Introduction

This chapter examines the different ways in which spatial datasets are acquired and structured to take advantage of the visualisation and analytical abilities of GIS. It is conventional to distinguish between primary and secondary data sources because acquisition methods, data formats and structuring processes differ considerably between the two. Primary data consist of measurements or information collected from field observations, survey, excavation and remote sensing. Secondary data refer to information that has already been processed and interpreted, available most often as paper or digital maps. Many users of GIS wish to integrate primary and secondary datasets (for example, to plot the location of primary survey data across an elevation model obtained from a data supplier). Both types of data have advantages and disadvantages, which this chapter examines in some detail. By the end of this chapter you will be familiar with the ways in which both primary and secondary data are obtained, and the issues and procedures for assessing the quality of combined datasets.

Primary geospatial data

Primary, or ‘raw’, geospatial data has not been significantly processed or transformed since the information was first captured. Archaeologists generate vast quantities of primary data during excavation and survey, such as the location of settlements, features and artefacts, geoarchaeological and palaeo-environmental data and the location of raw material sources within the landscape. Raw data may also be available from databases of information compiled by other agencies: the location of archaeological sites, for example, can be obtained from Sites and Monuments Records and published site ‘gazetteers’.

Introduction: thinking about regions

A GIS can be used to create, represent and analyse many kinds of region. Some regions have an objective reality, at least to the extent that they are widely recognised and have a readily detectable influence on aspects of human behaviour. The most obvious examples of this kind are sociopolitical regions such as the territories of modern nation states. Other regions have an objective reality in another sense: that they are defined by some natural process. A good example of a natural region is the watershed; that is, the area within which all rainfall drains to some specified point in a drainage network. A third kind of region is essentially just analytical in the sense that it is created for a specific short-lived purpose and may never be recognised by anyone other than the analyst. For example, an archaeologist might determine the region containing all land within 100 m of a proposed high-speed railway line in order to identify at-risk archaeological sites, but it is the list of sites and their locations, not the region, that is fed back into the planning process.

Regions are readily represented as polygons in a vector map, or less efficiently as cells coded in such a way as to distinguish between inside and outside a region in a raster map. Where the extent of regions are known in advance of GIS-based analysis, as is often the case with sociopolitical regions, their generation and manipulation within a GIS is mostly an issue of data capture and map query.

Introduction: point and spatial operations

In this chapter we introduce a number of point and spatial operations that can be performed on continuous field data. We begin with the use of map algebra, before moving on to the calculation of derivatives (e.g. slope and aspect) and spatial filtering (e.g. smoothing and edge detection), all of which are widely used by archaeologists. In the final section we introduce more specialised techniques that have archaeological potential.

Map algebra is a point operation, whereas the other techniques discussed in this chapter are spatial operations. Point operations compute the new attribute value of a location with coordinates (x, y) from the attribute values in other maps at the same location (x, y), (Fig. 9.1b). In contrast, spatial operations compute the new attribute value of a location from the attribute values in the same map, but at other locations – those in the neighbourhood (Fig. 9.1a). The neighbourhood used in a spatial operation may or may not be spatially contiguous. For example, slope is usually calculated using the elevation values in a neighbourhood comprising the four or eight map cells immediately adjacent to the location in question (see below), but we saw in Chapter 6 how inverse distance weighting interpolates elevation values from some number of nearest spot heights, irrespective of how far away those spot heights actually are.

Introduction

Cartographers have long recognised the influence that maps have on the shaping of spatial consciousness (Monmonier 1991; Wood 1992; Lewis and Wigen 1997). The purpose of this chapter is to explore the way maps, whether paper or digital, may be used to present spatial information and to highlight some design principles to maximise their effectiveness at this task. In doing so we describe a range of mapping techniques appropriate for the different sorts of data routinely handled by archaeologists. We also consider some major cartographic principles and design conventions that help make maps effective communication devices, and discuss the growing importance of the Internet and interactive mapping for the publication of spatial data.

Designing an effective map

As defined in Chapter 2, maps are traditionally divided into two categories: topographic and thematic. The former term describes maps that contain general information about features of the Earth's surface, whereas thematic maps are limited to single subjects, such as soils, geology, historic places, or some other single class of phenomena. Both types of map must contain some basic pieces of information so that the reader is able to comprehend and contextualise the data that is being presented. The most basic of these, without which a map is difficult if not impossible to understand, are: (i) a title; (ii) a scale; (iii) a legend and (iv) an orientation device, such as a north arrow (Table 12.1).

Introduction

This chapter describes the way that spatial and attribute data are structured and stored for use within a GIS. It provides the necessary information about data models and database design to enable archaeologists unfamiliar with computer databases to make appropriate decisions about how best to construct a system that will work well and efficiently.

A database is a collection of information that is structured and recorded in a consistent manner. A card catalogue that records information about archaeological sites, such as their location and date, is as much a database as a full-fledged web-searchable digital sites and monuments record. Digital databases differ from their paper counterparts mainly in that they are dependent on database software for searching and retrieving records. The complexity of the data structure will also be increased as digital databases are often broken into several different related files. This reduces the amount of duplicated information in a database, improves access speed and also enables the retrieval of small subsets of data rather than complete records. Software that is used to store, manage and manipulate data is referred to as a Database Management System (DBMS). The objectives of a DBMS are to store and retrieve data records in the most efficient way possible, from both the perspective of the overall size of the database and also the speed at which that data can be accessed.

The technology of DBMS is a major research focus in computer science.

Introduction

Spatial analysis lies at the core of GIS and builds on a long history of quantitative methods in archaeology. Many of the foundations of spatial analysis were established by quantitative geographers in the 1950s and 1960s, and adopted and modified by archaeologists in the 1970s and 1980s. For a variety of reasons, spatial analysis fell out of fashion both in archaeology and in the other social sciences. In part this was because of the perceived overgeneralisation of certain types of mathematical models, but also because of a shift towards more contextually orientated and relativist studies of human behaviour. Recently, however, there has been a renewed interest in the techniques of spatial analysis for understanding the spatial organisation of human behaviour that takes on board these criticisms. In the last decade there have been several advances within the social sciences, particularly geography and economics, in their ability to reveal and interpret complex patterns of human behaviour at a variety of scales, from the local to the general, using spatial statistics. Archaeology has participated somewhat less in these recent developments, although there is a growing literature that demonstrates a renewed interest in the application of these techniques to the study of past human behaviour. In this chapter we review some historically important methods (e.g. linear regression, spatial autocorrelation, cluster analysis) and also highlight more recent advances in the application of spatial analysis to archaeology (e.g. Ripley's K, kernel density estimates, linear logistic regression).

Introduction

The most valuable (non-human) resource that any organisation possesses is its data. Hardware and software are easily replaceable but the loss of data can be catastrophic for an organisation. Information loss, whether full or partial, is easily avoided through the routine taking of backups and the storage of data off-site. As there is plenty of readily available information on how best to implement a backup and data-recovery procedure, we do not consider it in any detail in this book. What is less obvious, particularly to those new to GIS and digital data, is the similarly important task of data maintenance. Consider, for example, the following three scenarios:

• An employee in a cultural resource management (CRM) unit is assigned the task of updating site locations from newly acquired GPS data. How should the fact that a few site locations have been updated be documented and where and how should the old data be stored?

• An aerial photograph of a portion of landscape has been rectified and georeferenced, and is ready to be used to delineate features of archaeological significance. How and where should information about the degree of error in the georeferencing be documented? Where and how should the errors for the newly digitised archaeological features be documented?

• A research student is collecting data on soil types for Eastern Europe from several different national agencies that each have different scales and recording systems. How is this student able to search and compare and ultimately integrate datasets in a manner that ensures the data will be appropriate for his/her needs?

This chapter reviews four typical applications of GIS in archaeology: management of archaeological resources, excavation, landscape archaeology and the spatial modelling of past human behaviour. For each application we discuss some general issues concerning the use of GIS in that particular context, followed by a presentation of a case study that illustrates the contribution that GIS has made. Although these examples are in no way exhaustive, they do provide a good overview of the capabilities and potential contributions that GIS can make to archaeological management and research.

Management of archaeological resources

It is not our intention to discuss the objectives of cultural resource management (CRM), nor the appropriate structure of a spatial database for managing the archaeological record, as these decisions are most appropriately made by government bodies and the archaeologists charged with the tasks of recording and managing the archaeological resource. However, we note that archaeological and historic databases have increasingly been subject to government scrutiny. In the UK, this most recently occurred in a parliamentary review of archaeology that took place in 2003 (APPAG 2003; Gilman 2004). In particular, the UK archaeological databases termed ‘Sites and Monuments Records’ (SMRs) are under review in light of recent developments in information technology, especially GIS and the Internet (e.g. Newman 2002). This report makes it clear that SMRs should evolve into broader Historic Environment Records (HERs) that include information such as historic buildings, parks and gardens, historic aircraft crash sites, etc.

Facial reconstruction is the scientific art of building the face onto the skull for the purposes of individual identification. Scientific art is the application of artistic skills whilst following scientific rules. This procedure has been exercised for over a century and there exist three main techniques:

1. (1) The two-dimensional 2-D artistic representation of the face, usually drawn over a photograph of the skull.

2. (2) Three-dimensional 3-D facial reconstruction using a sculptural technique.

3. (3) Three-dimensional facial reconstruction using computer-generated images.

These techniques share the common principle of relating the skeletal structure to the overlying soft tissue. The technique of superimposition, which has a long history in the forensic arena, is not considered here since it requires photographic evidence of a suspect in order to connect an individual with the unidentified skull (see Iscan & Helmer, 1993; Knight & Whittaker, 1997; Whittaker et al., 1998). The artistic and sculptural reconstruction techniques have been used for recognition in forensic identification investigations worldwide, and these procedures are usually employed when the police do not have a suspect for identification.

Background

The fact that the facial reconstruction procedure exists at all is a reflection of our unlimited fascination with human faces, and this preoccupation has led to a more specific interest in the faces of people from the past. The remains of people are constantly excavated and the desire to discover how those people may have appeared has been seemingly limitless. The history of modelling a face onto a skull is extensive and there are numerous early symbolic examples (see Figs.

Traditionally the skull is the single most studied bone in physical anthropology, and has a complex form that develops under the influences of growth, tension and maturation. The skull is made up of 22 bones (excluding Wormian bones and ear ossicles) consisting of 14 facial bones and 8 cranial bones. It is the most complex part of the skeleton and is of major importance for physical anthropology. Knowledge of common cranial terminology is useful when assessing the skull.

1. The skull is the entire skeletal framework of the head.

2. The mandible is the lower jaw.

3. The cranium is the skull without the mandible.

4. The calvaria is the cranium without the face.

5. The splanchnocranium is the facial skeleton.

6. The neurocranium is the brain case.

7. The Frankfurt Plane is reached when a horizontal line passes through the inferior border of the orbit (orbitale) and the external auditory meatus (porion) on both sides of the skull (see Fig. 3.1).

Figures 3.2 and 3.3 illustrate the position and name of each of the bones of the skull and describe common cranial terms.

There are many personal identification details that can be determined from the skull. The three most important factors are the sex, age and racial origin of the person, and without these determinants it would be nearly impossible to identify the individual. A complete and undamaged skeleton can be assessed with an extremely high level of accuracy for sex (98 per cent), have the age estimated to within five years and be assigned to one of three major racial origin groups (Caucasian, Negroid and Mongoloid).

Knowledge of common morphological terms is necessary when carrying out an assessment of the face. Figs. 4.1 to 4.5 illustrate these facial surface anatomical terms. There has been a long history of research into quantifying the relationship between the skeletal structure of the skull and the overlying soft tissues of the face, with the express purpose of facilitating facial reconstruction. Gerasimov (1971) was convinced that there was a clear correlation between the relief of the skull and the surface of the soft stratum. He claimed that this could be illustrated by the asymmetry of the skull, which is also exhibited in the asymmetry of the face. He clarified this with a photographic study of faces to create totally right-sided and left-sided faces from an original face. He took a frontal-view photograph of a subject and split the photograph on a line that dissected the glabella and the philtrum. He then created two faces by mirror imaging each side and attaching it to its mirror image: one made up of two right sides and one of two left sides. He found for every subject two distinct faces were created: a ‘fine’ face and a ‘rough’ face. He suggested that asymmetry is a basic element of individuality and that since the asymmetry is natural, any reconstruction of the soft tissues will define the character of this asymmetry and secure similarity to the actual face (see Fig. 4.6).

No two faces are alike, not even those of identical twins. Each face is unique. The human face is one of the most important social tools. An enormous variety of communication signals are produced using the face and it governs the expression of emotion, interest, desire and attention. We use our faces to attract, repel, scare, soothe and entertain. The face suggests details such as age, gender, culture, health and ethnic group. It is usually the first part of the body that we notice and the only part that we address. We are each capable of perceiving the smallest variation between faces and it is this ability that allows us to carry out personal recognition and identification. As adults we recognise and differentiate hundreds of faces of our family, friends, colleagues, famous people etc. This is illustrated by our ability to distinguish eventually the faces of identical twins (see Fig. 1.1). Even though the faces of identical twins are remarkably similar and they share the same genetic profile, their faces are in fact slightly different and people who know identical twins very well can distinguish them from one another.

Facial reconstruction is a process whereby the face of an individual is built onto the skull for the purpose of identification. The theory behind facial reconstruction is that in the same way that we all have unique faces, we all have unique skulls, and it is the small variations in the shape, form and proportions of the skull that lead to significant variations in our faces. When I first became involved in facial anthropology, I too had a great deal of difficulty believing that the amount of variation seen in the world's population of faces could also be exhibited in skulls. Even though we are all experts at facial recognition and identification, due to our innate ability to distinguish one face from another, we find it difficult to believe that the skull can provide a detailed map for the face. This must be, in part, due to our inability to distinguish one skull from another in the same way that we can distinguish one face from another. Uninitiated observers will not be able to demonstrate proportional and feature variation between skulls with ease. Since all skulls appear similar in shape and proportions to the inexperienced eye, it is assumed that the information provided by one skull must be virtually the same as that provided by another skull. However, the practised and experienced observer can demonstrate unlimited variation in shape, size, proportion and detail between skulls. I am now convinced: each skull is as individual as each face.