Difference Between Spatial And Geospatial
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Geospatial Analysis
Author: Michael John De Smith
language: en
Publisher: Troubador Publishing
Release Date: 2007
"The Guide has been designed for everyone involved in geospatial analysis, from undergraduate and postgraduate to professional analyst, software engineer and GIS practitioner. It builds upon the spatial analysis topics included in the US National Academies 'Beyond Mapping' and 'Learning to think spatially' agendas, the UK 'Spatial Literacy in Teaching' programme, the NCGIA Core Curriculum and the AAAG/UCGIS Body of Knowledge. As such it provides a valuable reference guide and accompaniment to courses built around these programmes."--Back cover.
Geocomputation with R
Geocomputation with R is for people who want to analyze, visualize and model geographic data with open source software. It is based on R, a statistical programming language that has powerful data processing, visualization, and geospatial capabilities. The book equips you with the knowledge and skills to tackle a wide range of issues manifested in geographic data, including those with scientific, societal, and environmental implications. This book will interest people from many backgrounds, especially Geographic Information Systems (GIS) users interested in applying their domain-specific knowledge in a powerful open source language for data science, and R users interested in extending their skills to handle spatial data. The book is divided into three parts: (I) Foundations, aimed at getting you up-to-speed with geographic data in R, (II) extensions, which covers advanced techniques, and (III) applications to real-world problems. The chapters cover progressively more advanced topics, with early chapters providing strong foundations on which the later chapters build. Part I describes the nature of spatial datasets in R and methods for manipulating them. It also covers geographic data import/export and transforming coordinate reference systems. Part II represents methods that build on these foundations. It covers advanced map making (including web mapping), "bridges" to GIS, sharing reproducible code, and how to do cross-validation in the presence of spatial autocorrelation. Part III applies the knowledge gained to tackle real-world problems, including representing and modeling transport systems, finding optimal locations for stores or services, and ecological modeling. Exercises at the end of each chapter give you the skills needed to tackle a range of geospatial problems. Solutions for each chapter and supplementary materials providing extended examples are available at https://geocompr.github.io/geocompkg/articles/.
Historical GIS
Author: Ian N. Gregory
language: en
Publisher: Cambridge University Press
Release Date: 2007-12-13
Historical GIS is an emerging field that uses Geographical Information Systems (GIS) to research the geographies of the past. Ian Gregory and Paul Ell's study, first published in 2007, comprehensively defines this field, 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 and rejuvenate historical research through 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 where GIS has been used to enhance research debates. The result is a clear agenda charting how GIS will develop as one of the most important approaches to scholarship in historical geography.