Transactions of the Institute of British Geographers

Introduction Remit of This Book Local Models and Methods What Is Local? Spatial Dependence Spatial Scale Stationarity Spatial Data Models Data Sets Used for Illustrative Purposes A Note on Notation Overview Local Modeling Approaches to Local Adaptation Stratification or Segmentation of Spatial Data Moving Window/Kernel Methods Locally Varying Model Parameters Transforming and Detrending Spatial Data Overview Grid Data Exploring Spatial Variation in Single Variables Global Univariate Statistics Local Univariate Statistics Analysis of Grid Data Moving Windows for Grid Analysis Wavelets Segmentation Analysis of Digital Elevation Models Overview Spatial Relations Spatial Autocorrelation: Global Measures Spatial Autocorrelation: Local Measures Global Regression Local Regression Regression and Spatial Data Spatial Autoregressive Models Multilevel Modeling Allowing for Local Variation in Model Parameters Moving Window Regression (MWR) Geographically Weighted Regression (GWR) Spatially Weighted Classification Overview Spatial Prediction 1: Deterministic Methods Point Interpolation Global Methods Local Methods Areal Interpolation General Approaches: Overlay Local Models and Local Data Limitations: Point and Areal Interpolation Overview Spatial Prediction 2: Geostatistics Random Function Models Stationarity Global Models Exploring Spatial Variation Kriging Equivalence of Splines and Kriging Conditional Simulation The Change of Support Problem Other Approaches Local Approaches: Nonstationary Models Nonstationary Mean Nonstationary Models for Prediction Nonstationary Variogram Variograms in Texture Analysis Summary Point Patterns Point Patterns Visual Examination of Point Patterns Density and Distance Methods Statistical Tests of Point Patterns Global Methods Distance Methods Other Issues Local Methods Density Methods Accounting for the Population at Risk The Local K Function Point Patterns and Detection of Clusters Overview Summary: Local Models for Spatial Analysis Review Key Issues Software Future Developments Summary References Index

http://pcwww.liv.ac.uk/~cdlloyd/LMSA2eExamples12.pdf

Local Models for Spatial Analysis

Differences in the reporting units of data from diverse sources and changes in units over time are common obstacles to analysis of areal data. We compare common approaches to this problem in the context of changes over time in the boundaries of U.S. census tracts. In every decennial census many tracts are split, consolidated, or changed in other ways from the previous boundaries to reflect population growth or decline. We examine two interpolation methods to create a bridge between years, one that relies only on areal weighting and another that also introduces population weights. Results demonstrate that these approaches produce substantially different estimates for variables that involve population counts, but they have a high degree of convergence for variables defined as rates or averages. Finally the paper describes the Longitudinal Tract Data Base (LTDB), through which we are making available public-use tools to implement these methods to create estimates within 2010 tract boundaries for any tract-level data (from the census or other sources) that are available for prior years as early as 1970.

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Interpolating U.S. Decennial Census Tract Data from as Early as 1970 to 2010: A Longtitudinal Tract Database.

John Gerring's exceptional textbook has been thoroughly revised in this second edition. It offers a one-volume introduction to social science methodology relevant to the disciplines of anthropology, economics, history, political science, psychology and sociology. This new edition has been extensively developed with the introduction of new material and a thorough treatment of essential elements such as conceptualization, measurement, causality and research design. It is written for students, long-time practitioners and methodologists and covers both qualitative and quantitative methods. It synthesizes the vast and diverse field of methodology in a way that is clear, concise and comprehensive. While offering a handy overview of the subject, the book is also an argument about how we should conceptualize methodological problems. Thinking about methodology through this lens provides a new framework for understanding work in the social sciences.

Social Science Methodology: A Unified Framework

The last 10 years have seen a sudden rise in interest in the use of Geographical Information Systems (GIS) in historical research. This has led to a field that has become known as `historical GIS'. This development started in the more quantitative ends of the discipline but has spread to encompass qualitative research as well. Interest in historical GIS is not restricted to researchers who would previously have regarded themselves as historical geographers, but has in fact led to an increased awareness of the importance of geography from across the discipline of history. This paper introduces historical GIS and critically evaluates how it is affecting the practice of historical geography.

http://journals.sagepub.com/doi/pdf/10.1177/0309132507081495

Historical GIS: structuring, mapping and analysing geographies of the past

Historical GIS is an emerging field that uses Geographical Information Systems (GIS) to research the geographies of the past. The authors present the first study to define this emerging field comprehensively, exploring all aspects of using GIS in historical research. A GIS is a form of database in which every item of data is linked to a spatial location. This technology offers unparalleled opportunities to add insight to and rejuvenate historical research thought the ability to identify and use the geographical characteristics of data. Historical GIS introduces the basic concepts and tools underpinning GIS technology, describing and critically assessing the visualisation, analytical and e-Science methodologies that it enables, and examining key scholarship in which GIS has been used to enhance research debates. The result is a clear agenda charting how GIS will develop as one the most important approaches to scholarship in historical geography.

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Historical GIS: Technologies, Methodologies, and Scholarship

This book is available from Cambridge University Press at http://www.cambridge.org/uk/catalogue/catalogue.asp?isbn=9780521771559

Rival Jerusalems: The Geography of Victorian Religion

The census and similar sources of data have been published for two centuries so the information that they contain should provide an unparalleled insight into the changing population of Britain over this time period. To date, however, the seemingly trivial problem of changes in boundaries has seriously hampered the use of these sources as they make it impossible to create long run time series of spatially detailed data. The paper reviews methodologies that attempt to resolve this problem by using geographical information systems and areal interpolation to allow the reallocation of data from one set of administrative units onto another. This makes it possible to examine change over time for a standard geography and thus it becomes possible to unlock the spatial detail and the temporal depth that are held in the census and in related sources. © 2005 Royal Statistical Society.

Breaking the boundaries: geographical approaches to integrating 200 years of the census

Historical GIS has the potential to re‐invigorate our use of statistics from historical censuses and related sources. In particular, areal interpolation can be used to create long‐run time‐series of spatially detailed data that will enable us to enhance significantly our understanding of geographical change over periods of a century or more. The difficulty with areal interpolation, however, is that the data that it generates are estimates which will inevitably contain some error. This paper describes a technique that allows the automated identification of possible errors at the level of the individual data values.

Error‐sensitive historical GIS: Identifying areal interpolation errors in time‐series data

Several countries have made large investments in building historical Geographical Information Systems (GIS) databases containing census and other quantitative statistics over long periods of time. Making good use of these databases requires approaches that explore spatial and temporal change. The authors use a variety of visualization and spatial analysis techniques to explore population change in Ireland during and after the Great Famine of the late 1840s. Importantly, the techniques allow differences over space and time to be explored, thus stressing the diversity between places, rather than making all places appear the same, a common criticism of many statistical approaches. The authors demonstrate the potential of these techniques to explore geographical and temporal variations in large quantitative GIS datasets.

Analyzing Spatiotemporal Change by Use of National Historical Geographical Information Systems: Population Change during and after the Great Irish Famine

Paul S. Ell

Papers

Historical GIS: Technologies, Methodologies, and Scholarship

Rival Jerusalems: The Geography of Victorian Religion

Breaking the boundaries: geographical approaches to integrating 200 years of the census

Error‐sensitive historical GIS: Identifying areal interpolation errors in time‐series data

Analyzing Spatiotemporal Change by Use of National Historical Geographical Information Systems: Population Change during and after the Great Irish Famine