Deploying multispectral remote sensing for multitemporal analysis of archaeological crop stress at Ravenshall, Fife
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Whilst intensification of farming practices poses a threat to the preservation of archaeological traces, developments in monitoring vegetation health remotely may improve our ability to detect historic features across landscapes. Discrete areas of contrasting vegetation reflectance known as crop marks can be studied as proxies for buried archaeology that has affected growing plants. This study aims to assess the effectiveness of the Parrot Sequoia multispectral sensor, recently developed for agricultural applications, for detection of crop marks. In a pilot test of the archaeological potential for this sensor, a series of observations have been taken from an unmanned aerial vehicle (UAV) at Ravenshall field, Fife between April and July 2017. The resulting reflectance maps have been compared to red, green and blue (RGB) photography taken with a Nikon D800E digital camera from seven light aircraft surveys across the season. The contrast between vegetation samples that lie above identified archaeology and the surrounding field was assessed by looking at the separability in regional histogram values across different image band combinations. Separable values indicative of crop marks were found in both the multispectral and RGB results from June 2017 onwards. A number of vegetation index (VI) maps, particularly the Simple Ratio (SR) and Normalised Difference Vegetation Index (NDVI) were found to be effective for distinguishing crop marks in the multispectral results, with archaeological samples found to be changing at different rates from the surrounding field. The Sequoia offered improved spatial and spectral resolution over the RGB photography, showing potential for subtle crop mark detection across compact study areas.