手法を比較

	Intrasite Spatial Analysis	Structure from Motion
分野	考古学	考古学
系統	Process / pipeline	Process / pipeline
提唱年	1976	2012
提唱者	Ian Hodder & Clive Orton; activity-area approaches elaborated by Robert Whallon and others	Computer-vision SfM adapted for archaeological recording (popularized with low-cost photogrammetry, c. 2010s)
種類	Within-site spatial pipeline for detecting artifact clusters and activity areas	Image-based 3D reconstruction pipeline for site and artifact recording
原典	Hodder, I., & Orton, C. (1976). Spatial Analysis in Archaeology. Cambridge University Press. ISBN: 9780521210805	Renfrew, C., & Bahn, P. (2016). Archaeology: Theories, Methods, and Practice (7th ed.). Thames & Hudson. ISBN: 9780500292105
別名	Within-Site Spatial Analysis, Activity-Area Analysis, Artifact Distribution Analysis, Intra-Site Spatial Patterning	SfM Photogrammetry, Structure-from-Motion Modeling, Image-Based 3D Recording, Multi-View Photogrammetry
関連	2	2
概要	Intrasite spatial analysis studies how artifacts and features are distributed within a single site or living floor in order to reconstruct how space was used. Where settlement-pattern analysis treats whole sites as points, intrasite analysis zooms in to the scatter of tools, debris, hearths, and structures across an excavated surface, asking whether particular artifact types cluster together, whether activities were spatially segregated, and where discrete activity areas lay. The toolkit ranges from density and kernel mapping through clustering methods such as k-means to dimensional analysis of variance, the grid-based technique designed to find the scale at which artifacts are patterned. Ian Hodder and Clive Orton's Spatial Analysis in Archaeology set out the statistical foundations, and Conolly and Lake show how GIS-based density and association methods extend them.	Structure from Motion (SfM) is a photogrammetric technique that reconstructs three-dimensional models of archaeological subjects from sets of ordinary overlapping photographs. Borrowed from computer vision, it works by automatically finding the same physical points in many images, solving simultaneously for where each photograph was taken and where those points lie in space, and then building a dense point cloud, a meshed surface, and a photo-textured model. Because it needs only a camera and overlapping coverage, SfM has made high-resolution 3D recording of excavation surfaces, standing structures, artifacts, and whole landscapes (often from drones) fast and affordable. Scaled and georeferenced with control points, the resulting models integrate with GIS for measurement, analysis, and archiving, making SfM a core tool of digital field recording as reflected in Renfrew and Bahn and in the GIS workflows described by Conolly and Lake.