GIS-based landform classification of Bronze Age archaeological sites on Crete Island

Abstract

Various physical attributes of the Earth’s surface are factors that influence local topography and indirectly influence human behaviour in terms of habitation locations. The determination of geomorphological setting plays an important role in archaeological landscape research. Several landform types can be distinguished by characteristic geomorphic attributes that portray the landscape surrounding a settlement and influence its ability to sustain a population. Geomorphometric landform information, derived from digital elevation models (DEMs), such as the ASTER Global DEM, can provide useful insights into the processes shaping landscapes. This work examines the influence of landform classification on the settlement locations of Bronze Age (Minoan) Crete, focusing on the districts of Phaistos, Kavousi and Vrokastro. The landform classification was based on the topographic position index (TPI) and deviation from mean elevation (DEV) analysis to highlight slope steepness of various landform classes, characterizing the surrounding landscape environment of the settlements locations. The outcomes indicate no interrelationship between the settlement locations and topography during the Early Minoan period, but a significant interrelationship exists during the later Minoan periods with the presence of more organised societies. The landform classification can provide insights into factors favouring human habitation and can contribute to archaeological predictive modelling.

GIS-based Landform Classification of Eneolithic Archaeological Sites in the Plateau-plain Transition Zone (NE Romania): Habitation Practices vs. Flood Hazard Perception

“…Positive or negative values of TPI indicate that the central point is located higher (z 0 > z) or lower (z 0 < z), respectively, than its average surroundings. In this equation, the range of TPI depends not only on distinguishes between z 0 and z, but also with respect to R, because a large R-value generally reveals large-scale landform units (major valleys, mountains, hills), while smaller values highlight small-scale features (stream valleys, headwaters, local ridges) [4,5,29] (Figure 4a).…”

“…Method (1): classification of the topographic surface into discrete slope position classes using the DEV [29] (Figure 4d). Method (2): classification of the topographic surface into a complex landscape feature by combining the parameters from two neighbourhood size [4,28]…”

“…Landforms are defined as specific geomorphic features on the Earth's surface, ranging from large-scale features (e.g., plains, mountain ranges) to small-scale features (e.g., individual hills, valleys), as well as their component landforms, such as hilltops, valley bottoms, exposed ridges, flat plains, and upper or lower slopes [1][2][3]. In recent decades, the development of GIS software and free access to datasets has attracted the interest of researchers in implementing new computer algorithms to approach the morphometric attributes and topography of the Earth's surface [2,4]. Also, there has been an upward trend in the use of GIS-based analysis to classify landforms over various scientific fields such as geo-pedology [5][6][7][8], geomorphology and seafloor mapping [9][10][11][12][13][14][15], hydrology [16][17][18], climatology [19], landscape mapping and ecology [20,21], and archaeology [4,[22][23][24].…”

“…In this context, one of the first approaches to find application in archaeological studies was the analysis of convexity, concavity, and flatness of the topographic surface [28][29][30][31]. Despite this, at present only a few studies with applications in the field of archaeology based on GIS-landform classifications have been developed [4,24,28,29]. In recent years, there have been intensive applications of LiDAR data in the analysis of floods in a GIS environment [32,33], yet no applications towards prehistoric flood hazards.The territory of NE Romania is characterized by a high density of Eneolithic archaeological sites (chronological framework: ca.…”

“…Besides the literature on the morphological features in the study area [42][43][44][45][46], only a few works deal with the local or the relative topographic position of archaeological settlements in the landscape [47,48]; most of them refer to the evaluation of cultural heritage sites to natural hazards (landslides, gully erosion) and anthropogenic impact [49][50][51][52][53][54].Understanding the connections between the small-scale features, large-scale landforms, flood hazard perception, and the types of archaeological settlement is an important method applied in the study of the prehistoric peoples because the landscape can reveal insights into settlement distribution and dynamics over time [4,27]. This paper provides the first landform classification of 730 Eneolithic sites, using the TPI (Topographic Position Index) [3,5,28,55], and the SD (standard deviation) of the mean elevation, abbreviated as DEV by [29], around archaeological sites [3,4,29], which can classify the landscape in terms of slope position and landform categories and morphological classes based on the geomorphology [1,4,56,57]. The results can provide insights into factors favoring human habitation during the Eneolithic period in the plateau-plain transition zone of NE Romania and contribute to archaeological predictive modelling at regional-scale based on small-scale morphological features and flood hazard patterns [45,49,[58][59][60][61].…”