A methodology for the self-training and self-assessing of new GPR practitioners: Measuring diagnostic proficiency illustrated by a case study of a historic African-American cemetery for unmarked graves

IF 2.1 3区 地球科学 0 ARCHAEOLOGY Archaeological Prospection Pub Date : 2023-01-13 DOI:10.1002/arp.1893
Jacob Michael Martin, Mark E. Everett
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引用次数: 3

Abstract

In ground penetrating radar (GPR) surveys of African-American cemeteries suspected to contain unmarked graves, determining the proficiency of a new GPR practitioner is vital and perhaps even more fundamental than that of the GPR hardware, deployment configuration and software. Proficiency may be defined as the practitioner's true-positive, true-negative, false-positive (i.e., false alarms) and false-negative (i.e., misses) percentages. We embarked on this research as a means to improve our own proficiency in unmarked grave detection and to develop an algorithm by which to improve the proficiency of any new GPR practitioner. After surveying the Salem Cemetery in Brazos County, TX, and the Old Danville-Shepherd Hill Cemetery in Montgomery County, TX, we first classified subsurface targets based on in-field, visual inspection of the real-time, onscreen, unprocessed (except for an automatic gain control) GPR B-scans. We then developed a proxy for ground-truthing that allowed us to calculate the proficiency of the in-field classifications. From this proxy, we established a quantitative prevalence threshold for identifying or rejecting a subsurface object as a target of interest. Its quantitative nature allowed us to quantitatively control and adjust that threshold, a threshold we set at 70% likely to be to a specific target of interest. We show that our classification accuracy increased from 66.2% at the Salem Cemetery to 75.0% at the Old Danville-Shepherd Hill Cemetery and, through use of diagnostic evaluations originally developed for medical imaging and herein applied to geophysics, showed that the accuracy improved due to increases in true-negative classifications, that is, in examining real-time, onscreen, mostly unprocessed GPR B-scans, discerning a potential target and correctly concluding it was not an unmarked grave. This research outlines the procedure we developed to measure the proficiency of a new GPR practitioner.

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新探地雷达从业人员自我训练和自我评估的方法:以一个历史上的非裔美国人墓地的无标记坟墓为例,说明了测量诊断能力的方法
在对非裔美国人墓地进行探地雷达(GPR)调查时,确定新探地雷达从业者的熟练程度至关重要,甚至可能比探地雷达硬件、部署配置和软件更重要。熟练度可以定义为从业者的真阳性、真阴性、假阳性(即虚报)和假阴性(即漏报)百分比。我们开始这项研究是为了提高我们自己在无标记坟墓探测方面的熟练程度,并开发一种算法,通过这种算法可以提高任何新的GPR从业者的熟练程度。在对德克萨斯州Brazos县的Salem公墓和Montgomery县的Old Danville - Shepherd Hill公墓进行调查后,我们首先对地下目标进行了分类,该分类基于现场、实时视觉检查、屏幕显示、未处理(自动增益控制除外)的GPR B扫描。然后,我们开发了一个地面真实的代理,使我们能够计算实地分类的熟练程度。从这个代理中,我们建立了一个定量的流行阈值,用于识别或拒绝地下物体作为感兴趣的目标。它的定量特性允许我们定量地控制和调整阈值,我们将阈值设置为70%的可能性,以达到特定的兴趣目标。我们表明,我们的分类准确率从塞勒姆公墓的66.2%提高到老丹维尔-谢菲尔德山公墓的75.0%,并且,通过使用最初为医学成像开发的诊断评估,并在此应用于地球物理学,表明准确性由于真阴性分类的增加而提高,即在检查实时,屏幕上,大部分未处理的GPR B扫描,识别潜在目标并正确地得出结论,它不是一个未标记的坟墓。本研究概述了我们开发的程序,以衡量新的探地雷达从业者的熟练程度。
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来源期刊
Archaeological Prospection
Archaeological Prospection 地学-地球科学综合
CiteScore
3.90
自引率
11.10%
发文量
31
审稿时长
>12 weeks
期刊介绍: The scope of the Journal will be international, covering urban, rural and marine environments and the full range of underlying geology. The Journal will contain articles relating to the use of a wide range of propecting techniques, including remote sensing (airborne and satellite), geophysical (e.g. resistivity, magnetometry) and geochemical (e.g. organic markers, soil phosphate). Reports and field evaluations of new techniques will be welcomed. Contributions will be encouraged on the application of relevant software, including G.I.S. analysis, to the data derived from prospection techniques and cartographic analysis of early maps. Reports on integrated site evaluations and follow-up site investigations will be particularly encouraged. The Journal will welcome contributions, in the form of short (field) reports, on the application of prospection techniques in support of comprehensive land-use studies. The Journal will, as appropriate, contain book reviews, conference and meeting reviews, and software evaluation. All papers will be subjected to peer review.
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