Multispectral remote sensing for post‐dictive analysis of archaeological remains. A case study from Bronte (Sicily)

A post-dictive analysis using WorldView-2 (WV-2) multispectral imagery demonstrates the potential of remote sensing for detecting archaeological features in the volcanic landscape of Bronte, Sicily. The study, conducted within UNESCO's Etna Park, highlights the effectiveness of specific vegetation indices—particularly the Normalized Difference Vegetation Index (NDVI) and Simple Ratio Index (SRI)—in identifying subsurface structures despite challenges posed by geology and spontaneous vegetation. By analyzing pre-excavation imagery from 2015, researchers identified the Near-Infrared 1 (NIR_1) and Red Edge bands as most useful for archaeological investigations. The study emphasizes the feasibility of low-cost, open-source software (FOSS) approaches in landscape archaeology, offering a scalable method for future research.

Gennaro, A., Candiano, A., Fargione, G., Mangiameli, M., & Mussumeci, G. (2019). Multispectral remote sensing for post‐dictive analysis of archaeological remains. A case study from Bronte (Sicily). Archaeological Prospection, 26(4), 299–311. Portico. https://doi.org/10.1002/arp.1745