Examining Land-Use through GIS-Based Kernel Density Estimation: A Re-Evaluation of Legacy Data from the Berbati-Limnes Survey

Abstract

The use of archaeological survey data for evaluation of landscape dynamics has commonly been concerned with the distribution of settlements and changes in number of recorded sites over time.Here we present a new quantitative approach to survey-based legacy data, which allows further assessments of the spatial configuration of possible land-use areas. Utilizing data from an intensive archaeological survey in the Berbati-Limnes area, Greece, we demonstrate how GIS-based kernel density estimations (KDE) can be used to produce cluster-based density surfaces that may be linked to past land-use strategies. By relating density surfaces to elevation and slope, it is also possible to quantify shifts in the use of specific environments on a regional scale, allowing us to model and visualize land-use dynamics over time. In this respect, the approach provides more multifaceted information to be drawn from archaeological legacy data, providing an extended platform for research on human-environment interactions.

Climate variability and landscape dynamics in the Late Hellenistic and Roman north-eastern Peloponnese

“…We base our analyses on digitised site data from five archaeological surveys (Figure 4). Using a 2.5km radius analysis for each dataset, representing an idealised catchment zone for Greek agricultural settlements (see Bintliff 2012: 271), we created a threetiered kernel division representing a maximum extent of possible land use, a medium extent and a minimum extent, the latter of which shows only the high density of land use (following the method presented in Bonnier et al 2019). The results of the individual analyses carried out for each dataset were then merged to provide an aggregated quantification of trends in land-use expansion and contraction.…”

Matilda’s castles, northern Apennines: geological and geomorphological constrains

“…In our work, we chose to focus on structural features and slope processes: other than producing the most widespread landforms in the landscape, these represent the most important factors influencing terrain stability of the region and therefore infrastructure stability. To compare the potential impact of geomorphological features on castle locations landslides and faults on the map were transformed into point layers (100 m equal interval points for fault lines, centroids for landslide polygons, area-weighted random points for badlands polygons) and visualised as influence areas through analyses of density based on kernel method (di Lernia et al, 2013;Silvermann, 1986), with a radius of 500 m. This method allows to produce heatmaps representing the main hotspots for the considered features, in order to identify high-risk areas (Bonnier, Finné, & Weiberg, 2019;Danese, Lazzari, & Murgante, 2008).…”

Spatial-Temporal Analysis of Land Cover and Use Changes Using Gis Tools. Case Study Băneasa Neighborhood, Bucharest

“…Heat Map dynamic method is used to view the distribution of data in a particular area. Kernel Density Estimation has increasingly been used to examine the spatial distribution and frequency of land use (Scăunaș, Merciu, 2016;Bonnier et al, 2019;Merciu et al, 2018). Kernel Density Estimation is a useful method to investigate the density calculation and representation of spatially and temporally highly dynamic point data sets (Krisp, Peters, 2011).…”