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| exploratory regression arcgis: Spatial Analytics with ArcGIS Eric Pimpler, 2017-04-26 Pattern Analysis and cluster mapping made easy About This Book Analyze patterns, clusters, and spatial relationships using ArcGIS tools Get up to speed in R programming to create custom tools for analysis Sift through tons of crime and real estate data and analyze it using the tools built in the book Who This Book Is For This book is for ArcGIS developers who want to perform complex geographic analysis through the use of spatial statistics tools including ArcGIS and R. No knowledge of R is assumed. What You Will Learn Get to know how to measure geographic distributions Perform clustering analysis including hot spot and outlier analysis Conduct data conversion tasks using the Utilities toolset Understand how to use the tools provided by the Mapping Clusters toolset in the Spatial Statistics Toolbox Get to grips with the basics of R for performing spatial statistical programming Create custom ArcGIS tools with R and ArcGIS Bridge Understand the application of Spatial Statistics tools and the R programming language through case studies In Detail Spatial statistics has the potential to provide insight that is not otherwise available through traditional GIS tools. This book is designed to introduce you to the use of spatial statistics so you can solve complex geographic analysis. The book begins by introducing you to the many spatial statistics tools available in ArcGIS. You will learn how to analyze patterns, map clusters, and model spatial relationships with these tools. Further on, you will explore how to extend the spatial statistics tools currently available in ArcGIS, and use the R programming language to create custom tools in ArcGIS through the ArcGIS Bridge using real-world examples. At the end of the book, you will be presented with two exciting case studies where you will be able to practically apply all your learning to analyze and gain insights into real estate data. Style and approach Filled with live examples that you can code along with, this book will show you different methods and techniques to effectively analyze spatial data with ArcGIS and the R language. The exciting case studies at the end will help you immediately put your learning to practice. |
| exploratory regression arcgis: Spatial Analysis Methods and Practice George Grekousis, 2020-06-11 An introductory overview of spatial analysis and statistics through GIS, including worked examples and critical analysis of results. |
| exploratory regression arcgis: Geographically Weighted Regression A. Stewart Fotheringham, Chris Brunsdon, Martin Charlton, 2003-02-21 Geographical Weighted Regression (GWR) is a new local modelling technique for analysing spatial analysis. This technique allows local as opposed to global models of relationships to be measured and mapped. This is the first and only book on this technique, offering comprehensive coverage on this new 'hot' topic in spatial analysis. * Provides step-by-step examples of how to use the GWR model using data sets and examples on issues such as house price determinants, educational attainment levels and school performance statistics * Contains a broad discussion of and basic concepts on GWR through to ideas on statistical inference for GWR models * uniquely features accompanying author-written software that allows users to undertake sophisticated and complex forms of GWR within a user-friendly, Windows-based, front-end (see book for details). |
| exploratory regression arcgis: Geospatial Data Analytics and Urban Applications Sandeep Narayan Kundu, 2022-01-03 This book highlights advanced applications of geospatial data analytics to address real-world issues in urban society. With a connected world, we are generating spatial at unprecedented rates which can be harnessed for insightful analytics which define the way we analyze past events and define the future directions. This book is an anthology of applications of spatial data and analytics performed on them for gaining insights which can be used for problem solving in an urban setting. Each chapter is contributed by spatially aware data scientists in the making who present spatial perspectives drawn on spatial big data. The book shall benefit mature researchers and student alike to discourse a variety of urban applications which display the use of machine learning algorithms on spatial big data for real-world problem solving. |
| exploratory regression arcgis: Using ArcGIS Geostatistical Analyst Kevin Johnston, Environmental Systems Research Institute (Redlands, Calif.), 2001 |
| exploratory regression arcgis: GIS and Geocomputation for Water Resource Science and Engineering Barnali Dixon, Venkatesh Uddameri, 2016-02-08 GIS and Geocomputation for Water Resource Science and Engineering not only provides a comprehensive introduction to the fundamentals of geographic information systems but also demonstrates how GIS and mathematical models can be integrated to develop spatial decision support systems to support water resources planning, management and engineering. The book uses a hands-on active learning approach to introduce fundamental concepts and numerous case-studies are provided to reinforce learning and demonstrate practical aspects. The benefits and challenges of using GIS in environmental and water resources fields are clearly tackled in this book, demonstrating how these technologies can be used to harness increasingly available digital data to develop spatially-oriented sustainable solutions. In addition to providing a strong grounding on fundamentals, the book also demonstrates how GIS can be combined with traditional physics-based and statistical models as well as information-theoretic tools like neural networks and fuzzy set theory. |
| exploratory regression arcgis: Using ArcGIS Spatial Analyst Steve Kopp, Jill McCoy, Kevin Johnston, Environmental Systems Research Institute (Redlands, Calif.), 2001 |
| exploratory regression arcgis: Handbook of Applied Spatial Analysis Manfred M. Fischer, Arthur Getis, 2009-12-24 The Handbook is written for academics, researchers, practitioners and advanced graduate students. It has been designed to be read by those new or starting out in the field of spatial analysis as well as by those who are already familiar with the field. The chapters have been written in such a way that readers who are new to the field will gain important overview and insight. At the same time, those readers who are already practitioners in the field will gain through the advanced and/or updated tools and new materials and state-of-the-art developments included. This volume provides an accounting of the diversity of current and emergent approaches, not available elsewhere despite the many excellent journals and te- books that exist. Most of the chapters are original, some few are reprints from the Journal of Geographical Systems, Geographical Analysis, The Review of Regional Studies and Letters of Spatial and Resource Sciences. We let our contributors - velop, from their particular perspective and insights, their own strategies for m- ping the part of terrain for which they were responsible. As the chapters were submitted, we became the first consumers of the project we had initiated. We gained from depth, breadth and distinctiveness of our contributors’ insights and, in particular, the presence of links between them. |
| exploratory regression arcgis: Archaeological Spatial Analysis Mark Gillings, Piraye Hacıgüzeller, Gary Lock, 2020-01-16 Effective spatial analysis is an essential element of archaeological research; this book is a unique guide to choosing the appropriate technique, applying it correctly and understanding its implications both theoretically and practically. Focusing upon the key techniques used in archaeological spatial analysis, this book provides the authoritative, yet accessible, methodological guide to the subject which has thus far been missing from the corpus. Each chapter tackles a specific technique or application area and follows a clear and coherent structure. First is a richly referenced introduction to the particular technique, followed by a detailed description of the methodology, then an archaeological case study to illustrate the application of the technique, and conclusions that point to the implications and potential of the technique within archaeology. The book is designed to function as the main textbook for archaeological spatial analysis courses at undergraduate and post-graduate level, while its user-friendly structure makes it also suitable for self-learning by archaeology students as well as researchers and professionals. |
| exploratory regression arcgis: Multidimensional Approach to Quality of Life Issues Braj Raj Kumar Sinha, 2019-08-27 This comprehensive volume provides a broad overview of quality of life issues covering a wide geographical region: North America, Europe, parts of Africa, East Asia, and South Asia. Spread over more than 25 chapters, it includes the latest findings from these regions to provide a multidisciplinary account of the major dimensions of quality of life, and therefore has a vast scope. The volume is divided into four thematic parts: theoretical dimension; Demographic dimension; socio-cultural and economic dimensions; and urban and environment related dimensions. Extensive maps, diagrams and tables accompany the discussions and facilitate understanding. This is an indispensable reference and serves the interest of students and scholars of human geography, economics, demography, sociology, anthropology, social work, and philosophy. It is particularly useful for those engaged in further research on quality of life issues. |
| exploratory regression arcgis: Sustainable Smart Cities and Smart Villages Research Miltiadis D. Lytras, Anna Visvizi, 2018-10-19 This book is a printed edition of the Special Issue Sustainable Smart Cities and Smart Villages Research that was published in Sustainability |
| exploratory regression arcgis: Handbook of Archaeological Sciences A. Mark Pollard, Ruth Ann Armitage, Cheryl A. Makarewicz, 2023-02-09 HANDBOOK OF ARCHAEOLOGICAL SCIENCES A modern and comprehensive introduction to methods and techniques in archaeology In the newly revised Second Edition of the Handbook of Archaeological Sciences, a team of more than 100 researchers delivers a comprehensive and accessible overview of modern methods used in the archaeological sciences. The book covers all relevant approaches to obtaining and analyzing archaeological data, including dating methods, quaternary paleoenvironments, human bioarchaeology, biomolecular archaeology and archaeogenetics, resource exploitation, archaeological prospection, and assessing the decay and conservation of specimens. Overview chapters introduce readers to the relevance of each area, followed by contributions from leading experts that provide detailed technical knowledge and application examples. Readers will also find: A thorough introduction to human bioarchaeology, including hominin evolution and paleopathology The use of biomolecular analysis to characterize past environments Novel approaches to the analysis of archaeological materials that shed new light on early human lifestyles and societies In-depth explorations of the statistical and computational methods relevant to archaeology Perfect for graduate and advanced undergraduate students of archaeology, the Handbook of Archaeological Sciences will also earn a prominent place in the libraries of researchers and professionals with an interest in the geological, biological, and genetic basis of archaeological studies. |
| exploratory regression arcgis: Disaster and Emergency Management Methods Jason D. Rivera, 2021-07-27 Find the answers to disaster and emergency management research questions with Disaster and Emergency Management Methods. Written to engage students and to provide a flexible foundation for instructors and practitioners, this interdisciplinary textbook provides a holistic understanding of disaster and emergency management research methods used in the field. The disaster and emergency management contexts have a host of challenges that affect the research process that subsequently shape methodological approaches, data quality, analysis and inferences. In this book, readers are presented with the considerations that must be made before engaging in the research process, in addition to a variety of qualitative and quantitative methodological approaches that are currently being used in the discipline. Current, relevant, and fascinating real-world applications provide a window into how each approach is being applied in the field. Disaster and Emergency Management Methods serves as an effective way to empower readers to approach their own study of disaster and emergency management research methods with confidence. |
| exploratory regression arcgis: Spatial Regression Models for the Social Sciences Guangqing Chi, Jun Zhu, 2019-03-06 Spatial Regression Models for the Social Sciences shows researchers and students how to work with spatial data without the need for advanced mathematical statistics. Focusing on the methods that are commonly used by social scientists, Guangqing Chi and Jun Zhu explain what each method is and when and how to apply it by connecting it to social science research topics. Throughout the book they use the same social science example to demonstrate applications of each method and what the results can tell us. |
| exploratory regression arcgis: Spatial Statistics and Geostatistics Yongwan Chun, Daniel A Griffith, 2013-01-11 Ideal for anyone who wishes to gain a practical understanding of spatial statistics and geostatistics. Difficult concepts are well explained and supported by excellent examples in R code, allowing readers to see how each of the methods is implemented in practice - Professor Tao Cheng, University College London Focusing specifically on spatial statistics and including components for ArcGIS, R, SAS and WinBUGS, this book illustrates the use of basic spatial statistics and geostatistics, as well as the spatial filtering techniques used in all relevant programs and software. It explains and demonstrates techniques in: spatial sampling spatial autocorrelation local statistics spatial interpolation in two-dimensions advanced topics including Bayesian methods, Monte Carlo simulation, error and uncertainty. It is a systematic overview of the fundamental spatial statistical methods used by applied researchers in geography, environmental science, health and epidemiology, population and demography, and planning. A companion website includes digital R code for implementing the analyses in specific chapters and relevant data sets to run the R codes. |
| exploratory regression arcgis: Learning ArcGIS Pro 2 Tripp Corbin, 2020-07-24 Create 2D maps and 3D scenes, analyze GIS data, and share your results with the GIS community using the latest ArcGIS Pro 2 features Key FeaturesGet up to speed with the new ribbon-based user interface, projects, models, and common workflows in ArcGIS Pro 2Learn how to visualize, maintain, and analyze GIS dataAutomate analysis and processes with ModelBuilder and Python scriptsBook Description Armed with powerful tools to visualize, maintain, and analyze data, ArcGIS Pro 2 is Esri's newest desktop geographic information system (GIS) application that uses the modern ribbon interface and a 64-bit processor to make using GIS faster and more efficient. This second edition of Learning ArcGIS Pro will show you how you can use this powerful desktop GIS application to create maps, perform spatial analysis, and maintain data. The book begins by showing you how to install ArcGIS and listing the software and hardware prerequisites. You’ll then understand the concept of named user licensing and learn how to navigate the new ribbon interface to leverage the power of ArcGIS Pro for managing geospatial data. Once you’ve got to grips with the new interface, you’ll build your first GIS project and understand how to use the different project resources available. The book shows you how to create 2D and 3D maps by adding layers and setting and managing the symbology and labeling. You’ll also discover how to use the analysis tool to visualize geospatial data. In later chapters, you’ll be introduced to Arcade, the new lightweight expression language for ArcGIS, and then advance to creating complex labels using Arcade expressions. Finally, you'll use Python scripts to automate and standardize tasks and models in ArcGIS Pro. By the end of this ArcGIS Pro book, you’ll have developed the core skills needed for using ArcGIS Pro 2.x competently. What you will learnNavigate the user interface to create maps, perform analysis, and manage dataDisplay data based on discrete attribute values or range of valuesLabel features on a GIS map based on one or more attributes using ArcadeCreate map books using the map series functionalityShare ArcGIS Pro maps, projects, and data with other GIS community membersExplore the most used geoprocessing tools for performing spatial analysisCreate Tasks based on common workflows to standardize processesAutomate processes using ModelBuilder and Python scriptsWho this book is for If you want to learn ArcGIS Pro to create maps and, edit and analyze geospatial data, this ArcGIS book is for you. No knowledge of GIS fundamentals or experience with any GIS tool or ArcGIS software suite is required. Basic Windows skills, such as navigating and file management, are all you need. |
| exploratory regression arcgis: An Introduction to R for Spatial Analysis and Mapping Chris Brunsdon, Lex Comber, 2014-04-30 In an age of big data, data journalism and with a wealth of quantitative information around us, it is not enough for students to be taught only 100 year old statistical methods using ′out of the box′ software. They need to have 21st-century analytical skills too. This is an excellent and student-friendly text from two of the world leaders in the teaching and development of spatial analysis. It shows clearly why the open source software R is not just an alternative to commercial GIS, it may actually be the better choice for mapping, analysis and for replicable research. Providing practical tips as well as fully working code, this is a practical ′how to′ guide ideal for undergraduates as well as those using R for the first time. It will be required reading on my own courses. - Richard Harris, Professor of Quantitative Social Science, University of Bristol R is a powerful open source computing tool that supports geographical analysis and mapping for the many geography and ‘non-geography’ students and researchers interested in spatial analysis and mapping. This book provides an introduction to the use of R for spatial statistical analysis, geocomputation and the analysis of geographical information for researchers collecting and using data with location attached, largely through increased GPS functionality. Brunsdon and Comber take readers from ‘zero to hero’ in spatial analysis and mapping through functions they have developed and compiled into R packages. This enables practical R applications in GIS, spatial analyses, spatial statistics, mapping, and web-scraping. Each chapter includes: Example data and commands for exploring it Scripts and coding to exemplify specific functionality Advice for developing greater understanding - through functions such as locator(), View(), and alternative coding to achieve the same ends Self-contained exercises for students to work through Embedded code within the descriptive text. This is a definitive ′how to′ that takes students - of any discipline - from coding to actual applications and uses of R. |
| exploratory regression arcgis: Practicing Health Geography Prestige Tatenda Makanga, 2021-05-05 This volume uniquely presents case studies on health geography in Africa, and analyzes health practices in different African regions to illustrate a unified perspective to the geographies of health. The book describes various contemporary and traditional themes that have characterized the discipline of health geography, and uses its 13 case studies across 14 chapters to challenge the perceived dichotomy between health geography and medical geography among health researchers and practitioners. In 3 sections, the book provides readers with a comprehensive and interdisciplinary approach to understanding health geography in Africa. The first chapter introduces the major theories and perspectives in health geography, and how these characteristics apply to health geography practices in Africa. Section 1 discusses the different uses of space-based analyses in health geography, including geo-data infrastructures, geographies of disease burden, spatial epidemiology, spatially precise public health, and spatial access to health. Section 2 discusses the different uses of place-based analyses in health geography, including health representation, healthcare access, food allergies, and health determinants. Section 3 addresses how geography is incorporated into decision processes in Africa, and how policy planning shapes health-related interventions at the population and individual level. The case studies here discuss geo-enabling health records, health policy, public health planning, and mobile health geographies. |
| exploratory regression arcgis: Spatial Regression Analysis Using Eigenvector Spatial Filtering Daniel Griffith, Yongwan Chun, Bin Li, 2019-09-14 Spatial Regression Analysis Using Eigenvector Spatial Filtering provides theoretical foundations and guides practical implementation of the Moran eigenvector spatial filtering (MESF) technique. MESF is a novel and powerful spatial statistical methodology that allows spatial scientists to account for spatial autocorrelation in their georeferenced data analyses. Its appeal is in its simplicity, yet its implementation drawbacks include serious complexities associated with constructing an eigenvector spatial filter. This book discusses MESF specifications for various intermediate-level topics, including spatially varying coefficients models, (non) linear mixed models, local spatial autocorrelation, space-time models, and spatial interaction models. Spatial Regression Analysis Using Eigenvector Spatial Filtering is accompanied by sample R codes and a Windows application with illustrative datasets so that readers can replicate the examples in the book and apply the methodology to their own application projects. It also includes a Foreword by Pierre Legendre. - Reviews the uses of ESF across linear regression, generalized linear regression, spatial autocorrelation measurement, and spatially varying coefficient models - Includes computer code and template datasets for further modeling - Provides comprehensive coverage of related concepts in spatial data analysis and spatial statistics |
| exploratory regression arcgis: Learning ArcGIS Pro Tripp Corbin, GISP, 2015-12-04 Create, analyze, maintain, and share 2D and 3D maps with the powerful tools of ArcGIS Pro About This Book Visualize GIS data in 2D and 3D maps Create GIS projects for quick and easy access to data, maps, and analysis tools A practical guide that helps to import maps, globes, and scenes from ArcMap, ArcScene, or ArcGlobe Who This Book Is For This book is for anyone wishing to learn how ArcGIS Pro can be used to create maps and perform geospatial analysis. It will be especially helpful for those that have used ArcMap and ArcCatalog in the past and are looking to migrate to Esri's newest desktop GIS solution. Though previous GIS experience is not required, you must have a solid foundation using Microsoft Windows. It is also helpful if you understand how to manage folders and files within the Microsoft Windows environment. What You Will Learn Install ArcGIS Pro and assign Licenses to users in your organization Navigate and use the ArcGIS Pro ribbon interface to create maps and perform analysis Create and manage ArcGIS Pro GIS Projects Create 2D and 3D maps to visualize and analyze data Author map layouts using cartographic tools and best practices to show off the results of your analysis and maps Import existing map documents, scenes, and globes into your new ArcGIS Pro projects quickly Create standardized workflows using Tasks Automate analysis and processes using ModelBuilder and Python In Detail ArcGIS Pro is Esri's newest desktop GIS application with powerful tools for visualizing, maintaining, and analyzing data. ArcGIS Pro makes use of the modern ribbon interface and 64-bit processing to increase the speed and efficiency of using GIS. It allows users to create amazing maps in both 2D and 3D quickly and easily. This book will take you from software installation to performing geospatial analysis. It is packed with how-to's for a host of commonly-performed tasks. You will start by learning how to download and install the software including hardware limitations and recommendations. Then you are exposed to the new Ribbon interface and how its smart design can make finding tools easier. After you are exposed to the new interface, you are walked through the steps to create a new GIS Project to provide quick access to project resources. With a project created, you will learn how to construct 2D and 3D maps including how to add layers, adjust symbology, and control labeling. Next you will learn how to access and use analysis tools to help you answer real-world questions. Lastly, you will learn how processes can be automated and standardized in ArcGIS Pro using Tasks, Models, and Python Scripts. This book will provide an invaluable resource for all those seeking to use ArcGIS Pro as their primary GIS application or for those looking to migrate from ArcMap and ArcCatalog. Style and approach This book includes detailed explanations of the GIS functionality and workflows in ArcGIS Pro. These are supported by easy-to-follow exercises that will help you gain an understanding of how to use ArcGIS Pro to perform a range of tasks. |
| exploratory regression arcgis: Applied Spatial Data Analysis with R Roger S. Bivand, Edzer Pebesma, Virgilio Gómez-Rubio, 2013-06-21 Applied Spatial Data Analysis with R, second edition, is divided into two basic parts, the first presenting R packages, functions, classes and methods for handling spatial data. This part is of interest to users who need to access and visualise spatial data. Data import and export for many file formats for spatial data are covered in detail, as is the interface between R and the open source GRASS GIS and the handling of spatio-temporal data. The second part showcases more specialised kinds of spatial data analysis, including spatial point pattern analysis, interpolation and geostatistics, areal data analysis and disease mapping. The coverage of methods of spatial data analysis ranges from standard techniques to new developments, and the examples used are largely taken from the spatial statistics literature. All the examples can be run using R contributed packages available from the CRAN website, with code and additional data sets from the book's own website. Compared to the first edition, the second edition covers the more systematic approach towards handling spatial data in R, as well as a number of important and widely used CRAN packages that have appeared since the first edition. This book will be of interest to researchers who intend to use R to handle, visualise, and analyse spatial data. It will also be of interest to spatial data analysts who do not use R, but who are interested in practical aspects of implementing software for spatial data analysis. It is a suitable companion book for introductory spatial statistics courses and for applied methods courses in a wide range of subjects using spatial data, including human and physical geography, geographical information science and geoinformatics, the environmental sciences, ecology, public health and disease control, economics, public administration and political science. The book has a website where complete code examples, data sets, and other support material may be found: http://www.asdar-book.org. The authors have taken part in writing and maintaining software for spatial data handling and analysis with R in concert since 2003. |
| exploratory regression arcgis: Geospatial Analysis Michael John De Smith, Michael F. Goodchild, Paul Longley, 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. |
| exploratory regression arcgis: Geospace Observation of Natural Hazards Dimitar Ouzounov, Jann-Yenq Liu, Patrick Timothy Taylor, Katsumi Hattori, 2022-02-25 |
| exploratory regression arcgis: Statistical Analysis of Geographic Information with ArcView GIS and ArcGIS David Wing-Shun Wong, Jay Lee, 2005 |
| exploratory regression arcgis: Encyclopedia of GIS Shashi Shekhar, Hui Xiong, 2007-12-12 The Encyclopedia of GIS provides a comprehensive and authoritative guide, contributed by experts and peer-reviewed for accuracy, and alphabetically arranged for convenient access. The entries explain key software and processes used by geographers and computational scientists. Major overviews are provided for nearly 200 topics: Geoinformatics, Spatial Cognition, and Location-Based Services and more. Shorter entries define specific terms and concepts. The reference will be published as a print volume with abundant black and white art, and simultaneously as an XML online reference with hyperlinked citations, cross-references, four-color art, links to web-based maps, and other interactive features. |
| exploratory regression arcgis: Programming Arcgis Pro With Python Eric Pimpler, 2017-11-03 This hands on exercise book starts with an overview of the Python 3.x language. You'll learn the basic constructs of this powerful, easy to learn language for automating your ArcGIS Pro geoprocessing tasks. You'll also learn how to install, configure, and write scripts using the popular PyCharm development environment. We'll then dive into the details of the ArcGIS Pro arcpy module by learning how to execute geoprocessing tools from your scripts. From there you'll learn how to manage project and layer files, and manage the data within those files. You'll discover how to programmatically add, insert, remove, and move layers in table of contents. Next, you'll learn how to apply symbology and update properties of layers, work with 2D and 3D display properties, and manage layouts. You'll also learn how to automate map production through the use of map series functionality, formerly called map books. The later part of the books covers attribute and spatial queries, and the creation of selection sets for feature classes and tables along with the arcpy data access module for insert, updating, and deleting data from feature classes and tables. Finally, we'll close the book by discovering how you can create your own custom geoprocessing tools using custom toolboxes with ArcGIS Pro and Python. |
| exploratory regression arcgis: ArcGIS 9 Jill McCoy, 2004 This book is an excellent reference for users of ESRI ArcGIS Spatial Analyst, one of the extensions to the ArcGIS Desktop products ArcInfo, ArcEditor, and ArcView. ArcGIS Spatial Analyst lets ArcGIS Desktop users create, query, and analyze cell-based raster maps; derive new information from existing data; query information across multiple data layers; and fully integrate cell-based raster data with traditional vector data sources. ArcGIS Spatial Analyst helps you answer questions such as How steep is it in a certain location? or What is the least-cost path from point A to point B? Begin with the quick-start tutorial for an overview of performing spatial analysis using the functions of ArcGIS Spatial Analyst. If you prefer, jump right in and experiment on your own. The book also includes concise, step-by-step, fully illustrated examples. |
| exploratory regression arcgis: Spatial Analysis of Coastal Environments Sarah M. Hamylton, 2017-04-13 This book covers the spatial analytical tools needed to map, monitor and explain or predict coastal features, with accompanying online exercises. |
| exploratory regression arcgis: Spatial Econometrics using Microdata Jean Dubé, Diègo Legros, 2014-11-10 This book provides an introduction to spatial analyses concerning disaggregated (or micro) spatial data. Particular emphasis is put on spatial data compilation and the structuring of the connections between the observations. Descriptive analysis methods of spatial data are presented in order to identify and measure the spatial, global and local dependency. The authors then focus on autoregressive spatial models, to control the problem of spatial dependency between the residues of a basic linear statistical model, thereby contravening one of the basic hypotheses of the ordinary least squares approach. This book is a popularized reference for students looking to work with spatialized data, but who do not have the advanced statistical theoretical basics. |
| exploratory regression arcgis: Spatial Data Analysis Robert P. Haining, 2003-04-17 Spatial Data Analysis: Theory and Practice, first published in 2003, provides a broad ranging treatment of the field of spatial data analysis. It begins with an overview of spatial data analysis and the importance of location (place, context and space) in scientific and policy related research. Covering fundamental problems concerning how attributes in geographical space are represented to the latest methods of exploratory spatial data analysis and spatial modeling, it is designed to take the reader through the key areas that underpin the analysis of spatial data, providing a platform from which to view and critically appreciate many of the key areas of the field. Parts of the text are accessible to undergraduate and master's level students, but it also contains sufficient challenging material that it will be of interest to geographers, social and economic scientists, environmental scientists and statisticians, whose research takes them into the area of spatial analysis. |
| exploratory regression arcgis: Point Pattern Analysis Barry N. Boots, Arthur Getis, 1988-03 Boots and Getis provide a concise explanation of point pattern analysis - a series of techniques for identifying patterns of clustering or regularity in a set of geographical locations. They discuss quadrat and distance methods of measurement, and consider the problems associated with these methods. The authors also outline and compare other measures of arrangement, suggesting when these techniques should be used. |
| exploratory regression arcgis: Micro-Place Homicide Patterns in Chicago Andrew P. Wheeler, Christopher R. Herrmann, Richard L. Block, 2020-12-10 This brief examines 36,263 homicides in Chicago over a 53-year study period, 1965 through 2017, at micro place grid cells of 150 by 150 meters. This study shows not only long-term historical patterns of homicides in Chicago, but also places that historical context of homicide in reference to the dramatic increases in homicides in 2016-2017. It uses several different inequality metrics, as well as kernel density maps to demonstrate that homicides were more clustered in the 1960’s compared to later periods. Using zero inflated group-based trajectory models, it demonstrates the long-term temporal stability of homicides at micro places. This brief will be of interest to researchers in policing, homicide, and research methods in criminology. |
| exploratory regression arcgis: Geographic Information Systems, Spatial Modelling and Policy Evaluation Manfred M. Fischer, Peter Nijkamp, 2012-12-06 Geographical Information Systems (GIS) provide an enhanced environment for spatial data processing. The ability of geographic information systems to handle and analyse spatially referenced data may be seen as a major characteristic which distinguishes GIS from information systems developed to serve the needs of business data processing as well as from CAD systems or other systems whose primary objective is map production. This book, which contains contributions from a wide-ranging group of international scholars, demonstrates the progress which has been achieved so far at the interface of GIS technology and spatial analysis and planning. The various contributions bring together theoretical and conceptual, technical and applied issues. Topics covered include the design and use of GIS and spatial models, AI tools for spatial modelling in GIS, spatial statistical analysis and GIS, GIS and dynamic modelling, GIS in urban planning and policy making, information systems for policy evaluation, and spatial decision support systems. |
| exploratory regression arcgis: Spatial Analysis And GIS S Fotheringham, Peter Rogerson, 2013-04-08 Geographic information systems represent an exciting and rapidly expanding technology via which spatial data may be captured, stored, retrieved, displayed, manipulated and analysed. Applications of this technology include detailed inventories of land use parcels. Spatial patterns of disease, geodemographics, environmental management and macroscale inventories of global resources. The impetus for this book is the relative lack of research into the integration of spatial analysis and GIS, and the potential benefits in developing such an integration. From a GIS perspective, there is an increasing demand for systems that do something other than display and organize data. From a spatial analytical perspective, there are advantages to linking statistical methods and mathematical models to the database and display capabilities of a GIS. Although the GIS may not be absolutely necessary for spatial analysis, it can facilitate such an analysis and moreover provide insights that might otherwise have been missed. The contributions to the book tell us where we are and where we ought to be going. It suggests that the integration of spatial analysis and GIS will stimulate interest in quantitative spatial science, particularly exploratory and visual types of analysis and represents a unique statement of the state-of-the-art issues in integration and interface. |
| exploratory regression arcgis: The Spatial Dimension of Risk Detlef Muller-Mahn, 2012-11-27 Through its exploration of the spatial dimension of risk, this book offers a brand new approach to theorizing risk, and significant improvements in how to manage, tolerate and take risks. A broad range of risks are examined, including natural hazards, climate change, political violence, and state failure. Case studies range from the Congo to Central Asia, from tsunami in Japan and civil war affected areas in Sri Lanka to avalanche hazards in Austria. In each of these cases, the authors examine the importance and role of space in the causes and differentiation of risk, in how we can conceptualize risk from a spatial perspective and in the relevance of space and locality for risk governance. This new approach – endorsed by Ragnar Löfstedt and Ortwin Renn, two of the world's leading and most prolific risk analysts – is essential reading for those charged with studying, anticipating and managing risks. |
| exploratory regression arcgis: Information Criteria and Statistical Modeling Sadanori Konishi, Genshiro Kitagawa, 2008 Statistical modeling is a critical tool in scientific research. This book provides comprehensive explanations of the concepts and philosophy of statistical modeling, together with a wide range of practical and numerical examples. The authors expect this work to be of great value not just to statisticians but also to researchers and practitioners in various fields of research such as information science, computer science, engineering, bioinformatics, economics, marketing and environmental science. It’s a crucial area of study, as statistical models are used to understand phenomena with uncertainty and to determine the structure of complex systems. They’re also used to control such systems, as well as to make reliable predictions in various natural and social science fields. |
| exploratory regression arcgis: Silvicultures Fernando Allende Álvarez, Gillian Gomez-Mediavilla, Nieves López-Estébanez, 2019-06-05 The history and past management of trees within woodlands are the main objectives of this book. The authors show four points of view about one theme: silvicultures. Wood pasture systems of South East England and Northern Italy, Spanish pollard forests, and Portuguese montado are great examples of European ancient forests. Reconstruction of forest ecology, management, protection, and the understanding of these silvicultures from different perspectives are the main values of this monograph. The authors would like to make all readers aware of the value of ancient forests as cultural and socioecosystem services. |
| exploratory regression arcgis: GIS in Public Health Practice Massimo Craglia, Ravi Maheswaran, 2016-04-19 Significant advances in the evaluation and use of geographic information have had a major effect on key elements of public health. Strides in mapping technology as well as the availability and accuracy of health information enable public health practitioners to link and analyze data in new ways at international, regional, and even street levels. Th |
| exploratory regression arcgis: Encyclopedia of Geographic Information Science Karen Kemp, 2008 Geographic information science (GIScience) is an emerging field that combines aspects of many different disciplines. Spatial literacy is rapidly becoming recognized as a new, essential pier of basic education, alongside grammatical, logical and mathematical literacy. By incorporating location as an essential but often overlooked characteristic of what we seek to understand in the natural and built environment, geographic information science (GIScience) and systems (GISystems) provide the conceptual foundation and tools to explore this new frontier. The Encyclopedia of Geographic Information Science covers the essence of this exciting, new, and expanding field in an easily understood but richly detailed style. In addition to contributions from some of the best recognized scholars in GIScience, this volume contains contributions from experts in GIS' supporting disciplines who explore how their disciplinary perspectives are expanded within the context of GIScienceâ€what changes when consideration of location is added, what complexities in analytical procedures are added when we consider objects in 2, 3 or even 4 dimensions, what can we gain by visualizing our analytical results on a map or 3D display? Key Features Brings together GIScience literature that is spread widely across the academic spectrum Offers details about the key foundations of GIScience, no matter what their disciplinary origins Elucidates vocabulary that is an amalgam of all of these fields Key Themes Conceptual Foundations Cartography and Visualization Design Aspects Data Manipulation Data Modeling Geocomputation Geospatial Data Societal Issues Spatial Analysis Organizational and Institutional Aspects The Encyclopedia of Geographic Information Science is an important resource for academic and corporate libraries. |
| exploratory regression arcgis: Comprehensive Geographic Information Systems , 2017-07-21 Geographical Information Systems, Three Volume Set is a computer system used to capture, store, analyze and display information related to positions on the Earth’s surface. It has the ability to show multiple types of information on multiple geographical locations in a single map, enabling users to assess patterns and relationships between different information points, a crucial component for multiple aspects of modern life and industry. This 3-volumes reference provides an up-to date account of this growing discipline through in-depth reviews authored by leading experts in the field. VOLUME EDITORSThomas J. CovaThe University of Utah, Salt Lake City, UT, United StatesMing-Hsiang TsouSan Diego State University, San Diego, CA, United StatesGeorg BarethUniversity of Cologne, Cologne, GermanyChunqiao SongUniversity of California, Los Angeles, CA, United StatesYan SongUniversity of North Carolina at Chapel Hill, Chapel Hill, NC, United StatesKai CaoNational University of Singapore, SingaporeElisabete A. SilvaUniversity of Cambridge, Cambridge, United Kingdom Covers a rapidly expanding discipline, providing readers with a detailed overview of all aspects of geographic information systems, principles and applications Emphasizes the practical, socioeconomic applications of GIS Provides readers with a reliable, one-stop comprehensive guide, saving them time in searching for the information they need from different sources |
EXPLORATORY Definition & Meaning - Merriam-Webster
The meaning of EXPLORATORY is of, relating to, or being exploration. How to use exploratory in a sentence.
EXPLORATORY | English meaning - Cambridge Dictionary
EXPLORATORY definition: 1. done in order to discover more about something: 2. done in order to discover more about…. Learn more.
EXPLORATORY Definition & Meaning - Dictionary.com
Exploratory definition: pertaining to or concerned with exploration.. See examples of EXPLORATORY used in a sentence.
Exploratory - definition of exploratory by The Free Dictionary
exploratory - serving in or intended for exploration or discovery; "an exploratory operation"; "exploratory reconnaissance"; "digging an exploratory well in the Gulf of Mexico"; "exploratory …
exploratory adjective - Definition, pictures, pronunciation and …
Definition of exploratory adjective in Oxford Advanced Learner's Dictionary. Meaning, pronunciation, picture, example sentences, grammar, usage notes, synonyms and more.
EXPLORATORY definition and meaning | Collins English Dictionary
Exploratory actions are done in order to discover something or to learn the truth about something. Exploratory surgery revealed her liver cancer. Two of Britain's biggest rival supermarket …
Exploratory - Definition, Meaning & Synonyms - Vocabulary.com
Whether you’re a teacher or a learner, Vocabulary.com can put you or your class on the path to systematic vocabulary improvement.
exploratory, adj. meanings, etymology and more - Oxford English …
What does the adjective exploratory mean? There are six meanings listed in OED's entry for the adjective exploratory . See ‘Meaning & use’ for definitions, usage, and quotation evidence.
What does exploratory mean? - Definitions.net
Exploratory refers to the act of investigating, examining, or analyzing something in a detailed way to learn more about it, especially when this involves searching for new facts or understanding. …
Exploratory Definition & Meaning - YourDictionary
Serving to explore or investigate. An exploration or investigation. Exploratory work is associated intimately both with prospecting and with development, but the purpose is quite distinct from …
EXPLORATORY Definition & Meaning - Merriam-Webster
The meaning of EXPLORATORY is of, relating to, or being exploration. How to use exploratory in a sentence.
EXPLORATORY | English meaning - Cambridge Dictionary
EXPLORATORY definition: 1. done in order to discover more about something: 2. done in order to discover more about…. Learn more.
EXPLORATORY Definition & Meaning - Dictionary.com
Exploratory definition: pertaining to or concerned with exploration.. See examples of EXPLORATORY used in a sentence.
Exploratory - definition of exploratory by The Free Dictionary
exploratory - serving in or intended for exploration or discovery; "an exploratory operation"; "exploratory reconnaissance"; "digging an exploratory well in the Gulf of Mexico"; "exploratory …
exploratory adjective - Definition, pictures, pronunciation and …
Definition of exploratory adjective in Oxford Advanced Learner's Dictionary. Meaning, pronunciation, picture, example sentences, grammar, usage notes, synonyms and more.
EXPLORATORY definition and meaning | Collins English Dictionary
Exploratory actions are done in order to discover something or to learn the truth about something. Exploratory surgery revealed her liver cancer. Two of Britain's biggest rival supermarket …
Exploratory - Definition, Meaning & Synonyms - Vocabulary.com
Whether you’re a teacher or a learner, Vocabulary.com can put you or your class on the path to systematic vocabulary improvement.
exploratory, adj. meanings, etymology and more - Oxford English …
What does the adjective exploratory mean? There are six meanings listed in OED's entry for the adjective exploratory . See ‘Meaning & use’ for definitions, usage, and quotation evidence.
What does exploratory mean? - Definitions.net
Exploratory refers to the act of investigating, examining, or analyzing something in a detailed way to learn more about it, especially when this involves searching for new facts or understanding. …
Exploratory Definition & Meaning - YourDictionary
Serving to explore or investigate. An exploration or investigation. Exploratory work is associated intimately both with prospecting and with development, but the purpose is quite distinct from …
