It must be right, GIS told me so! Questioning the infallibility of GIS as a methodological tool
Abstract
While the benefits of GIS are widely touted among archaeologists today, less attention has been paid to the potential pitfalls and drawbacks of this undeniably important methodological tool. One of the greatest challenges of geospatial modeling is unbalanced data: due to the nature of the archaeological record, we can never assume that the remnants of past behavioral processes we are working with constitute a fully representative sample. Rather, our datasets are reflective of differential social and natural preservation conditions, as well as research biases. Most regional geospatial studies must collate diverse data collected over decades by researchers with varying backgrounds and goals, using assorted spatial scales and levels of technological sophistication. Such factors contribute substantial uncertainty to our models, uncertainty that should be recognized, quantified, and mitigated. If GIS techniques are to continue shifting the way we conduct archaeology and improve our abilities to answer questions regarding past behavior, then we must question the infallibility of GIS as a methodological tool and direct more attention toward developing robust geospatial applications that can meet the idiosyncratic needs of archaeological analysis. This paper explores one example of how such uncertainty investigation can be conducted.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
The Elements of Statistical Learning
Hastie, T., Tibshirani, R., & Friedman, J. (2009) · Springer Series in Statistics · doi:10.1007/978-0-387-84858-7 · Cited by 25,970 · see citing works
The Elements of Statistical Learning
Hastie, T., Friedman, J., & Tibshirani, R. (2001) · Springer Series in Statistics · doi:10.1007/978-0-387-21606-5 · Cited by 24,162 · see citing works
Empirical Model Building and Response Surfaces
Freeny, A. E., Box, G. E. P., & Draper, N. R. (1988) · Technometrics · doi:10.2307/1270169 · Cited by 5,238 · see citing works
Rapoport, A. (1986) · Cited by 2,276 · see citing works
Empirical Model-Building and Response Surfaces.
Kshirsagar, A. M., Box, G. E. P., & Draper, N. R. (1988) · Journal of the American Statistical Association · doi:10.2307/2288890 · Cited by 1,894 · see citing works
von Bertalanffy, L. (1949) · Nature · doi:10.1038/163156a0 · Cited by 228 · see citing works
Experiencing the past? The development of a phenomenological archaeology in British prehistory
Brück, J. (2005) · Archaeological Dialogues · doi:10.1017/s1380203805001583 · Cited by 227 · see citing works
Robin, C. (2002) · Journal of Social Archaeology · doi:10.1177/14605302002002397 · Cited by 148 · see citing works
GIS, critique, representation and beyond
Hacıgüzeller, P. (2012) · Journal of Social Archaeology · doi:10.1177/1469605312439139 · Cited by 88 · see citing works
The Concept of Equifinality in Taphonomy
Lyman, R. L. (2004) · Cited by 67 · see citing works
Understanding the bias-variance tradeoff
Fortmann‐Roe, S. (2012) · Cited by 63 · see citing works
An Introduction to Prehistoric Archeology
Hole, F., & Heizer, R. F. (1969) · Andalas University Repository (Andalas University) · Cited by 62 · see citing works
Simulating change : archaeology into the twenty-first century
Costopoulos, A., & Lake, M. (2010) · Cited by 53 · see citing works
An Introduction to Prehistoric Archaeology
Hole, F., & Heizer, R. F. (1966) · Anthropologica · doi:10.2307/25604680 · Cited by 52 · see citing works
White, A. A. (2013) · Journal of Anthropological Archaeology · doi:10.1016/j.jaa.2012.12.003 · Cited by 31 · see citing works
Uncertainty and Sensitivity Analysis in Archaeological Computational Modeling
Burg, M. B., Peeters, H., & Lovis, W. A. (2016) · Interdisciplinary Contributions to Archaeology/Interdisciplinary contributions to archaeology · doi:10.1007/978-3-319-27833-9 · Cited by 28 · see citing works
Wickstead, H. (2009) · Journal of Social Archaeology · doi:10.1177/1469605309104138 · Cited by 27 · see citing works
Burg, M. B. (2013) · Journal of Archaeological Science · doi:10.1016/j.jas.2013.01.008 · Cited by 22 · see citing works
Introduction to Uncertainty and Sensitivity Analysis in Archaeological Computational Modeling
Burg, M. B., Peeters, H., & Lovis, W. A. (2016) · Interdisciplinary Contributions to Archaeology/Interdisciplinary contributions to archaeology · doi:10.1007/978-3-319-27833-9_1 · Cited by 10 · see citing works
Watts, J. L. (2013) · The Digital Archeological Record (tDAR) · doi:10.6067/xcv8v125pd · Cited by 6 · see citing works
White, A. A. (2016) · Interdisciplinary Contributions to Archaeology/Interdisciplinary contributions to archaeology · doi:10.1007/978-3-319-27833-9_7 · Cited by 5 · see citing works
Watts, J. L. (2016) · Interdisciplinary Contributions to Archaeology/Interdisciplinary contributions to archaeology · doi:10.1007/978-3-319-27833-9_6 · Cited by 2 · see citing works
Assessing Nonlinear Behaviors in an Agent-Based Model
Carroll, J. W. (2016) · Interdisciplinary Contributions to Archaeology/Interdisciplinary contributions to archaeology · doi:10.1007/978-3-319-27833-9_5 · Cited by 2 · see citing works
Burg, M. B. (2016) · Interdisciplinary Contributions to Archaeology/Interdisciplinary contributions to archaeology · doi:10.1007/978-3-319-27833-9_4 · Cited by 2 · see citing works
Burg, M. B. (2016) · Landscape Archaeology Conference (LAC) · doi:10.5463/lac.2014.58 · Cited by 1 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- Eastman, 1999, vol. 2
Cited by
Sorted by citations
Modelling of pathways and movement networks in archaeology: an overview of current approaches
Verhagen, P., Nuninger, L., & Groenhuijzen, M. R. (2019) · Computational Social Sciences · doi:10.1007/978-3-030-04576-0_11 · Cited by 117 · see citing works
Lewis, J. (2021) · Journal of Archaeological Method and Theory · doi:10.1007/s10816-021-09522-w · Cited by 53 · see citing works
Seifried, R. M., & Gardner, C. A. M. (2019) · Journal of Archaeological Science: Reports · doi:10.1016/j.jasrep.2019.01.014 · Cited by 29 · see citing works
A maxent predictive model for hunter-gatherer sites in the southern pampas, argentina
Rafuse, D. J. (2021) · Open Quaternary · doi:10.5334/oq.97 · Cited by 17 · see citing works
Counter-Mapping Maroon Cartographies: GIS and Anticolonial Modeling in St. Croix
Dunnavant, J. P., Wernke, S. A., & Kohut, L. E. (2023) · ACME · doi:10.7202/1107310ar · Cited by 12 · see citing works
- Authors
- Brouwer Burg, M.
- Venue
- Journal of Archaeological Science
- Publisher
- Elsevier BV
- Published
- 2017-08
- Volume
- 84
- Pages
- 115-120
- ISSN
- 0305-4403 (ISSN-L)
- OpenAlex
- W2415808967
- Cited by
- 34
- References
- 25
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 4 · 2023: 5 · 2022: 5 · 2021: 4 · 2020: 4 · 2019: 5 · 2018: 4
- FWCI
- 7.78
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Archaeological Science (publishedVersion)
- The 81st Annual Meeting of the Society for American Archaeology
- Funders
- Albert Einstein College of Medicine, Yeshiva University
- Topics
- Physical Sciences › Earth and Planetary Sciences › Space and Planetary Science › Archaeological Research and Protection
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Spatial and Panel Data Analysis
- Social Sciences › Arts and Humanities › Archeology › Archaeological and Geological Studies
- Keywords
- geographic information systems, archaeological data, class imbalance, sampling bias, uncertainty quantification, geospatial modeling, archaeological record, spatial scale, research bias, methodological critique
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
