Spatial Analysis Methods and Practice : Describe – Explore – Explain through GIS /

"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...

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Үндсэн зохиолч: Grekousis, George, author 636122
Формат: text
Хэл сонгох:eng
Хэвлэсэн: Cambridge, United Kingdom ; New York, NY : Cambridge University Press, 2020
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author Grekousis, George, author 636122
author_facet Grekousis, George, author 636122
author_sort Grekousis, George, author 636122
collection OCEAN
description "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, 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"--
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spelling KOHA-OAI-TEST:5902532023-01-24T01:24:36ZSpatial Analysis Methods and Practice : Describe – Explore – Explain through GIS / Grekousis, George, author 636122 textCambridge, United Kingdom ; New York, NY : Cambridge University Press,2020©2020eng"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, 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"--Includes bibliographical references and index.1. Think spatially: basic concepts of spatial analysis and space conceptualization -- 2. Exploratory spatial data analysis tools and statistics -- 3. Analyzing geographic distributions and point patterns -- 4. Spatial autocorrelation -- 5. Multivariate data in geography: data reduction and clustering -- 6. Modeling relationships: regression and geographically weighted regression -- 7. Spatial econometrics."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, 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"--PSZ_JBSpatial analysis (Statistics)Geographic information systemsURN:ISBN:9781108498982
spellingShingle Spatial analysis (Statistics)
Geographic information systems
Grekousis, George, author 636122
Spatial Analysis Methods and Practice : Describe – Explore – Explain through GIS /
title Spatial Analysis Methods and Practice : Describe – Explore – Explain through GIS /
title_full Spatial Analysis Methods and Practice : Describe – Explore – Explain through GIS /
title_fullStr Spatial Analysis Methods and Practice : Describe – Explore – Explain through GIS /
title_full_unstemmed Spatial Analysis Methods and Practice : Describe – Explore – Explain through GIS /
title_short Spatial Analysis Methods and Practice : Describe – Explore – Explain through GIS /
title_sort spatial analysis methods and practice describe explore explain through gis
topic Spatial analysis (Statistics)
Geographic information systems
work_keys_str_mv AT grekousisgeorgeauthor636122 spatialanalysismethodsandpracticedescribeexploreexplainthroughgis