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E-raamat: Spatiotemporal Analytics

(National Science Foundation, Arlington, Virginia, USA)
  • Formaat: 266 pages
  • Ilmumisaeg: 17-Mar-2023
  • Kirjastus: CRC Press
  • Keel: eng
  • ISBN-13: 9781000844542
  • Formaat - EPUB+DRM
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  • Raamatukogudele
  • Formaat: 266 pages
  • Ilmumisaeg: 17-Mar-2023
  • Kirjastus: CRC Press
  • Keel: eng
  • ISBN-13: 9781000844542

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This book introduces readers to spatiotemporal analytics that are extended from spatial statistics. Spatiotemporal analytics help analysts to quantitatively recognize and evaluate the spatial patterns and their temporal trends of a set of geographic events or objects. Spatiotemporal analyses are very important in geography, environmental sciences, economy, and many other domains. Spatiotemporal Analytics explains in very simple terms the concepts of spatiotemporal data and statistics, theories, and methods used. Each chapter introduces a case study as an example application for an in-depth learning process. The software used and the codes provided enable readers not only to learn statistics but also to use them effectively in their projects.

Provides a comprehensive understanding of spatiotemporal analytics to readers with minimum knowledge in statistics.

Written in simple, understandable language with step-by-step instructions.



Includes numerous examples for all theories and methods explained in the book covering a wide range of applications from different disciplines.

Each application includes a software code needed to follow the instructions.

Each chapter also has a set of prepared PowerPoint slides to help spatiotemporal analytics instructors explain the content.

Undergraduate and graduate students who use Geographic Information Systems or study Geographical Information Science will find this book useful. The subject matter is also pertinent to an array of disciplines such as agriculture, anthropology, archaeology, architecture, biology, business administration and management, civic engineering, criminal justice, epidemiology, geography, geology, marketing, political science, and public health.
Editor vii
Contributors ix
Chapter 1 Introduction to Spatiotemporal Analytics
1(12)
Jay Lee
Chapter 2 Spatiotemporal Centrography and Dispersion
13(22)
Langxue Dang
Jay Lee
Huiyu Lin
Chapter 3 Spatiotemporal Quadrat Analytics
35(18)
Zhuo Chen
Chapter 4 Spatiotemporal Nearest Neighbor Analytics
53(24)
Qingsong Liu
Jay Lee
Chapter 5 Spatiotemporal Ripley's A and L Functions
77(14)
Jay Lee
Chapter 6 Spatiotemporal Autocorrelation Analytics
91(22)
Shengwen Li
Xuyang Cheng
Bo Wan
Junfang Gong
Jay Lee
Chapter 7 Spatiotemporal G Statistical Analytics
113(14)
Huiyu Lin
Zhuo Chen
Chapter 8 Spatiotemporal Kernel Density Estimation
127(18)
Junfang Gong
Zhuang Zeng
Bo Wan
Shengwen Li
Jay Lee
Chapter 9 Spatiotemporally Weighted Regression
145(30)
Bo Huang
Sensen Wu
Chapter 10 Spatiotemporal Bayesian Regression
175(32)
Ortis Yankey
Tao Hu
Han Yue
Peixiao Wang
Xiao Xu
Chapter 11 Spatiotemporal Process Analytics and Simulations
207(26)
Moira O'Neill
Jay Lee
Chapter 12 Spatiotemporal Analytical Unit Problems
233(22)
Langxue Dang
Huiyu Lin
Jay Lee
Index 255
Jay Lee received his doctoral degree in Geography from the University of Western Ontario in 1989. Since then, he has tagut GIS and related courses at Kent State University. His research in applied geography aims at solving practical problems that the society faces. Dr. Lee applied spatial and spatiotemporal analysis of geographic information in his works of over 120 published journal articles, book chapters and books. Among others, he has co-authored two widely read books on statistical analysis of geographic information with GIS. Dr. Lees research grants include funding supports from NSF, USGS, EPA, NIJ, HUD, NASA, NOAA, and other state and local agencies.