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Dataset results
7 results for “Landscape Archaeology”
Destruction of the Cultural-Archaeological Landscape in the Gaza Strip
This dataset contains 10 archaeological sites in Gaza strip destroyed during the war 2023-2024. The dataset was compiled by Ministry of Tourism & Antiquities of Palestine (MOTA) team, Dr. Sufyan Deis.
Supplementary GIS data - Potential and implications of automated pre-processing of LiDAR-based digital elevation models for large-scale archaeological landscape analysis
<p>A supplementary dataset related to the paper discussing preparation of a digital elevation model derived from DMR 5G (LiDAR-based DEM of the Czech Republic) cleaned of modern artificial features. It includes data used as a clipping mask and data produced during the testing phase.</p> <p>Contents:</p> <ul> <li>..\clipping_buffers.gdb\ - Clipping buffers based on ZABAGED dataset used for masking the original data stored as ESRI geodatabase.</li> <li>..\drainages\ - Drainages with Strahler order higher than four (potential watercourses) for the original and filtered DEMs. <ul> <li>drainages_filtered - Drainges identified in the filtered DEM stored as GeoTIFF.</li> <li>drainages_original - Drainges identified in the original DEM stored as GeoTIFF. </li> </ul> </li> <li>..\LSC\ - Locations with significant land surface curvature for the original and filtered DEMs. <ul> <li>LSC_filtered - Significant LSC identified in the filtered DEM stored as GeoTIFF. </li> <li>LSC_original - Significant LSC identified in the original DEM stored as GeoTIFF. </li> </ul> </li> <li>..\visibility\ - Viewsheds computed over the original and filtered DEMs. <ul> <li>Libice\ - Sample viewsheds computed for the early medieval hillfort of Libice. <ul> <li>Libice_visibility_filtered - Viewshed based on the filtered DEM stored as GeoTIFF. </li> <li>Libice_visibility_original - Viewshed based on the original DEM stored as GeoTIFF. </li> <li>observer_points - Observer points used for calculating the viewsheds.</li> </ul> </li> <li>regular_grid\ - Cumulative viewsheds calculated for regularly spaced points in a 10 x 10 km grid with a visibility radius of 5 km and an observer height of 2 m; a total of 574 viewsheds. <ul> <li>visibility_filtered - Cumulative viewshed for the filtered DEM stored as GeoTIFF.</li> <li>visibility_original - Cumulative viewshed for the original DEM stored as GeoTIFF. </li> <li>visibility_test_buffers - Buffers used for the viewshed calculations stored as ESRI shapefile.</li> <li>visibility_test_observers - Observer points used for the viewshed calculations stored as ESRI shapefile.</li> </ul> </li> </ul> </li> </ul> <p> </p> <p>Preprint version of the related paper:</p> <p>Novák, David and Pružinec, Filip, Potential and Implications of Automated Pre-Processing of Lidar-Based Digital Elevation Models for Large-Scale Archaeological Landscape Analysis. Available at SSRN: <a href="https://ssrn.com/abstract=4063514">https://ssrn.com/abstract=4063514</a></p>
Data and scripts for the paper Building a Low-cost UAV-based LiDAR Sensor for Landscape Archaeology
<p>This repository contains the modified OpenMMS scripts for Linux and Raspberry Pi firmware for LiDAR sensor presented in the paper Building a Low-cost UAV-based LiDAR Sensor for Landscape Archaeology at the CAA 2024 conference in Auckland, New Zealand. Included are the LiDAR and trajectory data collected at the site of Antiochia ad Cragum in 2022 in an area roughly north-east of what is known as the Small Bath Area. Each zip file contains two adjacent flights oriented either principally east-west or north-south. The four flights cover the same area in an overlapping pattern.</p> <p>The LiDAR and trajectory data are released under the Creative Commons Attribution 4.0 International license and the modified OpenMMS firmware and scripts are released under the original GNU GPL v3.0 or later license.</p>
Stonehenge LiDAR Archaeology Landscape
A LiDAR landscape of the key archaeological features around Stonehenge including Stonehenge itself, The Avenue, the Cursus and numerous barrow burial mounds. The 1 metre LiDAR is only partial at Stonehenge with many of the sites to the west not included in the current opendata coverage. This is a digital terrain model version which represents the bare ground surface only so prominent buildings, trees and even the stones of the Stonehenge circles are stripped off in this case. Created using 1 metre DTM LiDAR opendata provided by the Environment Agency. Built in QGIS using the QGIS2threeJS plugin. Thanks to Mike Gill of the Avon Valley Archaeological Society for the python code which converts QGIS models into a format compatible with Sketchfab. Best viewed full screen and in HD (see options at bottom of model view). Feel free to share on various media, download, or embed on your website using the embed code. Source: Objaverse 1.0 / Sketchfab
Data from: Mapping Tasmania's cultural landscapes: using habitat suitability modelling of archaeological sites as a landscape history tool
Aim: Understanding past distributions of people across the landscape is key to understanding how people used, affected and related to the natural environment. Here we use habitat suitability modelling to represent the landscape distribution of Tasmanian Aboriginal archaeological sites and assess the implications for patterns of past human activity. Location: Tasmania, Australia Methods: We developed a RandomForest 'habitat suitability' model of site records in the Tasmanian Aboriginal Heritage Register. We applied a best-effort bias correction, considered 31 predictor variables relating to climate, topography and resource proximity, and used a variable selection procedure to optimise the final model. Model uncertainty was assessed via bootstrapping and we ran an analogous MAXENT model as a cross-validation exercise. Results: The results from the RandomForest and MAXENT models are highly congruent. The strongest environmental predictors of site occurrence include distance to coast, elevation, soil clay content, topographic roughness and distance to inland water. The highest habitat suitability scores are distributed across a wide range of environments in central, northern and eastern Tasmania, including coastal areas, inland water body margins, and forests and savannas in the drier parts of Tasmania. With the exception of coastal areas much of western Tasmania has low habitat suitability scores, consistent with theories of low-density Holocene Tasmanian Aboriginal settlement in this region. Main conclusions: Our modelling suggests Tasmanian Aboriginal people occupied a heterogeneity of habitats but targeted coastal areas around the whole island, and drier, less steep, and/or open forest and savanna environments in the central lowlands. The western interior was identified as being rarely used by Aboriginal people in the Holocene, with the exception of isolated pockets of habitat; yet whether this is a true reflection of Aboriginal resource use demands increased archaeological surveys, particularly in the Tasmanian Wilderness World Heritage Area.
Data from: Mapping Tasmania's cultural landscapes: using habitat suitability modelling of archaeological sites as a landscape history tool
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Exploring the ontological links between Human Ecodynamics and field Archaeology through the integration of archaeological reports into DataARC's landscape ontology (MPhil by research thesis)
<p>The Zip file contains another 8 different folders. In each one, you will find the images and charts from Skútustaðir’s Archaeological Reports (permalink to the reports: https://www.nabohome.org/cgi-bin/explore.pl?seq=3). Each folder corresponds to one report. File’s names are abbreviated. Please, see the attached metadata for a full understanding of the abbreviated names. These images and charts were produced as part of the creation of a dataset for my MPhil thesis.</p> <p>Project_files_metadata provides all the information necessary for understanding the Zip file (and its files) and the CSV.</p> <p>The CSV file contains the dataset created and used for my MPhil thesis.</p> <p>The project was carried out within the DataARC Project as an MPhil thesis. The thesis explores the creation of (archaeo-historical) knowledge using data within a general framework of Big Data. Human Ecodynamics is the <em>paradigm </em>which guides the DataARC Project. My project explores how to link grey data from archaeological reports into a general computational ontology developed for representing Human Ecodynamics by making use of multiple datasets.</p>
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OpenNeuro
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