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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), and thermal imagery in order to better understand the optimal contexts and environmental conditions for various sensors. We present new methods to remove noise from imagery and to combine multiple raster datasets in order to improve archaeological feature visibility. Analysis compares results of aerial imaging with ground-penetrating radar and magnetic gradiometry surveys, illustrating the complementary nature of these distinct remote sensing methods. Results demonstrate the value of high-resolution thermal and NIR imagery, as well as of multi-temporal image analysis, for the detection of archaeological features on and below the ground surface, offering an improved set of methods for the integration of these emerging technologies into archaeological field investigations.
Hill et al. (Thu,) studied this question.