Integrated use of GIS and remote sensing techniques for landscape-scale archaeological analysis: the case study of Metaponto, Basilicata, Italy

References

• Abate, N., A. Elfadaly, N. Masini, and R. Lasaponara. 2020. Multitemporal 2016–2018 sentinel-2 data enhancement for landscape archaeology: The case study of the Foggia province, southern Italy. Remote Sensing 12: 1309. doi:10.3390/rs12081309.
   Web of Science ®Google Scholar
• Abate, N., A. Frisetti, F. Marazzi, N. Masini, and R. Lasaponara. 2021. Multitemporal–multispectral UAS surveys for archaeological research: The case study of San Vincenzo Al Volturno (Molise, Italy). Remote Sensing 13: 2719. doi:10.3390/rs13142719.
   Web of Science ®Google Scholar
• Abate, N., and R. Lasaponara. 2019. Preventive archaeology based on open remote sensing data and tools: The cases of Sant’Arsenio (SA) and foggia (FG), Italy. Sustainability 11: 4145. doi:10.3390/su11154145.
   Web of Science ®Google Scholar
• Abate, N., D. Roubis, V. Vitale, M. Sileo, F. Sogliani, N. Masini, and R. Lasaponara. 2022. Integrated use of multi-temporal multi-sensor and multiscale Remote Sensing data for the understanding of archaeological contexts: The case study of Metaponto, Basilicata. Journal of Physics: Conference Series 2204: 012020. doi:10.1088/1742-6596/2204/1/012020.
   Google Scholar
• Adamesteanu, D., D. Mertens, and F. D’Andria. 1975. Metaponto I. Roma, Italy: Accademia Nazionale dei Lincei.
   Google Scholar
• Agapiou, A., D. Hadjimitsis, and D. Alexakis. 2012. Evaluation of broadband and narrowband vegetation indices for the identification of archaeological crop marks. Remote Sensing 4: 3892–3919. doi:10.3390/rs4123892.
   Web of Science ®Google Scholar
• Agapiou, A., D.G. Hadjimitsis, A. Sarris, A. Georgopoulos, and D.D. Alexakis. 2013. Optimum temporal and spectral window for monitoring crop marks over archaeological remains in the Mediterranean region. Journal of Archaeological Science 40: 1479–1492. doi:10.1016/j.jas.2012.10.036.
   Web of Science ®Google Scholar
• Agapiou, A., D.G. Hadjimitsis, K. Themistocleous, G. Papadavid, and L. Toulios. 2010. Detection of archaeological crop marks in Cyprus using vegetation indices from Landsat TM/ETM+ satellite images and field spectroscopy measurements. In Presented at the remote sensing, Toulouse, France, eds. U. Michel, and D.L. Civco, 78310V. doi:10.1117/12.864935
   Google Scholar
• Agapiou, A., V. Lysandrou, R. Lasaponara, N. Masini, and G.G. Hadjimitsis. 2016. Study of the variations of archaeological marks at neolithic site of lucera, Italy using high-resolution multispectral datasets. Remote Sensing 8: 723. doi:10.3390/rs8090723.
   Web of Science ®Google Scholar
• Aiazzi, B., L. Alparone, S. Baronti, A. Garzelli, and M. Selva. 2013. Spie proceedings. Proc SPIE 8892: 0889203. doi:10.1117/12.2030560.
   Google Scholar
• Alcaras, E., C. Parente, and A. Vallario. 2021. Automation of Pan-sharpening methods for pléiades images using GIS basic functions. Remote Sensing 13: 1550. doi:10.3390/rs13081550.
   Web of Science ®Google Scholar
• Amani, M., A. Ghorbanian, S.A. Ahmadi, M. Kakooei, A. Moghimi, S.M. Mirmazloumi, S.H.A. Moghaddam, et al. 2020. Google earth engine cloud computing platform for remote sensing Big data applications: A comprehensive review. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 13: 5326–5350. doi:10.1109/JSTARS.2020.3021052.
   Web of Science ®Google Scholar
• Barrile, V., E. Bernardo, A. Fotia, and G. Bilotta. 2022. Integration of laser scanner, ground-penetrating radar, 3D models and mixed reality for artistic, archaeological and cultural heritage dissemination. Heritage 5: 1529–1550. doi:10.3390/heritage5030080.
   Google Scholar
• Beck, A. 2007. Archaeological site detection: The importance of contrast. Presented at the Proceedings of the 2007 Annual Conference of the Remote Sensing and Photogrammetry Society, Newcastle Upon Tyne, UK, 11–14 September 2007, ISPRS, pp. 307–312.
   Google Scholar
• Bertelli, G. 2005. L’insediamento medievale di Torre di Mare (Metaponto) e i suoi rapporti con il territorio. Primi dati. In Presented at the I congresso nazionale di archeologia medievale: auditorium del centro studi della cassa di risparmio di Pisa (ex benedettine), Pisa, 29–31 May 1997, ed. S. Gelichi, 200–205.
   Google Scholar
• Bertelli, G., and D. Roubis. 2002. Torre di Mare 1. Ricerche Archeologiche nell’Insediamento Medievale di Metaponto (1995–1999). Bari, Italy: Adda.
   Google Scholar
• Calleja, J.F., O. Requejo Pagés, N. Díaz-Álvarez, J. Peón, N. Gutiérrez, E. Martín-Hernández, A. Cebada Relea, D. Rubio Melendi, and P. Fernández Álvarez. 2018. Detection of buried archaeological remains with the combined use of satellite multispectral data and UAV data. International Journal of Applied Earth Observation and Geoinformation 73: 555–573. doi:10.1016/j.jag.2018.07.023.
   Web of Science ®Google Scholar
• Campana, S., M. Dabas, L. Marasco, S. Piro, and D. Zamuner. 2009. Integration of remote sensing, geophysical surveys and archaeological excavation for the study of a medieval mound (Tuscany, Italy) Archaeol. Prospect 16: 167–176.
   Google Scholar
• Campana, S., and M. Forte. eds. 2006. From space to place: 2nd International Conference on Remote Sensing in Archaeology: proceedings of the 2nd international workshop, CNR, Rome, Italy, December 4-7, 2006, BAR international series. Presented at the international conference on remote sensing in archaeology, Archeopress, Oxford. Consiglio nazionale delle ricerche (Italy)
   Google Scholar
• Campana, S., and R. Franchovich. 2003. Landscape archaeology in Tuscany: cultural resource management, remotely sensed techniques, GIS based data integration and interpretation. In Presented at the reconstruction of archaeological landscapes through digital technologies, Proceedings of the 1st Italy-United States Workshop, Boston, Massachusetts, USA (November 1–3 2001), eds. M. Forte, and P.R. Williams, 15–28. Oxford, UK: Oxford University Press.
   Google Scholar
• Capozzoli, L., G. Romano, M. Sileo, R. Lasaponara, J. Bastante, D. Sieczkowska, and N. Masini. 2022. New results from archaeogeophysical investigations in Machu Picchu. In Machu Picchu in context, eds. M. Ziółkowski, N. Masini, and J.M. Bastante, 265–300. Cham: Springer International Publishing. doi:10.1007/978-3-030-92766-0_7
   Google Scholar
• Cerra, D., A. Agapiou, R.M. Cavalli, and A. Sarris. 2018. An objective assessment of hyperspectral indicators for the detection of buried archaeological relics. Remote Sensing 10: 500. doi:10.3390/rs10040500.
   Web of Science ®Google Scholar
• Chuvieco, E., M.P. Martín, and A. Palacios. 2002. Assessment of different spectral indices in the red-near-infrared spectral domain for burned land discrimination. International Journal of Remote Sensing 23: 5103–5110. doi:10.1080/01431160210153129.
   Web of Science ®Google Scholar
• Corrado, G., G. Aiello, D. Barra, P. Di Leo, D. Gioia, M.A. Antonio, R. Parisi, and M. Schiattarella. 2022. Late Quaternary evolution of the Metaponto coastal plain, southern Italy, inferred from geomorphological and borehole data. Quaternary International, 638–639, 84–110. doi:10.1016/j.quaint.2022.01.008.
   Web of Science ®Google Scholar
• D’Andria, F. 1975. Metaponto romana, in: atti XV conv.M.grecia. Presented at the XV Conv.M.Grecia, Napoli, 539–544.
   Google Scholar
• Diara, F., and F. Rinaudo. 2018. Open Source HBIM for Cultural Heritage: A Project Proposal XLII-2, 303–309. doi:10.5194/isprs-archives-XLII-2-303-2018
   Google Scholar
• Elfadaly, A., M. Abate, N. Masini, and R. Lasaponara. 2020. Sar sentinel 1 imaging and detection of palaeo-landscape features in the Mediterranean area. Remote Sensing 12: 2611. doi:10.3390/rs12162611.
   Web of Science ®Google Scholar
• Elfadaly, A., K. Abutaleb, D.M. Naguib, and R. Lasaponara. 2022. Detecting the environmental risk on the archaeological sites using satellite imagery in Basilicata Region, Italy. The Egyptian Journal of Remote Sensing and Space Science 25: 181–193. doi:10.1016/j.ejrs.2022.01.007.
   Web of Science ®Google Scholar
• Estornell, J., J.M. Martí-Gavliá, M.T. Sebastiá, and J. Mengual. 2013. Principal component analysis applied to remote sensing. Modelling in Science Education and Learning 6: 83. doi:10.4995/msel.2013.1905.
   Google Scholar
• Fattore, C., N. Abate, F. Faridani, N. Masini, and R. Lasaponara. 2021. Google earth engine as multi-sensor open-source tool for supporting the preservation of archaeological areas: The case study of flood and fire mapping in metaponto, Italy. Sensors 21: 1791. doi:10.3390/s21051791.
   PubMed Web of Science ®Google Scholar
• Fedi, M., F. Cella, G. Florio, M. La Manna, and V. Paoletti. 2017. Geomagnetometry for archaeology. In Sensing the past, eds. N. Masini, and F. Soldovieri, 203–230. Berlin, Heidelberg: Springer.
   Google Scholar
• Forte, M., and S.R.L. Campana2016. Digital methods and remote sensing in archaeology: Archaeology in the Age of sensing, quantitative methods in the humanities and social sciences. Springer International Publishing. doi:10.1007/978-3-319-40658-9
   Google Scholar
• Giannotta, M.T. 1980. Metaponto ellenistico-romana. Galatina.: Congedo Editore.
   Google Scholar
• Giardino, L. 1982. Metaponto tardo-imperiale e Turiostu: Proposta di identificazione in margine ad un miliarium di Giuliano l’Apostata. Studi Antich 3: 155–173.
   Google Scholar
• Giardino, L. 1991. Grumentum e Metaponto. Due esempi di passaggio dal tardoantico all'alto medioevo in Basilicata. Mélanges de L'Ecole Française de Rome. Moyen-Age, Temps Modernes 103: 827–858. doi:10.3406/mefr.1991.3202.
   Google Scholar
• Gioia, D., M. Bavusi, et al. 2017. A geoarchaeological study of the Metaponto coastal belt, Southern Italy, based on geomorphological mapping and GIS-supported classification of landforms. Geogr. Fis. E Din. Quat, 137–148. doi:10.4461/GFDQ.2016.39.13.
   Web of Science ®Google Scholar
• Gioia, D., M. Bavusi, P. Di Leo, T. Giammatteo, and M. Schiattarella. 2020. Geoarchaeology and geomorphology of the Metaponto area, Ionian coastal belt, Italy. Journal of Maps 16: 117–125. doi:10.1080/17445647.2019.1701575.
   Web of Science ®Google Scholar
• Holata, L., J. Plzák, R. Světlík, and J. Fonte. 2018. Integration of Low-resolution ALS and ground-based SfM photogrammetry data. A cost-effective approach providing an ‘enhanced 3D model’ of the hound Tor archaeological landscapes (Dartmoor, South-West England). Remote Sensing 10: 1357. doi:10.3390/rs10091357.
   Web of Science ®Google Scholar
• Jensen, J.R. 2016. Introductory digital image processing: A remote sensing perspective, Pearson series in geographic information science. Glenview, IL: Pearson Education, Inc.
   Google Scholar
• Khalaf, N., and T. Insoll. 2019. Monitoring Islamic archaeological landscapes in Ethiopia using open source satellite imagery. Journal of Field Archaeology 44: 401–419. doi:10.1080/00934690.2019.1629256.
   Web of Science ®Google Scholar
• Kumar, L., and O. Mutanga. 2018. Google earth engine applications since inception: usage, trends, and potential. Remote Sensing 10: 1509. doi:10.3390/rs10101509.
   Web of Science ®Google Scholar
• Lacava, M. 1891. Topografia e Storia di Metaponto. Napoli, Italy: Morano.
   Google Scholar
• Larson, D., C. Lipo, and E. Ambos. 2003. Application of advanced geophysical methods and engineering principles in an emerging scientific archaeology: Environmental Geoscience. Undefined.
   Google Scholar
• Lasaponara, R., N. Abate, and N. Masini. 2022. On the Use of google earth engine and sentinel data to detect “lost” sections of ancient roads. The case of Via Appia. IEEE Geoscience and Remote Sensing Letters, doi:10.1109/LGRS.2021.3054168.
   Web of Science ®Google Scholar
• Lasaponara, R., and N. Masini. 2006. Identification of archaeological buried remains based on the normalized difference vegetation index (NDVI) from Quickbird satellite data. IEEE Geoscience and Remote Sensing Letters 3: 325–328. doi:10.1109/LGRS.2006.871747.
   Web of Science ®Google Scholar
• Lasaponara, R., and N. Masini. 2006. On the potential of QuickBird data for archaeological prospection. International Journal of Remote Sensing 27: 3607–3614. doi:10.1080/01431160500333983.
   Web of Science ®Google Scholar
• Lasaponara, R., and N. Masini. 2007. Detection of archaeological crop marks by using satellite QuickBird multispectral imagery. Journal of Archaeological Science 34: 214–221. doi:10.1016/j.jas.2006.04.014.
   Web of Science ®Google Scholar
• Liss, B., M.D. Howland, and T.E. Levy. 2017. Testing Google Earth Engine for the automatic identification and vectorization of archaeological features: A case study from Faynan, Jordan. Journal of Archaeological Science: Reports 15: 299–304. doi:10.1016/j.jasrep.2017.08.013.
   Google Scholar
• Loncan, L., L.B. de Almeida, J.M. Bioucas-Dias, X. Briottet, J. Chanussot, N. Dobigeon, S. Fabre, W. Liao, et al. 2015. Hyperspectral pansharpening: A review. IEEE Geoscience and Remote Sensing Magazine 3: 27–46. doi:10.1109/MGRS.2015.2440094.
   Web of Science ®Google Scholar
• Luo, L., X. Wang, H. Guo, R. Lasaponara, X. Zong, N. Masini, G. Wang, et al. 2019. Airborne and spaceborne remote sensing for archaeological and cultural heritage applications: A review of the century (1907–2017). Remote Sensing of Environment 232: 111280. doi:10.1016/j.rse.2019.111280.
   Web of Science ®Google Scholar
• Masini, N., and R. Lasaponara. 2006. Satellite-based recognition of landscape archaeological features related to ancient human transformation. Journal of Geophysics and Engineering 3: 230–235. doi:10.1088/1742-2132/3/3/004.
   Web of Science ®Google Scholar
• Masini, N., and F. Soldovieri. 2017. Sensing the Past: From artifact to historical site, Geotechnologies and the Environment. Cham: Springer International Publishing. doi:10.1007/978-3-319-50518-3
   Google Scholar
• Mutanga, O., and L. Kumar. 2019. Google earth engine applications. Remote Sensing 11: 591. doi:10.3390/rs11050591.
   Web of Science ®Google Scholar
• Orengo, H.A., F.C. Conesa, A. Garcia-Molsosa, A. Lobo, A.S. Green, M. Madella, and C.A. Petrie. 2020. Automated detection of archaeological mounds using machine-learning classification of multisensor and multitemporal satellite data. Proceedings of the National Academy of Sciences 117: 18240–18250. doi:10.1073/pnas.2005583117.
   PubMed Web of Science ®Google Scholar
• Parcak, S.H. 2009. Satellite remote sensing for archaeology. London, New York: Routledge.
   Google Scholar
• Parcak, S.H. 2014. GIS, remote sensing, and landscape archaeology. Oxford University Press. doi:10.1093/oxfordhb/9780199935413.013.11
   Google Scholar
• Persico, R. 2014. Introduction to ground penetrating radar: inverse scattering and data processing. Hoboken, NJ: IEEE Press.
   Google Scholar
• Roubis, D. 2012. Ricognizioni infrasito a Santa Maria d’Anglona (Tursi –Mt). In ΑΜΦΙ ΣΙΡΙΟΣ ΡΟΑΣ. nuove ricerche Su eraclea e La siritide, eds. M. Osanna, and G. Zuchtriegel. osanna edizioni, 291–304. Venosa, Italy.
   Google Scholar
• Roubis, D. 2015. Archeologia dei paesaggi a Pandosia (S.M. d’Anglona). Siris 15: 163–176.
   Google Scholar
• Rouse, J., R.H. Haas, D. Deering, J.A. Schell, and J. Harlan. 1973. Monitoring the Vernal Advancement and Retrogradation (Green Wave Effect) of Natural Vegetation. [Great Plains Corridor]. undefined.
   Google Scholar
• Rowlands, A., and A. Sarris. 2007. Detection of exposed and subsurface archaeological remains using multi-sensor remote sensing. Journal of Archaeological Science 34: 795–803. doi:10.1016/j.jas.2006.06.018.
   Web of Science ®Google Scholar
• Stott, D., D. Boyd, A. Beck, and A. Cohn. 2015. Airborne LiDAR for the detection of archaeological vegetation marks using biomass as a proxy. Remote Sensing 7: 1594–1618. doi:10.3390/rs70201594.
   Web of Science ®Google Scholar
• Štular, B., S. Eichert, and E. Lozić. 2021. Airborne LiDAR point cloud processing for archaeology. pipeline and QGIS toolbox. Remote Sensing 13: 3225. doi:10.3390/rs13163225.
   Web of Science ®Google Scholar
• Tucker, C.J. 1979. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment 8: 127–150. doi:10.1016/0034-4257(79)90013-0.
   Web of Science ®Google Scholar
• White, D.C., M. Williams, and S.L. Barr. 2008. Detecting Sub-surface soil disturbance using hyperspectral first derivative band ratios of associated vegetation stress. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 37: 243–248.
   Google Scholar