Spatial Data Analysis With R
Home > Society and Social Sciences > Sociology and anthropology > Sociology > Population and demography > Spatial Data Analysis With R: (Advanced Quantitative Techniques in the Social Sciences)
Spatial Data Analysis With R: (Advanced Quantitative Techniques in the Social Sciences)

Spatial Data Analysis With R: (Advanced Quantitative Techniques in the Social Sciences)


     0     
5
4
3
2
1



Out of Stock


Notify me when this book is in stock
X
About the Book

This is an introduction for social science students to the growing field of spatial data analysis using the R platform. The text assumes no prior knowledge of either, beyond the contents of an introductory statistics course. It uses the open-source software R, and relevant spatial data analysis packages, to provide practical guidance of how to conduct spatial data analysis with readers′ own data sets. The book first briefly introduces students to R, covers some basic concepts in statistical data analysis, and then focuses on discussing the central ideas of spatial data analysis. All the discussions are supported with R scripts so that students can work on their own and produce results that the book helps interpret. Each chapter ends with review questions to test understanding. The book is suited for upper-level undergraduate social science students and graduate students, and other social scientists who are interested in analyzing their spatial data with R. A companion website for the book can be found on the Resources tab above. It includes R code and data for students to replicate the examples in the book. The password-protected instructor side of the site includes exercises and answers which can be set for homework.

Table of Contents:
Preface Acknowledgments About the Author Chapter 1. The Journey Starts With R 1.1 What Is R, and Why Should We Use R? 1.2 Getting and Familiarizing Yourselves With R 1.3 The Two Companions of R 1.4 Basic Operations in R 1.5 The R Packages 1.6 The R Task Views and Spatial Task View Conclusion Review Questions Chapter 2. Very Basic Concepts of Statistical Data Analysis 2.1 The Concepts of Variable, Random Variable and Variable Distribution, and Degrees of Freedom 2.2 The Concept of Hypothesis Testing 2.3 Exploratory Data Analysis 2.4 Have a Taste of Regression Analysis 2.5 Practices in R Review Questions Chapter 3. Spatial Data is Special: Working With the Complexity of Spatial Data 3.1 Spatial/Geographical/Map Data—Recognize Them 3.2 Spatial Data is Special—Spatial Effects 3.3 Spatial Data Analysis 3.4 Spatial Effects’ Impact on Data Analysis 3.5 Exploratory Spatial Data Analysis 3.6 Quantifying Spatial Autocorrelation—Essence of ESDA 3.7 Practice in R Review Questions Chapter 4. The Concept of Neighbor: Spatial Linkage Matrix and Spatial Weight 4.1 Second Contact: Spatial Autocorrelation 4.2 Spatial Neighbors—Are You My Neighbor? 4.3 Spatial Weight and Spatial Lag Revisit 4.4 Practice in R Review Questions Chapter 5. Global Spatial Autocorrelation 5.1 Third Contact: Spatial Autocorrelation: The Global and Local Versions 5.2 Introducing the Moran’s Index (Coefficient) 5.3 Practice in R Review Questions Chapter 6. Local Spatial Autocorrelation 6.1 Global and Local: What Is Their Relationship 6.2 The Local Moran’s Index 6.3 Global and Local Again: The Moran’s Scatterplot 6.4 Practice in R Review Questions Chapter 7. Spatial Autoregressive Models 7.1 Regression With Spatial Data 7.2 Taxonomy of Spatial Autoregressive Models as Alternative 7.3 Practice in R Review Questions Chapter 8. Eigenfunction-Based Spatial Filtering Regression 8.1 Fourth Contact: Spatial Autocorrelation 8.2 Spatial Autocorrelation as Map Pattern 8.3 Augmented Regression With Spatial Filters as Synthetic Covariates 8.4 Practice in R Review Questions Chapter 9. Introduction to Local Models: Geographically Weighted Regression and Eigenfunction-Based Spatial Filtering Approach 9.1 Global and Local Regression 9.2 Geographically Weighted Regression (GWR) 9.3 Eigenfunction-Based Spatial Filtering Approach to Addressing Spatial Nonstationarity 9.4 Comparison Between GWR and ESF SVC Models 9.5 Practice in R Review Questions Chapter 10. Brief Introduction to Spatial Panel Regression and SVC Panel Regression 10.1 Panel Dataset and Panel Regression 10.2 Spatial Panel Models 10.3 Spatially Varying Coefficient Process With Panel Model 10.4 Practice in R Review Questions Chapter 11. Conclusion 11.1 Journey So Far 11.2 Future Learning Directions Appendix: Answers to Review Questions References Index

About the Author :
Danlin Yu is a distinguished geographic information scientist, spatial data analyst, complex system modeler, and urban public health expert. With a specialization in geographic information and spatial data analysis, Dr. Yu has made significant contributions to the fields of urban remote sensing, cartographical design and presentation, spatial statistical analysis, geocomputation, urban and regional planning, and system dynamic modeling for complex systems. His work is particularly impactful in the realm of urban planning, sustainable development, public health and environmental health, where he applies advanced methodologies to tackle pressing urban challenges. Over nearly two decades of dedicated work in geographic information analysis, Dr. Yu has established himself as a leader in his field. His expertise spans the entire spectrum of spatial analysis, from mapping and statistical analysis to remote sensing data extraction and the development of innovative methodologies. His ability to integrate these diverse skill sets into cohesive and actionable insights has positioned him at the forefront of his discipline. Dr. Yu’s scholarly contributions are both extensive and influential. He has authored and co-authored over 100 peer-reviewed articles in internationally recognized journals, solidifying his reputation as a thought leader in geographic information science and urban studies. In addition, he has contributed to three collaborative books focusing on urban development and urbanization in China, providing critical insights into the complex processes shaping modern cities. His expertise in spatial statistical analysis has been applied across multiple domains, including urban public health, environmental management, and population prediction. His research has significantly advanced the understanding of upstream factors in infectious disease prevention and the causes of urban lead poisoning. Moreover, Dr. Yu’s innovative integration of spatial data analysis, complex system dynamics modeling, advanced machine learning, and big data analytics places him at the cutting edge of research in urban planning, sustainability, and public health. Throughout his career, Dr. Yu has collaborated with leading figures in the field, including spatial economist Dr. Roger Bivand, with whom he co-authored the R package for geographically weighted regression analysis (spgwr). Since 2010, he has been at the forefront of developing a new R package for “geographically weighted panel regression,” showcasing his pioneering contributions to the advancement of spatial analysis techniques. His work continues to influence the future direction of spatial data analysis and its applications in urban environments, making him a pivotal figure in the ongoing dialogue on sustainable urban development and public health.

Review :
This text provides an excellent introduction along with a thorough overview of spatial analysis techniques with R. The book provides a solid framework to move students through a wide variety of models and spatial frameworks for analysis while maintaining a level of accessibility superior to other texts on the subject. With the increasing importance and application of spatial analysis in research, this text is appropriate for a variety of disciplines including the natural sciences and social sciences. The book′s approach to teaching spatial data analysis has the potential to significantly enhance the learning experience in the classroom. The book effectively combines theoretical concepts with practical applications, providing students with the essential skills to translate learning into practice. This is a textbook I would use with my graduate students and doctoral students. This text will help students feel more comfortable with statistics and numbers.


Best Sellers


Product Details
  • ISBN-13: 9781071862384
  • Publisher: Sage Publications Inc Ebooks
  • Publisher Imprint: SAGE Publications Inc
  • Language: English
  • ISBN-10: 1071862383
  • Publisher Date: 11 Mar 2025
  • Binding: Digital download and online
  • Series Title: Advanced Quantitative Techniques in the Social Sciences


Similar Products

Add Photo
Add Photo

Customer Reviews

REVIEWS      0     
Click Here To Be The First to Review this Product
Spatial Data Analysis With R: (Advanced Quantitative Techniques in the Social Sciences)
Sage Publications Inc Ebooks -
Spatial Data Analysis With R: (Advanced Quantitative Techniques in the Social Sciences)
Writing guidlines
We want to publish your review, so please:
  • keep your review on the product. Review's that defame author's character will be rejected.
  • Keep your review focused on the product.
  • Avoid writing about customer service. contact us instead if you have issue requiring immediate attention.
  • Refrain from mentioning competitors or the specific price you paid for the product.
  • Do not include any personally identifiable information, such as full names.

Spatial Data Analysis With R: (Advanced Quantitative Techniques in the Social Sciences)

Required fields are marked with *

Review Title*
Review
    Add Photo Add up to 6 photos
    Would you recommend this product to a friend?
    Tag this Book Read more
    Does your review contain spoilers?
    What type of reader best describes you?
    I agree to the terms & conditions
    You may receive emails regarding this submission. Any emails will include the ability to opt-out of future communications.

    CUSTOMER RATINGS AND REVIEWS AND QUESTIONS AND ANSWERS TERMS OF USE

    These Terms of Use govern your conduct associated with the Customer Ratings and Reviews and/or Questions and Answers service offered by Bookswagon (the "CRR Service").


    By submitting any content to Bookswagon, you guarantee that:
    • You are the sole author and owner of the intellectual property rights in the content;
    • All "moral rights" that you may have in such content have been voluntarily waived by you;
    • All content that you post is accurate;
    • You are at least 13 years old;
    • Use of the content you supply does not violate these Terms of Use and will not cause injury to any person or entity.
    You further agree that you may not submit any content:
    • That is known by you to be false, inaccurate or misleading;
    • That infringes any third party's copyright, patent, trademark, trade secret or other proprietary rights or rights of publicity or privacy;
    • That violates any law, statute, ordinance or regulation (including, but not limited to, those governing, consumer protection, unfair competition, anti-discrimination or false advertising);
    • That is, or may reasonably be considered to be, defamatory, libelous, hateful, racially or religiously biased or offensive, unlawfully threatening or unlawfully harassing to any individual, partnership or corporation;
    • For which you were compensated or granted any consideration by any unapproved third party;
    • That includes any information that references other websites, addresses, email addresses, contact information or phone numbers;
    • That contains any computer viruses, worms or other potentially damaging computer programs or files.
    You agree to indemnify and hold Bookswagon (and its officers, directors, agents, subsidiaries, joint ventures, employees and third-party service providers, including but not limited to Bazaarvoice, Inc.), harmless from all claims, demands, and damages (actual and consequential) of every kind and nature, known and unknown including reasonable attorneys' fees, arising out of a breach of your representations and warranties set forth above, or your violation of any law or the rights of a third party.


    For any content that you submit, you grant Bookswagon a perpetual, irrevocable, royalty-free, transferable right and license to use, copy, modify, delete in its entirety, adapt, publish, translate, create derivative works from and/or sell, transfer, and/or distribute such content and/or incorporate such content into any form, medium or technology throughout the world without compensation to you. Additionally,  Bookswagon may transfer or share any personal information that you submit with its third-party service providers, including but not limited to Bazaarvoice, Inc. in accordance with  Privacy Policy


    All content that you submit may be used at Bookswagon's sole discretion. Bookswagon reserves the right to change, condense, withhold publication, remove or delete any content on Bookswagon's website that Bookswagon deems, in its sole discretion, to violate the content guidelines or any other provision of these Terms of Use.  Bookswagon does not guarantee that you will have any recourse through Bookswagon to edit or delete any content you have submitted. Ratings and written comments are generally posted within two to four business days. However, Bookswagon reserves the right to remove or to refuse to post any submission to the extent authorized by law. You acknowledge that you, not Bookswagon, are responsible for the contents of your submission. None of the content that you submit shall be subject to any obligation of confidence on the part of Bookswagon, its agents, subsidiaries, affiliates, partners or third party service providers (including but not limited to Bazaarvoice, Inc.)and their respective directors, officers and employees.

    Accept

    New Arrivals


    Inspired by your browsing history


    Your review has been submitted!

    You've already reviewed this product!