Published by Cambridge University Press, 2020
ISBN 10: 1108712932 ISBN 13: 9781108712934
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Published by Cambridge University Press, 2020
ISBN 10: 1108712932 ISBN 13: 9781108712934
Language: English
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Published by Cambridge University Press, 2020
ISBN 10: 1108498981 ISBN 13: 9781108498982
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Published by Cambridge University Press, 2020
ISBN 10: 1108712932 ISBN 13: 9781108712934
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Published by Cambridge University Press, 2020
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ISBN 10: 1108712932 ISBN 13: 9781108712934
Language: English
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Paperback. Condition: new. Paperback. This is an introductory textbook on spatial analysis and spatial statistics through GIS. Each chapter presents methods and metrics, explains how to interpret results, and provides worked examples. Topics include: describing and mapping data through exploratory spatial data analysis; analyzing geographic distributions and point patterns; spatial autocorrelation; spatial clustering; geographically weighted regression and OLS regression; and spatial econometrics. The worked examples link theory to practice through a single real-world case study, with software and illustrated guidance. Exercises are solved twice: first through ArcGIS, and then GeoDa. Through a simple methodological framework the book describes the dataset, explores spatial relations and associations, and builds models. Results are critically interpreted, and the advantages and pitfalls of using various spatial analysis methods are discussed. This is a valuable resource for graduate students and researchers analyzing geospatial data through a spatial analysis lens, including those using GIS in the environmental sciences, geography, and social sciences. This book presents an introductory overview of spatial data analysis methods and geoinformation analysis techniques. Each chapter introduces the related theory, explains how to interpret metrics outputs, and provides worked examples using ArcGIS and GeoDa. This is a valuable resource for graduate students and researchers analyzing geospatial data. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Published by Cambridge University Press, 2020
ISBN 10: 1108712932 ISBN 13: 9781108712934
Language: English
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ISBN 10: 1108712932 ISBN 13: 9781108712934
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Published by Cambridge University Press, 2020
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Add to basketPaperback. Condition: new. Paperback. This is an introductory textbook on spatial analysis and spatial statistics through GIS. Each chapter presents methods and metrics, explains how to interpret results, and provides worked examples. Topics include: describing and mapping data through exploratory spatial data analysis; analyzing geographic distributions and point patterns; spatial autocorrelation; spatial clustering; geographically weighted regression and OLS regression; and spatial econometrics. The worked examples link theory to practice through a single real-world case study, with software and illustrated guidance. Exercises are solved twice: first through ArcGIS, and then GeoDa. Through a simple methodological framework the book describes the dataset, explores spatial relations and associations, and builds models. Results are critically interpreted, and the advantages and pitfalls of using various spatial analysis methods are discussed. This is a valuable resource for graduate students and researchers analyzing geospatial data through a spatial analysis lens, including those using GIS in the environmental sciences, geography, and social sciences. This book presents an introductory overview of spatial data analysis methods and geoinformation analysis techniques. Each chapter introduces the related theory, explains how to interpret metrics outputs, and provides worked examples using ArcGIS and GeoDa. This is a valuable resource for graduate students and researchers analyzing geospatial data. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Published by Cambridge University Press, 2020
ISBN 10: 1108498981 ISBN 13: 9781108498982
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ISBN 10: 1108498981 ISBN 13: 9781108498982
Language: English
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Hardcover. Condition: new. Hardcover. This is an introductory textbook on spatial analysis and spatial statistics through GIS. Each chapter presents methods and metrics, explains how to interpret results, and provides worked examples. Topics include: describing and mapping data through exploratory spatial data analysis; analyzing geographic distributions and point patterns; spatial autocorrelation; spatial clustering; geographically weighted regression and OLS regression; and spatial econometrics. The worked examples link theory to practice through a single real-world case study, with software and illustrated guidance. Exercises are solved twice: first through ArcGIS, and then GeoDa. Through a simple methodological framework the book describes the dataset, explores spatial relations and associations, and builds models. Results are critically interpreted, and the advantages and pitfalls of using various spatial analysis methods are discussed. This is a valuable resource for graduate students and researchers analyzing geospatial data through a spatial analysis lens, including those using GIS in the environmental sciences, geography, and social sciences. This book presents an introductory overview of spatial data analysis methods and geoinformation analysis techniques. Each chapter introduces the related theory, explains how to interpret metrics outputs, and provides worked examples using ArcGIS and GeoDa. This is a valuable resource for graduate students and researchers analyzing geospatial data. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Published by Cambridge University Press, Cambridge, 2020
ISBN 10: 1108712932 ISBN 13: 9781108712934
Language: English
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Add to basketPaperback. Condition: new. Paperback. This is an introductory textbook on spatial analysis and spatial statistics through GIS. Each chapter presents methods and metrics, explains how to interpret results, and provides worked examples. Topics include: describing and mapping data through exploratory spatial data analysis; analyzing geographic distributions and point patterns; spatial autocorrelation; spatial clustering; geographically weighted regression and OLS regression; and spatial econometrics. The worked examples link theory to practice through a single real-world case study, with software and illustrated guidance. Exercises are solved twice: first through ArcGIS, and then GeoDa. Through a simple methodological framework the book describes the dataset, explores spatial relations and associations, and builds models. Results are critically interpreted, and the advantages and pitfalls of using various spatial analysis methods are discussed. This is a valuable resource for graduate students and researchers analyzing geospatial data through a spatial analysis lens, including those using GIS in the environmental sciences, geography, and social sciences. This book presents an introductory overview of spatial data analysis methods and geoinformation analysis techniques. Each chapter introduces the related theory, explains how to interpret metrics outputs, and provides worked examples using ArcGIS and GeoDa. This is a valuable resource for graduate students and researchers analyzing geospatial data. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Published by Cambridge University Press, 2020
ISBN 10: 1108498981 ISBN 13: 9781108498982
Language: English
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Published by Cambridge University Press Jun 2020, 2020
ISBN 10: 1108712932 ISBN 13: 9781108712934
Language: English
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Add to basketTaschenbuch. Condition: Neu. Neuware - An introductory overview of spatial analysis and statistics through GIS, including worked examples and critical analysis of results.