this project is to provide a full overview of various aspects of 3D data acquisition for UAV-based mapping. Based on the conclusions drawn in our related publications, it is stated that photogrammetry and laser scanning can result in data with similar geometrical properties when acquisition parameters are appropriately set. On the one hand, however, the used ALS-based system outperforms the photogrammetric platforms in terms of operational time and the area covered. On the other hand, conventional photogrammetry provides flexibility that might be required for very low-altitude flights, or emergency mapping. Furthermore, as the used ALS sensor only provides a geometrical representation of the topography, photogrammetric sensors are still required to obtain true color- or false color composites of the surface. Lastly, the variety of data, like pre- and post-rendered raster data, 3D models, and point clouds, requires the implementation of multiple methods for the online publication of data. Various client-side and server-side solutions are presented to make the data available for other researchers.</p>
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