High Performance Computing for Geospatial Applications

298 Pages·2020·10.319 MB·English

by  Wenwu Tang, Shaowen Wang

Geotechnologies and the Environment
Wenwu Tang
Shaowen Wang  Editors
High Performance
Computing
for Geospatial
Applications
Geotechnologies and the Environment
Volume 23
Series editors
Jay D. Gatrell, Department of Geology & Geography, Eastern Illinois University,
Charleston, IL, USA
Ryan R. Jensen, Department of Geography, Brigham Young University,
Provo, UT, USA
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More information about this series at http://www.springer.com/series/8088
Wenwu Tang • Shaowen Wang
Editors
High Performance
Computing for Geospatial
Applications
Editors
Wenwu Tang Shaowen Wang
Center for Applied Geographic Department of Geography and Geographic
Information Science Information Science
Department of Geography University of Illinois at Urbana­Champaign
and Earth Sciences Urbana, IL, USA
University of North Carolina at Charlotte
Charlotte, NC, USA
ISSN 2365­0575 ISSN 2365­0583 (electronic)
Geotechnologies and the Environment
ISBN 978­3­030­47997­8 ISBN 978­3­030­47998­5 (eBook)
https://doi.org/10.1007/978­3­030­47998­5
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Preface
“Use the right tool for the job.”
While high­performance computing (HPC) has been recognized as the right tool
for computationally intensive geospatial applications, there is often a gap between
the rapid development of HPC approaches and their geospatial applications that are
often lagging behind. The objective of this edited book is to (help) fill this gap so
that this important right tool can be used in an appropriate and timely manner.
This book includes fifteen chapters to examine the utility of HPC for novel geo­
spatial applications. Chapter 1 serves as an introduction to the entire book overarch­
ing all the other fourteen chapters, which are organized into four parts. Part I (Chaps.
2 and 3) focuses on theoretical and algorithmic aspects of HPC within the context
of geospatial applications. Part II (Chaps. 4–9) concentrates on how HPC is applied
to geospatial data processing, spatial analysis and modeling, and cartography and
geovisualization. Part III (Chaps. 10–14) covers representative geospatial applica­
tions of HPC from multiple domains. Part IV (Chap. 15) is a perspective view of
HPC for future geospatial applications.
This book serves as a collection of recent work written as review and research
papers on how HPC is applied to solve a variety of geospatial problems. As advanced
computing technologies keep evolving, HPC will continue to function as the right
tool for the resolution of many complex geospatial problems that are often compu­
tationally demanding. The key is to understand both the computational and geospa­
tial nature of these problems for best exploiting the amazing power of HPC. The
book is designed to serve this key purpose, which may help readers to identify per­
tinent opportunities and challenges revolving around geospatial applications of
HPC—i.e., use the right tool for the job at the right time.
Charlotte, NC, USA Wenwu Tang
Urbana, IL, USA Shaowen Wang
February 28, 2020
v
Acknowledgements
The editors want to take this opportunity to sincerely thank all the coauthors and
reviewers of chapters of this book for their considerable efforts and hard work. The
editors also owe special thanks to Zachary Romano and Silembarasan Panneerselvam
from Springer Nature for their strong support and timely help during the review and
editing process of this book. Minrui Zheng and Tianyang Chen provided assistance
on the formatting of the manuscripts of this book.
Nothing is more motivating than a baby cry; nothing is more relaxing than baby
giggles. Wenwu Tang wants to thank his wife, Shuyan Xia, and two sons, William
Tang and Henry Tang, for their love and understanding. The preparation of this book
was accompanied by the birth of baby Henry. While it is always challenging to bal­
ance between interesting academic work and continuous family duties, enduring
support from his family is the greatest source of strength for completing this book.
Shaowen Wang wants to acknowledge the support of the U.S. National Science
Foundation under the grant numbers: 1443080 and 1743184. Any opinions, find­
ings, and conclusions or recommendations expressed in this material are those of
the authors and do not necessarily reflect the views of the National Science
Foundation.
vii
Contents
1 Navigating High Performance Computing
for Geospatial Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Wenwu Tang and Shaowen Wang
Part I Theoretical Aspects of High Performance Computing
2 High Performance Computing for Geospatial Applications:
A Retrospective View . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
Marc P. Armstrong
3 Spatiotemporal Domain Decomposition
for High Performance Computing: A Flexible
Splits Heuristic to Minimize Redundancy . . . . . . . . . . . . . . . . . . . . . . 27
Alexander Hohl, Erik Saule, Eric Delmelle, and Wenwu Tang
Part II High Performance Computing for Geospatial Analytics
4 Geospatial Big Data Handling with High Performance
Computing: Current Approaches and Future Directions . . . . . . . . . . 53
Zhenlong Li
5 Parallel Landscape Visibility Analysis: A Case Study
in Archaeology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
Minrui Zheng, Wenwu Tang, Akinwumi Ogundiran,
Tianyang Chen, and Jianxin Yang
6 Quantum Computing for Solving Spatial
Optimization Problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
Mengyu Guo and Shaowen Wang
7 Code Reusability and Transparency of Agent-Based
Modeling: A Review from a Cyberinfrastructure Perspective . . . . . . 115
Wenwu Tang, Volker Grimm, Leigh Tesfatsion, Eric Shook,
David Bennett, Li An, Zhaoya Gong, and Xinyue Ye
ix
x Contents
8 Integration of Web GIS with High- Performance
Computing: A Container- Based Cloud Computing Approach . . . . . . 135
Zachery Slocum and Wenwu Tang
9 Cartographic Mapping Driven by High- Performance
Computing: A Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159
Wenwu Tang
Part III Domain Applications of High Performance Computing
10 High-Performance Computing for Earth System Modeling . . . . . . . . 175
Dali Wang and Fengming Yuan
11 High-Performance Pareto-Based Optimization Model
for Spatial Land Use Allocation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185
Xiaoya Ma, Xiang Zhao, Ping Jiang, and Yuangang Liu
12 High-Performance Computing in Urban Modeling . . . . . . . . . . . . . . . 211
Zhaoya Gong and Wenwu Tang
13 Building a GPU-Enabled Analytical Workflow
for Maritime Pattern Discovery Using Automatic
Identification System Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227
Xuantong Wang, Jing Li, and Tong Zhang
14 Domain Application of High Performance Computing
in Earth Science: An Example of Dust Storm Modeling
and Visualization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249
Qunying Huang, Jing Li, and Tong Zhang
Part IV Future of High Performance Computing
for Geospatial Applications
15 High Performance Computing for Geospatial Applications:
A Prospective View . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271
Marc P. Armstrong
Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285
Contributors
Li An Department of Geography and PKU­SDSU Center for Complex Human­
Environment Systems, San Diego State University, San Diego, CA, USA
Marc P. Armstrong Department of Geographical and Sustainability Sciences, The
University of Iowa, Iowa City, IA, USA
David  Bennett Department of Geographical and Sustainability Sciences,
University of Iowa, Iowa City, IA, USA
Tianyang  Chen Center for Applied Geographic Information Science, The
University of North Carolina at Charlotte, Charlotte, NC, USA
Department of Geography and Earth Sciences, The University of North Carolina at
Charlotte, Charlotte, NC, USA
Eric Delmelle Department of Geography and Earth Sciences, University of North
Carolina at Charlotte, Charlotte, NC, USA
Zhaoya Gong School of Geography, Earth and Environmental Sciences, University
of Birmingham, Edgbaston, Birmingham, UK
Volker  Grimm Department of Ecological Modelling, Helmholtz Center for
Environmental Research­UFZ, Leipzig, Germany
Mengyu Guo University of California, Berkeley, CA, USA
Alexander Hohl Department of Geography, University of Utah, Salt Lake City,
UT, USA
Qunying Huang Department of Geography, University of Wisconsin­Madison,
Madison, WI, USA
Ping Jiang School of Resource and Environmental Science, Wuhan University,
Wuhan, Hubei, China
xi