A comprehensive test of the Locally-Adaptive Model of Archaeological Potential (LAMAP). (February 2017)
- Record Type:
- Journal Article
- Title:
- A comprehensive test of the Locally-Adaptive Model of Archaeological Potential (LAMAP). (February 2017)
- Main Title:
- A comprehensive test of the Locally-Adaptive Model of Archaeological Potential (LAMAP)
- Authors:
- Carleton, W. Christopher
Cheong, Kong F.
Savage, Dan
Barry, Jack
Conolly, James
Iannone, Gyles - Abstract:
- Abstract: Extensive archaeological surveys are critical for understanding past human-landscape interaction, but they are frequently impeded by access difficulties, rugged terrain, or obscurant vegetation. These challenges can make extensive surveys prohibitively costly and time-consuming. Consequently, many archaeologists are interested in predictive techniques—i.e., methods that can estimate the potential for a given region to contain archaeological remains. Predictive techniques can reduce the costs of extensive surveys by allowing archaeologists to focus on the regions with the greatest archaeological potential. A few years ago, our research team developed a new technique called the Locally-Adaptive Model of Archaeological Potential (LAMAP) and used it to enhance our understanding of the relationship between the Classic Maya centre of Minanha, its surrounding landscape, and nearby Maya centres (Carleton et al. 2012). However, when we introduced the method its efficacy had yet to be comprehensively tested. Recently, we tested its efficacy using a combination of ground-truth survey and remote sensing of Classic Maya sites in west-central Belize. The test involved identifying previously unrecorded archaeological resources and comparing their locations to the LAMAP prediction and to a random model that acted as a null hypothesis. Our results indicate that the model performs very well. The high-potential areas of the study region contained three times more archaeological sitesAbstract: Extensive archaeological surveys are critical for understanding past human-landscape interaction, but they are frequently impeded by access difficulties, rugged terrain, or obscurant vegetation. These challenges can make extensive surveys prohibitively costly and time-consuming. Consequently, many archaeologists are interested in predictive techniques—i.e., methods that can estimate the potential for a given region to contain archaeological remains. Predictive techniques can reduce the costs of extensive surveys by allowing archaeologists to focus on the regions with the greatest archaeological potential. A few years ago, our research team developed a new technique called the Locally-Adaptive Model of Archaeological Potential (LAMAP) and used it to enhance our understanding of the relationship between the Classic Maya centre of Minanha, its surrounding landscape, and nearby Maya centres (Carleton et al. 2012). However, when we introduced the method its efficacy had yet to be comprehensively tested. Recently, we tested its efficacy using a combination of ground-truth survey and remote sensing of Classic Maya sites in west-central Belize. The test involved identifying previously unrecorded archaeological resources and comparing their locations to the LAMAP prediction and to a random model that acted as a null hypothesis. Our results indicate that the model performs very well. The high-potential areas of the study region contained three times more archaeological sites than low potential areas, a statistically significant result compared to our null model. Our findings indicate that the LAMAP is a useful new archaeological prediction tool and, as a corollary, that the hypothesis of human land-use behaviour underpinning it might accurately reflect the behaviour of the Classic Maya. Highlights: In 2012, we proposed the Locally-Adaptive Model of Archaeological Potential (LAMAP). At the time, we created a LAMAP prediction involving Classic Maya sites in Belize. We tested the model using new LiDAR and ground-based survey data from the study area. The LAMAP model appears to perform very well. High-potential areas contain about 3 times more sites than low-potential areas. … (more)
- Is Part Of:
- Journal of archaeological science. Volume 11(2017)
- Journal:
- Journal of archaeological science
- Issue:
- Volume 11(2017)
- Issue Display:
- Volume 11, Issue 2017 (2017)
- Year:
- 2017
- Volume:
- 11
- Issue:
- 2017
- Issue Sort Value:
- 2017-0011-2017-0000
- Page Start:
- 59
- Page End:
- 68
- Publication Date:
- 2017-02
- Subjects:
- Classic Maya -- GIS -- Predictive modeling -- LiDAR -- Survey -- Human-landscape interaction
Archaeology -- Periodicals
Archaeology -- Research -- Periodicals
930.1 - Journal URLs:
- http://www.sciencedirect.com/science/journal/2352409X ↗
http://www.sciencedirect.com/ ↗ - DOI:
- 10.1016/j.jasrep.2016.11.027 ↗
- Languages:
- English
- ISSNs:
- 2352-409X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 7863.xml