Our Checkered Past

IF 1.9 2区 历史学 0 ARCHAEOLOGY
Phillip O. Leckman, Michael Heilen
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引用次数: 0

Abstract

ABSTRACT Despite advocacy of landscape approaches in cultural resource management (CRM) and critiques of the site concept, CRM data collection methods in the western United States continue to focus on individual archaeological sites as units of observation, analysis, and management. The transect-recording unit (TRU) method strikes a balance between conventional site-based recording methods and site-less survey approaches by dividing survey space into a grid of uniformly sized cells for recording all cultural manifestations observed across a survey area. TRU survey generates site boundaries required by CRM regulations while retaining a fine-grained spatial framework for landscape-level research and management. This article discusses the technical requirements of the TRU system and its potential for improving landscape-level research and management. Advances in digital recording technologies and analysis techniques render the method efficient and effective in identifying cultural resource distributions and characteristics otherwise obscured by conventional approaches. The research and management potential of the TRU system is illustrated through identification and interpretation of precontact foot trails in New Mexico's Tularosa Basin. These trails are essentially invisible during pedestrian survey but are readily identifiable as linear patterns using aggregated landscape-scale TRU survey data from multiple survey projects, providing novel insight into precontact routes of movement and exchange.
我们曲折的过去
摘要尽管倡导文化资源管理中的景观方法,并对遗址概念提出批评,但美国西部的文化资源管理数据收集方法仍将重点放在单个考古遗址上,将其作为观测、分析和管理的单位。样带记录单元(TRU)方法通过将调查空间划分为大小均匀的细胞网格,用于记录在调查区域内观察到的所有文化表现,在传统的基于站点的记录方法和无站点的调查方法之间取得了平衡。TRU调查生成CRM法规要求的场地边界,同时保留用于景观级别研究和管理的细粒度空间框架。本文讨论了TRU系统的技术要求及其在提高景观水平研究和管理方面的潜力。数字记录技术和分析技术的进步使该方法在识别传统方法所掩盖的文化资源分布和特征方面变得高效和有效。通过对新墨西哥州图拉罗萨盆地接触前足迹的识别和解释,说明了TRU系统的研究和管理潜力。这些步道在行人调查过程中基本上是看不见的,但使用来自多个调查项目的景观规模TRU调查数据,可以很容易地识别为线性模式,为接触前的移动和交流路线提供了新的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.70
自引率
21.40%
发文量
39
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