Table Of ContentSpatiotemporal Analytics
This book introduces readers to spatiotemporal analytics that are extended
from spatial statistics. Spatiotemporal analytics help analysts to quantita-
tively 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 with 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 provided codes enable
readers not only to learn the analytics but also to use them effectively in
their projects.
• Provides a comprehensive understanding of spatiotemporal ana-
lytics 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
instructors of a course on spatiotemporal analytics with the con-
tent explained.
Undergraduate and graduate students who use Geographic Information
Systems or study Geographical Information Science will find this book
useful. The subject matter also pertains to an array of disciplines such
as agriculture, anthropology, archaeology, architecture, biology, business
administration and management, civic engineering, criminal justice, epi-
demiology, geography, geology, marketing, political science, and public
health.
Spatiotemporal Analytics
Jay Lee
Designed cover image: Image from Shutterstock (Image ID: 1115087306)
First edition publisshed 2023
by CRC Press
6000 Broken Sound Parkway NW, Suite 300, Boca Raton, FL 33487-2742
and by CRC Press
4 Park Square, Milton Park, Abingdon, Oxon, OX14 4RN
CRC Press is an imprint of Taylor & Francis Group, LLC
© 2023 selection and editorial matter, Jay Lee; individual chapters, the contributors
Reasonable efforts have been made to publish reliable data and information, but the author and
publisher cannot assume responsibility for the validity of all materials or the consequences of
their use. The authors and publishers have attempted to trace the copyright holders of all material
reproduced in this publication and apologize to copyright holders if permission to publish in this
form has not been obtained. If any copyright material has not been acknowledged please write
and let us know so we may rectify in any future reprint.
Except as permitted under U.S. Copyright Law, no part of this book may be reprinted, reproduced,
transmitted, or utilized in any form by any electronic, mechanical, or other means, now known or
hereafter invented, including photocopying, microfilming, and recording, or in any information
storage or retrieval system, without written permission from the publishers.
For permission to photocopy or use material electronically from this work, access www.
copyright.com or contact the Copyright Clearance Center, Inc. (CCC), 222 Rosewood Drive,
Danvers, MA 01923, 978-750-8400. For works that are not available on CCC please contact
[email protected]
Trademark notice: Product or corporate names may be trademarks or registered trademarks and
are used only for identification and explanation without intent to infringe.
ISBN: 978-1-032-303055 (hbk)
ISBN: 978-1-032-303062 (pbk)
ISBN: 978-1-003-304395 (ebk)
DOI: 10.1201/9781003304395
Typeset in Times
by codeMantra
Access the Support Material: www.routledge.com/9781032303055
Contents
Editor .......................................................................................................vii
Contributors .............................................................................................ix
Chapter 1 Introduction to Spatiotemporal Analytics ............................1
Jay Lee
Chapter 2 Spatiotemporal Centrography and Dispersion .....................13
Langxue Dang, Jay Lee, and Huiyu Lin
Chapter 3 Spatiotemporal Quadrat Analytics .....................................35
Zhuo Chen
Chapter 4 Spatiotemporal Nearest Neighbor Analytics .......................53
Qingsong Liu and Jay Lee
Chapter 5 Spatiotemporal Ripley’s K and L Functions .......................77
Jay Lee
Chapter 6 Spatiotemporal Autocorrelation Analytics ..........................91
Shengwen Li, Xuyang Cheng, Bo Wan, Junfang Gong,
and Jay Lee
Chapter 7 Spatiotemporal G Statistical Analytics .............................113
Huiyu Lin and Zhuo Chen
Chapter 8 Spatiotemporal Kernel Density Estimation .......................127
Junfang Gong, Zhuang Zeng, Bo Wan, Shengwen Li,
and Jay Lee
Chapter 9 Spatiotemporally Weighted Regression .............................145
Bo Huang and Sensen Wu
v
vi Contents
Chapter 10 Spatiotemporal Bayesian Regression .................................175
Ortis Yankey, Tao Hu, Han Yue, Peixiao Wang,
and Xiao Xu
Chapter 11 Spatiotemporal Process Analytics and Simulations .........207
Moira O’Neill and Jay Lee
Chapter 12 Spatiotemporal Analytical Unit Problems .........................233
Langxue Dang, Huiyu Lin, and Jay Lee
Index ......................................................................................................255
Editor
Dr. Jay Lee received his PhD in geography from the University of Western
Ontario in 1989. Since then, he has taught GIS and quantitative methods in
geography at Kent State University. Dr. Lee’s research interests stem from
integrating operations research and spatial analysis. He coauthored two edi-
tions of Statistical Analysis with GIS. Since 2017, Dr. Lee has worked on
extending spatial analytics to spatiotemporal analytics. This book represents
the research outcomes from the Applied Geography Laboratory at Kent State
University from 2017 to 2022.
vii
Contributors
Zhuo Chen Jay Lee
Department of Geography Department of Geography
Kent State University Kent State University
Kent, Ohio Kent, Ohio
Xuyang Cheng Shengwen Li
National Engineering Research School of Computer Science
Center for Geographic China University of Geosciences
Information Systems Wuhan, China
China University of Geosciences
Wuhan, China Huiyu Lin
Department of Geography
Langxue Dang Kent State University
School of Computer and Kent, Ohio
Information Engineering
Henan University Qingsong Liu
Henan, China Shenzhen e-Traffic Technology
Shenzhen, China
Junfang Gong
School of Geography and Moira O’Neill
Information Engineering Department of Geography
China University of Geosciences Kent State University
Wuhan, China Kent, Ohio
Tao Hu Bo Wan
Department of Geography School of Computer Science
Oklahoma State University China University of Geosciences
Stillwater, Oklahoma Wuhan, China
Bo Huang Peixiao Wang
Department of Geography and Surveying, Mapping, and Remote
Resource Management Sensing
The Chinese University of Hong Wuhan University
Kong Wuhan, China
Hong Kong, China
ix
