Articles by Giuseppe Espa

The paper summarises some preliminary results obtained by a research team of the Istituto per le Tecnologie Applicate ai Beni Culturali of the Italian National Research Council (CNR-ITABC) in the archaeological area of Sabina Tiberina (Rieti). The study makes use of statistical methods and information technology with the goal of implementing a GIS of the above mentioned territory. The area investigated, falling within the counties of Magliano Sabina and Stimigliano, presents a wide chronological stratification dating from prehistory to the Roman age. The anthropological pre-existence considered show differences depending on settlements themselves which are always numerous in the various ages; in fact the proximity of the river (the Tiber) is the reason for their existence, allowing a cultural transmission besides the natural function of trade route. This paper is divided into two parts. In the first, all data concerning surveys carried out with the goal of finding and classifying the settlements of Roman age are included. In the second, some descriptive-documentary aspects gained through developing the GIS, together with statistical processing aimed at the creation of maps of data and settlements, are commented upon.

Recent studies have emphasised the usefulness of a jointed employment, in historical and archaeological research, of the most advanced computer technologies with statistical methods. In this work, as an application of a Geographical Information System (GIS), we present a Matlab language program for the statistical analysis of spatial data related to ancient human settlements. The explanation of the program is preceded by some notes about the GIS, the area from which data have been collected, and the statistical methods applied to analyse the data.

The aim of this paper is to introduce a class of testable statistical models aimed at modelling archaeological sites locations (ASL) or a continuous space and at producing probability maps of ASL. These models are based on collected statistical and auxiliary information (such as information about the slope or exposure of the land, the topography, the hydrology, the topology, etc.). More explicitly the model for the ASL is based on the assumption that the location of the existing archaeological sites is fixed and that the location of new archaeological sites not yet found is a realization of a non-stationary point process depending on the spatial interaction with other existing sites, on the distance from important location or communication networks, and on a set of auxiliary variables. It is also possible to introduce into the discussion information we have about the archaeological site dimensions. In fact, it is plausible that the interaction between existing archaeological sites and candidate locations for new archaeological sites is dependent on their dimension. These models can prove valuable in that they formalize some “common sense” knowledge and can help in producing automated probability maps on a continuous space to support excavation decisions.

The aim of this work is to contribute to a better understanding of the historical and archaeological heritage. Archaeological and territorial data have been collected and processed in a GIS in order to provide information on the evolution of the population settlement in a selected area used as a case study. The area investigated was that located between the rivers Nera and Aniene (North-South direction) and between the river Tiber and the Sabine Mountains (East-West direction). It is historically identified as the “Sabina Tiberina” region. This area is characterised by a large number of sequential settlements of different populations beginning in the Iron through to the Medieval period. The GIS developed offers the possibility of describing and interpreting the territorial changes caused by the various populations. One of the main features of the GIS is its easy use for non-expert users (such as teachers, students and decision makers). Examples of different types of maps that can be generated by our GIS are presented. Two examples of composite maps containing different types of information (geographical, historical, geological etc.) are presented to show the possibilities afforded by the system.

The aim of the work described here is to contribute to the knowledge about the ancient population located in the Ager Eretanus, through the application of a statistical methodology known as “point pattern analysis”. We first present a brief discussion of the management of an application-oriented GIS in the field of archaeological research. We then present the results of a “second order analysis” undertaken on the data at our disposal. Finally, we discuss two interesting methodological problems: the first concerns the evaluation of the influence exerted on the model by possible errors in the location of the points; the second regards the proposal of a graphical representation which proves very useful in showing the variable intensity of the distribution of archaeological site.

Forecasting statistical models are becoming increasingly important in archaeological research. One of the reasons of this popularity is that archaeological sites tend to present themselves in particular environments so that forecasting models can help in identifying areas where the probability is higher based on previously collected statistical information. In the present paper we consider a class of statistical models designed to produce maps of the probability for archaeological site location (ASL) which incorporate both deductive and inductive considerations. In the discussion we criticise the use of the logistic regression for the production of ASL probability maps, a popular approach known in archaeological literature as the “integrated strategy”. The application of the method is statistically incorrect since in archaeological studies the hypothesis of independence between sites, which is at the basis of the logistic regression model, is violated. To overcome such limitations we propose two alternative models. The first one is an autopredictive model in which the probability of ASL is modelled as a function of the observations coming from field surveys in neighbouring zones. This approach accounts for the problem of non-independency of observations, but neglects a priori auxiliary information on the archaeological area. The second approach is a more comprehensive one which overcomes the problems of logistic regressions while preserving the role of a priori information.

Recently, an interesting debate has developed in the context of historic archaeological disciplines concerning the employment of typical technical scientific methodologies and instruments utilized in research. The aim of this article is to contribute to this debate by showing how it is possible to conjointly utilize information technology techniques and statistical methods in archaeological research for both descriptive and interpretative purposes. The objective was successfully achieved by integrating several common spatial-statistical methods (Ripley's K-function) with the potential offered by GIS. In fact, the collection of files and graphical data representation was followed up by statistical data processing which, with the identification of several important parameters, has enabled GIS files to be improved with further information for subsequent processing.