9,121 research outputs found

    Fast approximation of visibility dominance using topographic features as targets and the associated uncertainty

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    An approach to reduce visibility index computation time andmeasure the associated uncertainty in terrain visibility analysesis presented. It is demonstrated that the visibility indexcomputation time in mountainous terrain can be reduced substantially,without any significant information loss, if the lineof sight from each observer on the terrain is drawn only to thefundamental topographic features, i.e., peaks, pits, passes,ridges, and channels. However, the selected sampling of targetsresults in an underestimation of the visibility index ofeach observer. Two simple methods based on iterative comparisonsbetween the real visibility indices and the estimatedvisibility indices have been proposed for a preliminary assessmentof this uncertainty. The method has been demonstratedfor gridded digital elevation models

    Optimising visibility analyses using topographic features on the terrain

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    Exploring multiple viewshed analysis using terrain features and optimisation techniques

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    The calculation of viewsheds is a routine operation in geographic information systems and is used in a wide range of applications. Many of these involve the siting of features, such as radio masts, which are part of a network and yet the selection of sites is normally done separately for each feature. The selection of a series of locations which collectively maximise the visual coverage of an area is a combinatorial problem and as such cannot be directly solved except for trivial cases. In this paper, two strategies for tackling this problem are explored. The first is to restrict the search to key topographic points in the landscape such as peaks, pits and passes. The second is to use heuristics which have been applied to other maximal coverage spatial problems such as location-allocation. The results show that the use of these two strategies results in a reduction of the computing time necessary by two orders of magnitude, but at the cost of a loss of 10% in the area viewed. Three different heuristics were used, of which Simulated Annealing produced the best results. However the improvement over a much simpler fast-descent swap heuristic was very slight, but at the cost of greatly increased running times. © 2004 Elsevier Ltd. All rights reserved

    Using airborne LiDAR Survey to explore historic-era archaeological landscapes of Montserrat in the eastern Caribbean

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    This article describes what appears to be the first archaeological application of airborne LiDAR survey to historic-era landscapes in the Caribbean archipelago, on the island of Montserrat. LiDAR is proving invaluable in extending the reach of traditional pedestrian survey into less favorable areas, such as those covered by dense neotropical forest and by ashfall from the past two decades of active eruptions by the Soufrière Hills volcano, and to sites in localities that are inaccessible on account of volcanic dangers. Emphasis is placed on two aspects of the research: first, the importance of ongoing, real-time interaction between the LiDAR analyst and the archaeological team in the field; and second, the advantages of exploiting the full potential of the three-dimensional LiDAR point cloud data for purposes of the visualization of archaeological sites and features

    Dynamic landscapes and human dispersal patterns : tectonics, coastlines, and the reconstruction of human habitats

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    Studies of the impact of physical environment on human evolution usually focus on climate as the main external forcing agent of evolutionary and cultural change. In this paper we focus on changes in the physical character of the landscape driven by geophysical processes as an equally potent factor. Most of the landscapes where finds of early human fossils and artefacts are concentrated are ones that have been subjected to high levels of geological instability, either because of especially active tectonic processes associated with faulting and volcanic activity or because of proximity to coastlines subject to dramatic changes of geographical position and physical character by changes of relative sea level. These processes can have both beneficial effects, creating ecologically attractive conditions for human settlement, and deleterious or disruptive ones, creating barriers to movement, disruption of ecological conditions, or hazards to survival. Both positive and negative factors can have powerful selective effects on human behaviour and patterns of settlement and dispersal. We consider both these aspects of the interaction, develop a framework for the reconstruction and comparison of landscapes and landscape change at a variety of scales, and illustrate this with selected examples drawn from Africa and Arabia

    The urban heritage characterization using 3D geographic information systems. The system of medium-sized cities in Andalusia

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    The primary objective of this paper is to approach the use of the 3D Geographic Information Systems (3D GIS), as an instrumental tool that allows us to deal efficiently with the extensive amount of information that characterises a large part of the research carried out in the field of Urbanism and Regional Planning. Specifically, the study focuses on medium-sized cities in Andalusia, the most populous and the second largest region in Spain. The Andalusian urban system is substantially characterised by the historical importance of this type of cities within its territorial organisation, which dates back to more than two thousand years, and whose potential as sustainable and balanced stands out. In particular, it is intended to address features related to urban characterisation as medium-sized cities that have been declared as heritage sites, as well as, the integration of the cultural heritage into urban development planning as an active strategy by the cultural administration of the regional and local governments. In detail, this paper will analyse data relating to the development experienced, their characterisation through urban indicators or the evolution and traceability of their protection. In this sense, the use of 3D GIS will not only allow the efficient recording and the graphical representation of a significant amount of data resulting from the quantitative and qualitative analysis carried out but also model them using the third dimension to facilitate a cross analysis among the cities under study. Definitely, the aim is to demonstrate the suitability use of this technology in this type of scientific research.Ministry of Economy and Competitiveness of the Government of Spain HAR2016-79788-

    Surfaces from the visual past : recovering high-resolution terrain data from historic aerial imagery for multitemporal landscape analysis

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    Historic aerial images are invaluable sources of aid to archaeological research. Often collected with large-format photogrammetric quality cameras, these images are potential archives of multidimensional data that can be used to recover information about historic landscapes that have been lost to modern development. However, a lack of camera information for many historic images coupled with physical degradation of their media has often made it difficult to compute geometrically rigorous 3D content from such imagery. While advances in photogrammetry and computer vision over the last two decades have made possible the extraction of accurate and detailed 3D topographical data from high-quality digital images emanating from uncalibrated or unknown cameras, the target source material for these algorithms is normally digital content and thus not negatively affected by the passage of time. In this paper, we present refinements to a computer vision-based workflow for the extraction of 3D data from historic aerial imagery, using readily available software, specific image preprocessing techniques and in-field measurement observations to mitigate some shortcomings of archival imagery and improve extraction of historical digital elevation models (hDEMs) for use in landscape archaeological research. We apply the developed method to a series of historic image sets and modern topographic data covering a period of over 70 years in western Sicily (Italy) and evaluate the outcome. The resulting series of hDEMs form a temporal data stack which is compared with modern high-resolution terrain data using a geomorphic change detection approach, providing a quantification of landscape change through time in extent and depth, and the impact of this change on archaeological resources

    A high-precision liDAR-based method for surveying and classifying coastal notches

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    Formation of notches is an important process in the erosion of seaside cliffs. Monitoring of coastal notch erosion rate and processes has become a prime research focus for many coastal geomorphologists. Observation of notch erosion rate considers a number of characteristics, including cliff collapse risk, distinction of historical sea levels, and recognition of ongoing erosional mechanisms. This study presents new approaches for surveying and classifying marine notches based on a high-precision light detection and ranging (LiDAR)-based experiment performed on a small region of a coastal cliff in southern Portugal. A terrestrial LiDAR scanner was used to measure geometrical parameters and surface roughness of selected notches, enabling their classification according to shape and origin. The implemented methodology proved to be a highly effective tool for providing an unbiased analysis of marine morphodynamic processes acting on the seaside cliffs. In the analyzed population of voids carved into Miocene calcarenites in a coastal cliff section, two types of notch morphology were distinguished, namely U-shaped and V-shaped. The method presented here provides valuable data for landscape evaluation, sea-level changes, and any other types of analyses that rely on the accurate interpretation of cliff morphological features.National Science Centre [UMO-2015/17/D/ST10/02191

    Summary of significant results of remote sensing studies in 1965

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    Technology survey on remote sensors mounted in earth orbiting spacecraf

    A predictive model for Palaeolithic sites: a case study of Monforte de Lemos basin, NW Iberian Peninsula

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    Although a theoretical model for the settlement patterns of Galician Palaeolithic has been proposed in the last decades, it has not been statistically tested. The present paper aims to check whether this previous theoretical model can be verified statistically. For this purpose, a methodology based on the creation of a predictive model has been used in which the main environmental variables were analysed and their suitability for predicting the location of Palaeolithic sites statistically verified. The predictive model shows that the most accurate variables are elevation, slope, cost to potential hydrology, the cost to wetland areas, and visual prominence. The results demonstrated that the theoretical model was fulfilled in some of the variables previously proposed. Thus, we have shown the usefulness of this approach to test hypotheses and the results obtained open new possibilities of analysis in the study of the Palaeolithic sites in NW IberiaThis study is part of the research projects Dinámicas poblacionales y tecnológicas durante el Pleistoceno final-Holoceno de las Sierras orientales del Noroeste ibérico (R&D Projects of the Ministry of Science, PID2019-107480 GB-I00), Ocupaciones humanas durante el Pleistoceno en la cuenca media del Miño (HUM2007-63662/HIST) and Poblamiento durante el Pleistoceno Medio/Holoceno en las comarcas orientales de Galicia (HAR2010-21786/HIST). M. Díaz-Rodríguez is part of the CLIOARCH project which has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement 817564); and the NeanderEDGE project which has received funding from the Independent Research Fund Denmark (case number 9062-00027B). We are very grateful to the two anonymous reviewers and the editor, whose comments have contributed significantly and helped improve the initial version of this paper. The analyses of this work have been carried out in the statistical environment R (R Core Team, 2021)S
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