Confidence maps: a tool to evaluate data's relevance in spatial analysis.

Inventory data used in archaeology are often incomplete and heterogeneous. In the framework of the ArchaeDyn program, a method has been proposed to evaluate heterogeneity in archaeological inventories. The purpose of this work is to create a validation tool to interpret the results. This tool is called a "confidence map" and is produced by combining representation and reliability maps. The first step consists in generating representation maps to describe the clustering of archaeological items. The second step is based on reliability maps. Data providers are asked to define and outline the level of reliability of their data. Finally, representation and reliability layers are combined using map algebra. The resulting maps allow for the comparison and analysis of data confidenc

Lidor. Acquisition, traitement et analyse d'images LiDAR pour la modélisation des paléo-reliefs de la plaine littorale du Languedoc oriental.

Rapport d'ATIP Jeune Chercheur (CNRS)Rapport final du programme ATIP LidOR. Acquisition et traitement de données Lidar acquises en décembre 2006 dans la plaine littorale de Mauguio. L'ensemble des données Lidar acquises a pu être traité pour produire un premier Modèle Numérique de Terrain puis de Surface à 50 cm de résolution qui ont permis une exploration visuelle des données. D'un point de vue thématique, le travail de l'équipe s'est concentré sur le traitement des données avec trois objectifs principaux : la détection des aménagements de la plaine (irrigation, drainage...) depuis l'Antiquité ; la mise en évidence du réseau hydrographique " naturel " avant le détournement artificiel des cours d'eau et l'assèchement des dépressions humides ; la détection des microreliefs résiduels

Confidence maps: a tool to evaluate archaeological data's relevance in spatial analysis

L'article est disponible en ligne sur Virtual Library Propylaeum : http://archiv.ub.uni-heidelberg.de/propylaeumdok/volltexte/2010/551/pdf/08_05_ostir_et_al_confidence.pdfInternational audienc

Visualization of lidar-derived relief models for detection of archaeological features

International audienceThis paper presents visualisation techniques of high-resolution digital elevation models (DEMs) for visual detection of archaeological features. The methods commonly used in archaeology are reviewed and improvements are suggested. One straightforward technique that has so far not been used in archaeologye the shift method e is presented. The main purpose of this article is to compare and evaluate different visualisation methods. Two conclusions have been reached. Where a single method must be chosen e for printing or producing digital images for non-professionals e the use of sky view factor or slope gradient is endorsed, both presented in greyscale. Otherwise interpreters should choose different techniques on different terrain types: shift on flat terrain, sky viewfactor on mixed terrain, slope gradient on sloped terrain and sky view factor (preferably as a composite image with slope gradient) on rugged terrain

La télédétection

Qu'est-ce que le télédétection ? Un peu de physique... Classification d'image Télédétection et topographie Une approche interdisciplinaire Bibliographie : Pour en savoir plus Etudes de ca

Training archaeologists in the use of lidar: the TRAIL experience

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Models and tools for territorial dynamic studies (chapter 1)

As part of the ArchaeDyn project, a workgroup was formed to coordinate the development, implementation and application of methods and tools for spatial analysis. The workgroup's activities were directed at various problems. The first was to construct a grid common to all the workgroups and to homogenize the study areas used by the different workgroups in their databases. The 'confidence maps' method was suggested for assessing the quality and quantity of information inventoried in the databases. Confidence maps are produced from representation and reliability maps by simple map algebra and they can be considered as 'masks' for interpreting spatial analysis results. Finally, the research team tested, developed and adapted various statistical and geostatistical methods for defining the spatial indicators of stability over time (sustainability / permanent rhythms, changes, mobility / trajectories). This Chapter presents several exploratory analyses made within this framework

Understanding past territorial dynamics through the integrated study of movement, pathways and transport networks

International audienceSettlement patterns and path networks represent different but connected perspectives on human-environment interaction through movement, manifested through the appropriation and organisation of landscape by societies. Settlement patterns and path networks evolve with unharmonized temporalities, but in constant interaction which render the territorial studies very challenging. Remote sensing, GIS and 3D modeling have greatly contributed to our knowledge and understanding of movement as encapsulated in routes, but the methods employed make it difficult to connect with theories of engagement through travel. Pragmatically, it is difficult to integrate LiDAR-detected traces of pathways, which conflate temporalities, with network analysis techniques and settlement pattern analysis which focus on changing patterns over time.This paper argues for an integrated approach. After a general review of the main methods developed to detect and model movement, pathways and networks of transportation, a conceptual framework will be presented that will enable us to make the connection between the material evidence of routes and various computer-based models of movement, and thus better understand territorial dynamics. This conceptual framework investigates connectivity at various spatiotemporal scales. Most importantly, it creates an explicit framework for research using both detection and modelling-led approaches. A comparison of regional case studies from the literature will be presented to discuss the balance between general models and specific contextualisation

Developing FAIR Ontological Pathways: Linking Evidence of Movement in Lidar to Models of Human Behaviour

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