Communities, Settlements, Sites, and Surveys: Regional-Scale Analysis of Prehistoric Human Interaction

2005 ◽  
Vol 70 (1) ◽  
pp. 5-30 ◽  
Author(s):  
Christian E. Peterson ◽  
Robert D. Drennan

The study of developing complex societies can fruitfully focus on the human interactions that define communities, which have always been at the heart of settlement pattern research. Yet little attention has been paid to how communities of varying scales can actually be identified in archaeological survey data. Most often sites have simply been assumed to correspond to communities, although this practice has been criticized. Methods are offered to delineate communities at different scales systematically in survey data, and their implications for field data collection strategies are explored comparatively for cases from northeast China, Mesoamerica, and the northern Andes.

Limnology ◽  
2021 ◽  
Vol 22 (2) ◽  
pp. 169-177
Author(s):  
Yo Miyake ◽  
Hiroto Makino ◽  
Kenta Fukusaki

2021 ◽  
Vol 289 ◽  
pp. 112494
Author(s):  
Giuseppe Modica ◽  
Salvatore Praticò ◽  
Luigi Laudari ◽  
Antonio Ledda ◽  
Salvatore Di Fazio ◽  
...  

Geosciences ◽  
2018 ◽  
Vol 8 (7) ◽  
pp. 261 ◽  
Author(s):  
Christos Polykretis ◽  
Antigoni Faka ◽  
Christos Chalkias

The main purpose of this study is to explore the impact of analysis scale on the performance of a quantitative model for landslide susceptibility assessment through empirical analyses in the northern Peloponnese, Greece. A multivariate statistical model like logistic regression (LR) was applied at two different scales (a regional and a more detailed scale). Due to this scale difference, the implementation of the model was based on two landslide inventories representing in a different way the landslide occurrence (as point and polygon features), and two datasets of similar geo-environmental factors characterized by a different size of grid cells (90 m and 20 m). Model performance was tested by a standard validation method like receiver operating characteristics (ROC) analysis. The validation results in terms of accuracy (about 76%) and prediction ability (Area under the Curve (AUC) = 0.84) of the model revealed that the more detailed scale analysis is more appropriate for landslide susceptibility assessment and mapping in the catchment under investigation than the regional scale analysis.


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