Google Earth Engine for archaeologists: An updated look at the progress and promise of remotely sensed big data
Open accessAbstract
A wealth of remotely sensed data has accumulated over the past several decades and now constitutes an analytical resource primed for archaeological applications. To date, remotely sensed big data (RSBD) analytics in archaeology have focused on filling spatial gaps in the distribution of sites and features, characterizing environmental landscapes, and monitoring cultural heritage sites. The scientific promise of these data to expand our understanding of past human-environment interactions has not been fully realized. Limitations of data access, sufficient analytical and computational resources, and methodological awareness and education on the appropriate use of RSBD have limited the adoption and widespread use of RSBD in archaeology, despite its ubiquity in the Earth sciences. Google Earth Engine (GEE) is a freely available planetary-scale cloud computing platform that addresses the perennial challenges of data access, analysis, and computing power that are particularly acute among archaeologists aiming to derive insights from RSBD. GEE lowers the barrier to entry for analyzing RSBD, expanding the potential for these data in the automated identification of archaeological features through deep learning; fieldwork planning and archaeological practice; modeling of past environments and environmental variability; and cultural heritage impact and risk assessments. In doing so, it also contributes to open science via increased access, transparency, and reproducibility.
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Αγαπίου, Ά., Vionis, A. K., & Papantoniou, G. (2021) · Land · doi:10.3390/land10121365 · Cited by 26 · see citing works
Drone-Mounted Lidar Survey of Maya Settlement and Landscape
Murtha, T. M., Broadbent, E. N., Golden, C. J., Scherer, A., Schroder, W. C., Wilkinson, B., & Zambrano, A. M. A. (2019) · Latin American Antiquity · doi:10.1017/laq.2019.51 · Cited by 25 · see citing works
Self-citationUAV LiDAR Survey for Archaeological Documentation in Chiapas, Mexico
Schroder, W. C., Murtha, T. M., Golden, C. J., Scherer, A., Broadbent, E. N., Zambrano, A. M. A., Herndon, K. E., & Griffin, R. (2021) · Remote Sensing · doi:10.3390/rs13234731 · Cited by 25 · see citing works
Self-citationValidating Prehistoric and Current Social Phenomena Upon the Landscape of the Peten, Guatemala
Sever, T. L. (1997) · NASA Technical Reports Server (NASA) · Cited by 24 · see citing works
Satellite Remote Sensing for the Analysis of the Micia and Germisara Archaeological Sites
Negula, I. D., Moise, C., Lazăr, A. M., Rișcuța, N. C., Cristescu, C., Dedulescu, A. L., Mihalache, C. E., & Badea, A. (2020) · Remote Sensing · doi:10.3390/rs12122003 · Cited by 23 · see citing works
Howey, M. C. L., Sullivan, F. B., Burg, M. B., & Palace, M. (2020) · Journal of Field Archaeology · doi:10.1080/00934690.2020.1713435 · Cited by 21 · see citing works
Hogenson, K., Arko, S. A., Buechler, B., Hogenson, R., Herrmann, J., & Geiger, A. (2016) · AGU Fall Meeting Abstracts · Cited by 21 · see citing works
Elfadaly, A., Abutaleb, K., Naguib, D. M., & Lasaponara, R. (2022) · The Egyptian Journal of Remote Sensing and Space Science · doi:10.1016/j.ejrs.2022.01.007 · Cited by 20 · see citing works
TerraWatchers, Crowdsourcing, and At-Risk World Heritage in the Middle East
Savage, S. H., Johnson, A., & Levy, T. E. (2017) · Quantitative methods in the humanities and social sciences · doi:10.1007/978-3-319-65370-9_4 · Cited by 19 · see citing works
Davis, D. S. (2021) · Journal of Computer Applications in Archaeology · doi:10.5334/jcaa.72 · Cited by 19 · see citing works
Sever, T. L. (2000) · Springer eBooks · doi:10.1007/978-1-4615-4145-5_2 · Cited by 18 · see citing works
Mapping the Past: O. G. S. Crawford and the Development of Landscape Studies
Bowden, M. (2001) · Landscapes · doi:10.1179/lan.2001.2.2.29 · Cited by 18 · see citing works
Observing Geohazards from Space
Cigna, F. (2018) · Geosciences · doi:10.3390/geosciences8020059 · Cited by 18 · see citing works
Changes in Mesopotamian Wetlands: Investigations Using Diverse Remote Sensing Datasets
Al-Nasrawi, A. K. M., Fuentes, I., & Al-Shammari, D. (2021) · Wetlands · doi:10.1007/s13157-021-01490-x · Cited by 17 · see citing works
Science and Technology in Historic Preservation
Williamson, R. A., & Nickens, P. (2000) · Springer eBooks · doi:10.1007/978-1-4615-4145-5 · Cited by 16 · see citing works
Modelling the ancient maize agriculture potential of landforms in Tikal National Park, Guatemala
Balzotti, C. S., Webster, D. L., Murtha, T. M., Petersen, S. L., Burnett, R. L., & Terry, R. E. (2013) · International Journal of Remote Sensing · doi:10.1080/01431161.2013.798876 · Cited by 16 · see citing works
Self-citationLocating Amazonian Dark Earths (ADE) using vegetation vigour as a surrogate for soil type
Thayn, J. B., Price, K. P., & Woods, W. I. (2011) · International Journal of Remote Sensing · doi:10.1080/01431161.2010.512941 · Cited by 16 · see citing works
Cobb, P. J., Sigmier, J. H., Creamer, P. M., & French, E. R. (2019) · Open Archaeology · doi:10.1515/opar-2019-0010 · Cited by 15 · see citing works
The spatial pattern of climate change during the spread of farming into the Aegean
Gauthier, N. (2016) · Journal of Archaeological Science · doi:10.1016/j.jas.2016.09.004 · Cited by 14 · see citing works
El-Behaedi, R., & Ghoneim, E. M. (2018) · Journal of Archaeological Science Reports · doi:10.1016/j.jasrep.2018.05.019 · Cited by 14 · see citing works
Elfadaly, A., Shams, A. H., Elbehery, W., Elftatry, M., Wafa, O., Hiekl, A. M. A., Wilson, P., Silverstein, J., & Abouarab, M. A. R. (2022) · Archaeological Prospection · doi:10.1002/arp.1860 · Cited by 13 · see citing works
Satellite Data for All? Review of Google Earth Engine for Archaeological Remote Sensing
Firpi, O. A. (2016) · Internet Archaeology · doi:10.11141/ia.42.10 · Cited by 11 · see citing works
Howey, M. C. L., Palace, M., McMichael, C. N. H., & BRASWELL, B. H. (2014) · Advances in Archaeological Practice · doi:10.7183/2326-3768.2.3.195 · Cited by 10 · see citing works
Brandolini, F., Domingo-Ribas, G., Zerboni, A., & Turner, S. (2021) · Open Research Europe · doi:10.12688/openreseurope.13135.1 · Cited by 10 · see citing works
Abate, N., Roubis, D., Vitale, V., Sileo, M., Sogliani, F., Masini, N., & Lasaponara, R. (2022) · Journal of Physics Conference Series · doi:10.1088/1742-6596/2204/1/012020 · Cited by 10 · see citing works
Linking Past and Present Land-Use Histories in Southern Amazonas, Peru
Plekhov, D., VanValkenburgh, P., Abrams, P., Cutler, A., Han, J. S., Díaz, A. J. R., Sullivan, B., & Wernke, S. A. (2021) · Remote Sensing · doi:10.3390/rs13122274 · Cited by 8 · see citing works
Remote Sensing as a Tool for Tropical Ecology
Balzotti, C. S., Petersen, S. L., Terry, R. E., Scherer, A., & Golden, C. J. (2010) · Geography Compass · doi:10.1111/j.1749-8198.2010.00367.x · Cited by 6 · see citing works
Self-citationCrowd- and Community-Fuelled Archaeology.
Bonacchi, C., Bevan, A., Pett, D., & Keinan-Schoonbaert, A. (2015) · Archaeopress Publishing Ltd eBooks · doi:10.2307/jj.15135883.36 · Cited by 6 · see citing works
NASA Open-Source Science Initiative: Transform to OPen Science (TOPS)
Gentemann, C. L., Ivey, Y., Crawford, S., Baynes, K., Murphy, K., Ward, K., Cassidy, E. S., Ramachandran, R., Maskey, M., Luna-Cruz, Y., et al. (2021) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.5621673 · Cited by 4 · see citing works
Satellite based investigation for detection of ancient tombs’ looting in Cyprus
Agapiou, A., & Lysandrou, V. (2016) · Ktisis at Cyprus University of Technology (Cyprus University of Technology) · Cited by 2 · see citing works
Chapman, B., Blom, R. G., Golden, C. J., & Saatchi, S. (2008) · AGUFM · Cited by 1 · see citing works
Self-citationKocev, D., Simidjievski, N., Kostovska, A., et al. (2022) · arXiv (Cornell University) · doi:10.48550/arxiv.2208.03163 · Cited by 1 · see citing works
Flagged first, then by citations
Research works printed but not linked: 18
- Casana, 2014, Regional-Scale Archaeological Remote Sensing in the Age of Big Data: Automated Site Discovery vs. Brute Force Methods. Advances in Archaeological, Practice, 2, 222
- Golden, 2016, Reanalyzing environmental lidar data for archaeology: Mesoamerican applications and implications, Journal of Archaeological Science: Reports, Volume 9, October 2016, ISSN, 293–308, 2352
- Gutiérrez, G. and M.T. Searcy. (2016). Introduction to the UAV Special Edition. Advances in Archaeological Practice. 16(2).
- Hörr, 2014, Machine Learning Based Typology Development in Archaeology. Journal on Computing and Cultural, Heritage, 7
- Liss, 2017, Testing Google Earth Engine for the Automatic Identification and Vectorization of Archaeological Features: A Case Study of Faynan, Jordan. Journal of Archaeological Science: Reports., 15
- Liu, 2021, Remote Sensing-Based Monitoring of Immovable Cultural Relics, from Environmental Factors to the Protected Cultural Site: A Case Study of the Shunji Bridge, Sustainability., 13
- Mantellini, 2019, Evaluating the Human Impact on the Archaeological Landscape of Samarkand (Uzbekistan): A Diachronic Assessment of the Taylak District by Remote Sensing, Field Survey, and Local Knowledge. Archaeological Research, Asia, 20, 100143
- Marken, 2017, Maya Cities, People and Place: Comparative Perspectives from El Peru and Tikal, In Research Reports in Belizean Archaeology, V14, 177
- Olson, 2018, A Beginner’s Guide to Mesoscale Survey with Quadrotor-UAV Systems. Advances in Archaeological, Practice, 6
- Opitz, 2018, Recent Trends and Long-standing Problems in Archaeological Remote Sensing. Journal of Computer Applications, Archaeology, 1
- Ortman, 2019, A New Kind of Relevance for Archaeology. Frontiers in Digital, Humanities, 6
- Ramachandran, 2021, From Open Data to Open Science. Earth and Space, Science, 8
- Reygadas, 2021, Mapping Forest Disturbances across the Southwestern Amazon: Tradeoffs between Open-Source, Landsat-based Algorithms. Environmental Research Communications, 3, 9
- Sanders, W. T. (1956). The Central Mexican Symbiotic Region: A Study in Prehistoric Settlement Patterns. in Prehistoric Settlement Patterns in the New World, ed. G. R. Willey, pp. 115-127. Viking Publications in Anthropology, no. 2. New York: Wenner-Gren Foundation for Anthropological Research.
- Willey, 1953, Prehistoric settlement patterns in the Virú; Valley, Peru. Bureau of American Ethnology Bulletin., 155, 1
- Wimberly, 2022, Cloud-based applicatons for accessing satellite earth observations to support maleria early warning, Nature Scientific Data., 9
- Wong, 2019, Automating offshore infrastructure extractions using synthetic aperture radar and Google Earth Engine, Remote Sens. Environ., 233
- Xie, 2021, Mapping annual irrigation from landsat imagery and environmental variables across the coterminous United States, Remote Sens. Environ., 260
Cited by
Still being checked.
- Authors
- Herndon, K. E., Griffin, R., Schroder, W., Murtha, T., Golden, C., Contreras, D. A., Cherrington, E., Wang, L., Bazarsky, A., Kollias, G. V., & Alcover Firpi, O.
- Affiliations
- University of Alabama in Huntsville (US)
- University of Florida (US)
- Brandeis University (US)
- Corresponding author
- Herndon, Kelsey E.
- ORCID
- Herndon, Kelsey E.
- Venue
- Journal of Archaeological Science: Reports
- Publisher
- Elsevier BV
- Published
- 2023-08
- Volume
- 50
- Pages
- 104094
- ISSN
- 2352-409X (ISSN-L)
- OpenAlex
- W4383813200
- Cited by
- 21
- References
- 137
- Citations by year
- 2026: 4 · 2025: 10 · 2024: 7
- FWCI
- 12.25
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Archaeological Science Reports (publishedVersion, cc-by-nc-nd)
- Funders
- National Aeronautics and Space Administration (80NSSC20K1265)
- Topics
- Physical Sciences › Earth and Planetary Sciences › Space and Planetary Science › Archaeological Research and Protection
- Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Remote Sensing and Land Use
- Physical Sciences › Engineering › Ocean Engineering › Geophysical Methods and Applications
- Keywords
- Google Earth Engine, remote sensing of archaeological sites, cloud computing, automated feature detection, deep learning, environmental modeling, cultural heritage monitoring, open science, reproducibility, data access barriers
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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