2020
DOI: 10.3390/rs12040690
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Archaeological Remote Sensing Using Multi-Temporal, Drone-Acquired Thermal and Near Infrared (NIR) Imagery: A Case Study at the Enfield Shaker Village, New Hampshire

Abstract: While archaeologists have long understood that thermal and multi-spectral imagery can potentially reveal a wide range of ancient cultural landscape features, only recently have advances in drone and sensor technology enabled us to collect these data at sufficiently high spatial and temporal resolution for archaeological field settings. This paper presents results of a study at the Enfield Shaker Village, New Hampshire (USA), in which we collect a time-series of multi-spectral visible light, near-infrared (NIR)… Show more

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Cited by 60 publications
(53 citation statements)
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References 29 publications
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“…The suite of sensor technologies employed in this project offer a means to begin to achieve Kvamme's (2003) vision, because drone-based thermal and multispectral surveys not only can reveal a wide range of archaeological features that are otherwise invisible but can also be collected quickly, over large areas, at low cost. Our results from southeastern Kansas, as well as our previous work at sites in Illinois (McLeester et al 2018), New Mexico (Casana et al 2014), and New Hampshire (Casana et al 2017;Hill et al 2020), show the potential power of thermal and multispectral drone-based imaging to explore archaeological landscapes. The technology offers a rapid, low-cost method to prospect for unknown archaeological features over large areas, with the potential to reveal architecture, earthworks, or other landscape features that are not easily resolvable using other methods.…”
Section: Discussionsupporting
confidence: 75%
“…The suite of sensor technologies employed in this project offer a means to begin to achieve Kvamme's (2003) vision, because drone-based thermal and multispectral surveys not only can reveal a wide range of archaeological features that are otherwise invisible but can also be collected quickly, over large areas, at low cost. Our results from southeastern Kansas, as well as our previous work at sites in Illinois (McLeester et al 2018), New Mexico (Casana et al 2014), and New Hampshire (Casana et al 2017;Hill et al 2020), show the potential power of thermal and multispectral drone-based imaging to explore archaeological landscapes. The technology offers a rapid, low-cost method to prospect for unknown archaeological features over large areas, with the potential to reveal architecture, earthworks, or other landscape features that are not easily resolvable using other methods.…”
Section: Discussionsupporting
confidence: 75%
“…In order to identify Earth surface processes and associated landforms and, eventually, correlated archaeological and anthropic features, especially where political conflicts/warfare occur or the climate conditions prevent detailed fieldworks, the use of remote sensing techniques give a relevant support ( [23][24][25][26][27][28][29] and references therein). Moreover, wide extensions of the areas under investigation encourage the application of these techniques.…”
Section: Introductionmentioning
confidence: 99%
“…At the second stage, it was necessary to select samples with similar moduli of elasticity, without structural defects and with approximately the same porosity. This was done using laser ultrasonic structuroscopy [19]: 30 samples were examined with an UDL-2M automatic flaw detector. Figure 3 shows a schematic diagram of the detector.…”
Section: Measurement Of Local Elastic Wave Velocities In Samples By Lmentioning
confidence: 99%
“…These methods comprise destructive methods involving load testing under different loading conditions [11,12] and semi-destructive mechanical tests with simultaneous measurement of acoustic emission [13,14]. Non-destructive in situ and laboratory methods for inspecting natural materials are addressed in [15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32], including thermal control [16][17][18][19][20], multispectral optical remote sensing [21], ground penetrating radar [22,23], ultrasonic inspection [25,26], gamma-ray logging [27], terahertz spectroscopy [28], X-ray tomography [29,30], neutron radiography [31], and others [32].…”
Section: Introductionmentioning
confidence: 99%
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