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Fitzsimmons, A. R. (1984). Natural Hazards and Land Use Planning: An Annotated Bibliography. Boulder: Natural Hazards Research and Applications Information Centre, University of Colorado.

Golant, S. (1969). Human Behaviour Before the Disaster: A Selected Annotated Bibliography. Boulder: Natural Hazards Research and Applications Information Centre, University of Colorado.

Mitchell, J. K. (1968). A Selected Bibliography of Coastal Erosion, Protection and Related Human Activity in North America and the British Isles. Boulder: Natural Hazards Research and Applications Information Centre, University of Colorado.

Morton, D. R. (1984). A Selected, Partially Annotated Bibliography of Recent (1982–1983) Natural Hazards Publications. Boulder: Natural Hazards Research and Applications Information Centre, University of Colorado.

Morton, D. R (1986). A Selected, Partially Annotated Bibliography of Recent (1984–1985) Natural Hazards Publications. Boulder: Natural Hazards Research and Applications Information Centre, University of Colorado.

Morton, D. R. (1979). Bibliography on Natural Disaster Recovery and Reconstruction. Boulder: Natural Hazards Research and Applications Information Centre, University of Colorado.

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India has witnessed countless disasters in the last hundred years. This book is based on India's 4004 disaster research writings. Towards this goal, the number was neither predetermined nor an end in itself. It is an auto-evolved number. As a destination is to the seeker, so 4004 is to this research. This book is a research on India's disaster research using 4004.

A Veritable Niche

Why be concerned with the research already accomplished in the field? Why not simply get on with research itself? This too is a valid query. Research is perceived and perhaps truly is an intellectual engagement of a higher order. In the realm of academics, one is judged by individual research, not by the work of others. It could also be added that in a world of specialisation, the compilation of research is the forte of another group of professionals. Here, there is need to draw a fine line. Firstly, before knowledge was caged into cubbyholes, it was academia that compiled and interpreted the research in a given field. It remains to be seen what would have been the shades of research had this role sustained itself. Further, research on research is not equivalent to compilation. It also differs from a review of literature. The investigation of any idea or theme demands a reading of the relevant literature which functions as a background to evaluate a specific research objective.

Where does one begin? What is the first step? The library undoubtedly is the finest institution of civilisation. An ideal library is an ocean of published knowledge. World-class libraries exemplify this description. The Library of Congress is the oldest federal cultural institution of the United States of America. It has a collection of more than 130 million items, which includes 29 million books and other printed materials. Taking a walk along its bookshelves spanning over 850 kilometres would be like traversing four times the distance between Delhi and Agra. The library of Princeton University includes nearly 6.2 million books, 36,000 linear feet of manuscripts, and impressive holdings of rare books, prints and archives. The University of Cambridge has a collection of 4.4 million while the Oxford University Library Service holds 11 million items.

Compared to these world-class centres, the libraries in India seem like ponds. The Parliament Library, the largest in Delhi and the second largest in India after the National Library at Kolkata, holds 1.27 million volumes of printed books, reports, government publications, reports, debates, gazettes and other documents. While it would be unfair to compare an ocean with a pond, what is of help is the fact that the two are not isolated. As a hydrological cycle connects a pond, lake and an ocean, such are the currents of globalisation. Today, trade and the Internet allow a larger access to publications than was ever possible.

Before setting out to search for the research many prior decisions had to be taken. There was a need to fix the territory, identify the language of the literature to be surveyed, define the framework of time, and decide the sources that would be tapped. Decisions had to be taken about what to collect, how much to look for, and where to explore. While a roster can be drawn and an itinerary customised, some decisions could only be taken while in the field.

Delimiting the Territory

India was picked as the spatial unit for study. The political map of the world defines the territorial extent of this country as covering an area of 3.29 million square kilometres. Lying entirely in the northern hemisphere, the mainland measures 3214 kilometres from north to south between the latitudes and about 2933 kilometres from east to west between the longitudes. The Indian subcontinent was partitioned in 1947. For ensuring compatibility, the boundaries of present day India were superimposed on the pre-partition map and references to Pakistan or Bangladesh were excluded. Any research that made peripheral or incidental reference to India was omitted. Therefore, works at the global scale or even concerning Asia or South Asia were set aside. The selection was strictly confined to references centred on India.

Selecting the Language

Research can be written and communicated in many languages. Of these, English was singled out as the language for this research.

Can the 4004 light the way towards building a disaster free India? Have they pursued a paradigm which is in sink with the reality of disasters in India? Does the spirit of the 4004 have strength to lever change in the attitude towards disasters? The need is to focus on the role of the 4004. This involves going beyond the thematic classification or that based on type and outlet of research. To move back to the future of 4004 one needs to capture the soul of each reference.

When the 5017 research units were read again with vigilance, this time not for time, type or theme, not even for Indian or foreign, single or multiple author, event or place but for the spirit that guided the work, it indeed was revealing that the ‘natural’ and not the disaster had captured almost the entire attention. A rejoinder to this could be that this research focused on natural disasters and therefore natural would not only belong in the scheme of adjectives but also be the objective. But this is the crux of the discourse.

It is this automatic connection forged between natural and disaster, which nourishes the problem. After all studying a cyclone, earthquake, landslide or storm is not studying a disaster. These are simply natural phenomena, and physical processes that operate on the surface of the Earth. When the world was uninhabited, even then storms, volcanoes and earthquakes occurred freely.

Introduction

Selecting and classifying geospatial data on the basis of their location and attributes starts the process of data exploration, pattern recognition and the interpretation of spatial data. The first part of this chapter examines queries as part of the analytical process in GIS. A query is a formal request for a subset of data based on one or more selection criteria and forms a core function of GIS. The second part of this chapter then considers the subject of classification, which refers to the grouping or placing of data into categories on the basis of shared qualitative or quantitative characteristics. This chapter also discusses methods for the classification of multispectral satellite image data, which is an important process in the interpretation of remotely sensed imagery.

The query

There are three types of query performed in GIS: (i) phenomenal or attribute queries, which question the related non-spatial data tables of spatial objects (e.g. ‘select all sites that have obsidian artefacts’); (ii) topological queries, which question the geometric configuration of an object or relationship between objects (e.g. ‘select all sites within Smith County’); (iii) distance queries, which ask something about the spatial location of objects (e.g. ‘select all sites within 100 km of an obsidian source’).

In Chapter 4 the concept of the relational model was introduced for managing both attribute and spatial datasets. This is the most commonly encountered data structure in GIS.

Introduction

The power of GIS, as with other computer programs, can be deceptive: visually impressive but ultimately meaningless results can appear unassailable because of the sophisticated technologies used to produce them (Eiteljorg 2000). The familiar adage ‘garbage in, garbage out’ is particularly applicable to GIS, and one of our primary aims throughout this book is to provide guidance on how to use this technology in ways to strengthen and extend our understanding of the human past, rather than to obfuscate it. In this chapter we start by providing an overview of the ‘first principles’ of GIS: the software and hardware requirements, geodetic and cartographic principles, and GIS data models. These provide the conceptual building blocks that are essential for understanding what GIS is, how it works, and what its strengths and limitations are. Although some of these ‘first principles’ may be familiar to readers who are experienced in cartography and computer graphics, we nevertheless provide a thorough review of each as they yield the foundation on which we build in later chapters.

The basics

GIS functionality

What does a GIS do? Simply providing a definition of GIS and referring to its abilities to capture and manipulate spatial data doesn't provide much insight into its functionality. More informative is to break some of the basic tasks of a GIS into five groups: data acquisition, spatial data management, database management, data visualisation and spatial analysis.

About this book

The study of geographical information systems (GIS) has now matured to the point where non-specialists can take advantage of relatively user-friendly software to help them solve real archaeological problems. No longer is it the preserve of experts who – in the eyes of cynics – chose their archaeological case studies solely to illustrate solutions to GIS problems. This is, of course, a good thing, because GIS has so much to offer archaeology. Nevertheless, the widespread adoption of GIS brings with it several attendant dangers. The most problematic is that modern GIS packages offer users a variety of powerful tools that are easily applied, without providing much guidance on their appropriateness for the data or questions at hand. For example, many current GIS software packages require just a few mouse clicks to create an elevation model from a set of contour lines, but none that we know of would warn that the application of this method to widely spaced contours is likely to produce highly unsatisfactory results that could lead to a host of interpretative errors further down the line. Conversely, there is a risk that researchers who become overdependent on the data management abilities of GIS may shy away from tackling more analytical questions simply because it is not immediately obvious which buttons to push. It is our ambition that no archaeologist who keeps this manual near his or her computer will make such mistakes, nor be hesitant about tackling the sorts of questions that can only be answered with some of the more advanced tools that GIS packages offer.

Introduction

It is often appropriate to model the spatial organisation of human activity in terms of point locations and the relationships between them; for example the movement of goods between settlements or the intervisibility between forts. This chapter discusses the various network analysis tools that can be used to study such relationships. It also discusses techniques for predicting the likely path of an unknown route between point locations, as well as the flow of water and watersheds.

Given that the bulk of archaeological data is ultimately point based it is surprising that network analysis has not featured more prominently in the archaeological application of GIS. Of course, what is a point at one scale of analysis may be a region at another, and it is thus important to recognise that the applicability of network analysis is determined by the way in which the problem is framed rather than the geographical extent of a particular study. A few published archaeological network analyses have investigated subjects ranging in scale from the colonisation of new territory (Allen 1990; Zubrow 1990) and the location of ‘centres’ (Bell and Church 1985; Mackie 2001) to the connectivity of rooms in individual buildings (Foster 1989). There is no reason why this range could not be extended to even smaller extents: to, for example, investigate patterns of refitting among lithic artefacts in a single stratigraphic unit.