Spatial Data Analysis

Name: Spatial Data Analysis
ISBN: 9787301255537

毕硕本Peking University Press · ChinaAug 2025

Rating 3.4

Word count: 67 words
Chapters: 7
ISBN: 9787301255537

Summary

This book is written according to the development goal of cultivating comprehensive interdisciplinary undergraduate talents in higher education institutions, and introduces the principles and methods of spatial data analysis. The book consists of 17 chapters, mainly covering the introduction, the nature of spatial data, completion of spatial data, standardization of spatial data, exploratory spatial data analysis, spatial point pattern analysis, geostatistical data interpolation, grid data statistics, grid data regression analysis, spatial regression analysis, areal data spatial pattern analysis, spatial continuous data analysis methods, nonparametric statistics, spatial sampling methods, spatial measurement algorithms, spatial analysis algorithms, and spatial statistical analysis algorithms.

This book can be used as a textbook for students in related majors such as geographic information systems, computer science and technology, remote sensing science and technology, surveying and mapping engineering, and geographical science, and is also suitable for reference by personnel engaged in spatial data analysis and geographic information system applications.

Editor's review

This is a comprehensive and well-structured textbook on spatial data analysis. The author unfolds the material layer by layer around the nature, completion, and standardization of spatial data, as well as exploratory analysis, point pattern analysis, geostatistical interpolation, grid data statistics and regression, spatial regression, areal data pattern analysis, spatial sampling, and algorithm implementation, balancing principle explanation with method application. With 17 chapters, the book is more a systematic tutorial than a quick-reference manual, suitable for chapter-by-chapter study in a course. Its strength lies in combining statistical analysis thinking with the characteristics of spatial data; it discusses data preprocessing and also covers nonparametric statistics and spatial analysis algorithms, helping readers build a complete chain from data organization to modeling and inference. Readers can consolidate their understanding of methods with software practice. As a university textbook, it is theoretically dense and requires readers to have basic knowledge of statistics and geographic information systems to smoothly digest the formulas and algorithm descriptions.

Who it's for

A good fit for

Undergraduates in geographic information systems, surveying and mapping engineering, and related majors who need to systematically learn spatial data analysis methods
Remote sensing science and technology students seeking to fill gaps in spatial statistics and modeling knowledge
GIS application technicians needing reference for spatial interpolation and regression analysis methods
Graduate students in geographical science and related fields using the book to review the methodological system of spatial analysis

Not a good fit for

Readers with no foundation, who will struggle to follow formula derivations without basic statistics and GIS concepts
Readers who only want to quickly look up single operation steps; the book emphasizes principles rather than being a software operation manual
Practitioners concerned only with spatial data visualization and not statistical modeling

Reading tips

Read the introduction and the chapter on the nature of spatial data first to build a conceptual framework before moving to specific method chapters.
After learning each analysis method, do an exercise with a real spatial dataset to test your understanding of the principles.
For chapters with many formula derivations, first grasp the applicable conditions and conclusions of the methods, then read the derivations in detail on a second pass.
Read chapters on point pattern analysis, interpolation, and regression in comparison to see how analytical approaches differ across data types.

About the publisher

Peking University Press China · Founded in 1979

Peking University Press is a comprehensive university press whose publishing areas cover classical literature, popular science, social culture, world history, Western philosophy, and culture. Its catalogue contains 6,031 titles, with representative books including A Dream of Red Mansions, Relativity: The Special and General Theory (15th Edition) (with Einstein's classic papers on unified field theory and other topics), Elements, Conics, The Aristocratic Families of the Eastern Jin, The Philosophy of Mythology (Volume I), The Philosophy of Mythology (Volume II), and The Origin of Continents and Oceans. Representative authors include Cao Xueqin, Zhou Ruchang, Albert Einstein, Euclid, Apollonius, Tian Yuqing, Schelling, and Xian Gang. The press has developed distinctive strengths in classical Chinese literature and in the translation of Western philosophical classics, while also covering scientific classics and social and cultural studies. As public information is limited, this description is based only on the books in the catalogue and offers no further extrapolation.

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FAQ

Can I understand this book without a statistics background?

It will be somewhat difficult. The book involves regression analysis, nonparametric statistics, and spatial statistics, which require basic statistical concepts. It is advisable to first supplement foundational knowledge of descriptive and inferential statistics before reading the relevant chapters; while studying, prioritize the applicable conditions and operational ideas of the methods, then gradually delve into formula details.

Is this book suitable for use as a course textbook?

Yes. The book has 17 chapters, progressing from the nature of spatial data to various analysis methods and algorithms, with a progressive chapter arrangement that fits the teaching rhythm of similar courses. Teachers can select core chapters according to class hours, and students can also self-study chapter by chapter, but they need practice data to better master the methods.

Do the methods in the book require learning with specific software?

The materials do not specify particular software. Readers can choose commonly used GIS and statistical analysis tools according to their course or work environment and apply the book's methods in practice. It is advisable to complete a data processing exercise alongside each method to deepen understanding of the analysis workflow and result interpretation.

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About the author

毕硕本 Author

Bi Shuoben: publicly available information is limited. At present, only one work by this author is known, namely Spatial Data Analysis. Judging from the title and its listed category, the book deals with the processing, analysis, and application of spatial data, and is likely intended for teaching and examination needs in fields such as geographic information and surveying, which explains its classification under exam-related books. The work probably presents, in the form of a textbook or study guide, the chain of collecting, organizing, statistically analyzing, and visualizing spatial data, building a knowledge framework suited to learning and revision. For exam candidates, the value of such a work lies in clarifying concepts, summarizing methods, and offering practice ideas rather than pursuing advanced theoretical argument. Since the author's biography, education, positions, and institutional affiliation cannot be confirmed, this introduction makes no inferences and describes only the subject matter and possible use of the work; readers seeking the author's academic background should consult further public sources.