Edited Books

Social Sensing and Big Data Computing for Disaster Management captures recent advancements in leveraging social sensing and big data computing for supporting disaster management. Specifically, analysed within this book are some of the promises and pitfalls of social sensing data for disaster relevant information extraction, impact area assessment, population mapping, occurrence patterns, geographical disparities in social media use, and inclusion in larger decision support systems. Traditional data collection methods such as remote sensing and field surveying often fail to offer timely information during or immediately following disaster events. Social sensing enables all citizens to become part of a large sensor network which is low cost, more comprehensive, and always broadcasting situational awareness information. However, data collected with social sensing is often massive, heterogeneous, noisy, and unreliable in some aspects. Together, these issues represent a grand challenge toward fully leveraging social sensing for emergency management decision making under extreme duress.

ISBN 9780367617653
Published November 23, 2020 by Routledge
204 Pages

Edited By: Zhenlong Li, Qunying Huang, Christopher T. Emrich
Big Data Computing for Geospatial Applications The convergence of big data and geospatial computing has brought forth challenges and opportunities to Geographic Information Science with regard to geospatial data management, processing, analysis, modeling, and visualization. This book highlights recent advancements in integrating new computing approaches, spatial methods, and data management strategies to tackle geospatial big data challenges and meanwhile demonstrates opportunities for using big data for geospatial applications. Crucial to the advancements highlighted in this book is the integration of computational thinking and spatial thinking and the transformation of abstract ideas and models to concrete data structures and algorithms.

SBN 978-3-03943-244-8 (Hbk);
ISBN 978-3-03943-245-5 (PDF)
Published November, 2020 by MPDI
222 Pages

Edited By:  Zhenlong Li, Wenwu Tang, Qunying Huang, Eric Shook, Qingfeng Guan
Introduction to GIS Programming and Fundamentals with Python and ArcGIS® Combining GIS concepts and fundamental spatial thinking methodology with real programming examples, this book introduces popular Python-based tools and their application to solving real-world problems. It elucidates the programming constructs of Python with its high-level toolkits and demonstrates its integration with ArcGIS Theory. Filled with hands-on computer exercises in a logical learning workflow this book promotes increased interactivity between instructors and students while also benefiting professionals in the field with vital knowledge to sharpen their programming skills. Readers receive expert guidance on modules, package management, and handling shapefile formats needed to build their own mini-GIS. Comprehensive and engaging commentary, robust contents, accompanying datasets, and classroom-tested exercises are all housed here to permit users to become competitive in the GIS/IT job market and industry.

eBook ISBN9781315156682
Published May, 2017 by CRC Press
328 Pages

Edited By:  Chaowei Yang, Manzhu Yu, Qunying Huang, Zhenlong Li, Min Sun, Kai Liu, Yongyao Jiang, Jizhe Xia, Fei Hu
An exploration of the benefits of cloud computing in geoscience research and applications as well as future research directions, Spatial Cloud Computing: A Practical Approach discusses the essential elements of cloud computing and their advantages for geoscience. Using practical examples, it details the geoscience requirements of cloud computing, covers general procedures and considerations when migrating geoscience applications onto cloud services, and demonstrates how to deploy different applications. The book discusses how to choose cloud services based on the general cloud computing measurement criteria and cloud computing cost models. The authors examine the readiness of cloud computing to support geoscience applications using open source cloud software solutions and commercial cloud services. They then review future research and developments in data, computation, concurrency, and spatiotemporal intensities of geosciences and how cloud service can be leveraged to meet the challenges. They also introduce research directions from the aspects of technology, vision, and social dimensions.

ISBN 9781138075559
Published March, 2017 by CRC Press
357 Pages

Edited By:  Chaowei Yang, Qunying Huang, Zhenlong Li, Chen Xu, Kai Liu
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