Archaeological Research and Protection Open access Peer reviewed

Mapping past forests in the Atacama Desert, Chile: A remote sensing and machine learning approach for archaeology

Elena Balmaceda-Baraona, Víctor Méndez, Virginia McRostie, Ale Vidal-Elgueta and 1 more

Journal of Archaeological Science | Sep 15, 2026

Abstract

Abstract

The last decades have seen a significant increase in the use of spatial and remote sensing analytical techniques in the field of archaeology, leading to new perspectives and research questions. However, the full potential of these methods remains largely unexplored. Albeit the focus on site detection and resource mapping has been gaining traction, we have yet to examine the great potential these techniques could have to support various tasks, such as the design of targeted field campaigns, process optimization, and the identification of new findings, mainly in large and difficult-to-access areas. This paper presents a case study focused on mapping sub-fossil botanical remains (wood, leaf litter, charcoal and tree imprints) from past forests in the Pampa del Tamarugal (PdT), Atacama Desert, Chile (21°07′36″ S, 69°26′49″ O). These areas have proved key for the lives of pampean populations since the region's first settlements around 12.000 calibrated years before present (cal yr BP), being incorporated not only into subsistence strategies but also into their cosmologies. In this study, we present an experimental remote sensing model using Sentinel-2 free multispectral satellite imagery, which, when combined with ground truth data, allows for the detection of spectral proxies associated with past forests' spatial distribution. The results validate the use of remote sensing methods for the documentation of these past natural or silvicultural forest patches. Through the discussion of this case study, this paper highlights the remarkable potential of combining machine learning algorithms with traditional archaeological and paleoecological research, emphasizing their implications for field campaign planning and development, as well as resource optimization.

Direct answer

What can I do from this paper page?

Use this page to scan "Mapping past forests in the Atacama Desert, Chile: A remote sensing and machine learning approach for archaeology" quickly: start with the summary and abstract, then check the authors, source, topics, and related papers. From here, open Scollr to follow Archaeological Research and Protection, save the paper, or map adjacent work.

Authors

Researchers on this paper

Elena Balmaceda-Baraona

first | Pontificia Universidad Católica de Chile

Víctor Méndez

middle | Pontificia Universidad Católica de Chile

Virginia McRostie

middle | Pontificia Universidad Católica de Chile

Ale Vidal-Elgueta

middle | Pontificia Universidad Católica de Chile

Francisca P. Díaz

last | Pontificia Universidad Católica de Valparaíso | ORCID 0000-0002-1100-7801

Research areas

Follow related topics

Citation

BibTeX

@article{BalmacedaBaraona2026Mapping,
  title = {Mapping past forests in the Atacama Desert, Chile: A remote sensing and machine learning approach for archaeology},
  author = {Elena Balmaceda-Baraona and Víctor Méndez and Virginia McRostie and Ale Vidal-Elgueta and Francisca P. Díaz},
  journal = {Journal of Archaeological Science},
  year = {2026},
  doi = {10.1016/j.jas.2026.106688},
  url = {https://doi.org/10.1016/j.jas.2026.106688}
}

FAQ

Using this paper in a discovery workflow

How do I find related work for this paper?

Use the related papers and topic links on this page as starting points. In Scollr, you can also open the paper and build a literature map around its references, citing papers, and related work.

How can I keep up with new Archaeological Research and Protection papers?

Follow Archaeological Research and Protection in Scollr. New papers from the topic flow into a personalized feed, and you can save useful studies to revisit later.

Can I cite this paper from this page?

This page includes a static BibTeX block for Mapping past forests in the Atacama Desert, Chile: A remote sensing and machine learning approach for archaeology. Always verify the DOI, source, and publication details against the publisher record before submitting a manuscript.

Follow this research in Scollr

Follow the topics and authors behind this paper, save useful studies, and build a literature map when you are ready to go deeper.

Get the app