Are there geographic clusters of disease cases, or hotspots of crime? Can the geography of air quality be matched to where people hospitalized for respiratory complaints actually live? Spatial data is data about the world where the attribute of interest and its location on the earth's surface are recorded. This comprehensive overview of the subject shows how the above questions can be tackled. It is written for students and researchers in geography, economics, social science, the environmental sciences and statistics.
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Book Description
Spatial data is data about the world where we record both the attribute of interest, and its location on the earth's surface. We need to analyse such data for many reasons. Are there geographic clusters of disease cases, or hotspots of crime? Can we match the geography of air quality to where people hospitalised for respiratory complaints actually live? This first comprehensive overview of the subject shows how such questions can be tackled. It will interest students and researchers in geography, economics, social science, the environmental sciences and statistics.
About the Author
Robert Haining is Professor of Human Geography at the University of Cambridge.
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This book is one of my ever read in the field of Spatial data Analysis. I recommend it for any young researcher, who is trying to understand the matter of spatial Data Analysis.
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Inside This Book
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First Sentence:
Seen from the perspective of the scientist or the policy maker, analytical techniques are a means to an end: for the scientist the development of rigorous, scientifically based understanding of events and processes; for the policy maker the strategic and tactical deployment of resources informed by the application of scientific method and understanding. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
structured random effects, unmeasured predictors, autologistic model, areal partition, conditional autoregressive model, simple kriging weights, positive spatial dependence, simultaneous autoregression, spatial error model, trend surface models, analysing spatial data, exploratory spatial data analysis, exploring spatial data, median polishing, representing spatial variation, burglary data, data incompleteness, areas with small populations, density tracts, spatial data quality, spatial subsets, areal interpolation, specification shift, lung cancer data, spatial analysis methods Key Phrases - Capitalized Phrases (CAPs): (learn more)
Monte Carlo, New York, Greater Manchester, North Carolina, Variables Case New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Seen from the perspective of the scientist or the policy maker, analytical techniques are a means to an end: for the scientist the development of rigorous, scientifically based understanding of events and processes; for the policy maker the strategic and tactical deployment of resources informed by the application of scientific method and understanding. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
structured random effects, unmeasured predictors, autologistic model, areal partition, conditional autoregressive model, simple kriging weights, positive spatial dependence, simultaneous autoregression, spatial error model, trend surface models, analysing spatial data, exploratory spatial data analysis, exploring spatial data, median polishing, representing spatial variation, burglary data, data incompleteness, areas with small populations, density tracts, spatial data quality, spatial subsets, areal interpolation, specification shift, lung cancer data, spatial analysis methods Key Phrases - Capitalized Phrases (CAPs): (learn more)
Monte Carlo, New York, Greater Manchester, North Carolina, Variables Case New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 67
books:
See all 67 books this book cites
5
books
cite this book:
- Elements of Spatial Data Quality (The International Cartographic Association) by Guptill on 4 pages
- The Accuracy Of Spatial Databases by Michael F. Goodchild in Back Matter (1), Back Matter (2), and Back Matter (3)
- New Directions in Spatial Econometrics (Advances in Spatial Science) by Luc Anselin in Back Matter (1), and Back Matter (2)
- The Added Value of Geographical Information Systems in Public and Environmental Health (GeoJournal Library) by M.J. Lepper in Back Matter (1), and Back Matter (2)
- Economic Geography (Critical Concepts in the Social Sciences) by Ronald L. Martin in Back Matter (1), and Back Matter (2)
See all 67 books this book cites
- GIS in Public Health Practice by Massimo Craglia on page 28, and page 148
- GIS-based Studies in the Humanities and Social Sciences by Atsuyuki Okabe on page 263
- Spatial Analysis: A Guide for Ecologists by Marie-Josée Fortin in Back Matter
- GIS for Sustainable Development by Michele Campagna on page 286
- Geographical Information Systems in Archaeology (Cambridge Manuals in Archaeology) by James Conolly in Back Matter
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