Spatiotemporal Analysis of Air Pollution and Its Application in Public Health

Author:   Lixin Li (Professor, Department of Computer Sciences, Georgia Southern University) ,  Xiaolu Zhou (Assistant Professor, Department of Geography, Texas Christian University) ,  Weitian Tong (Assistant Professor, Department of Computer Science, Eastern Michigan University) ,  Lixin Li (Professor, Department of Computer Sciences, Georgia Southern University)
Publisher:   Elsevier Science Publishing Co Inc
ISBN:  

9780128158227


Pages:   328
Publication Date:   13 November 2019
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Spatiotemporal Analysis of Air Pollution and Its Application in Public Health


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Overview

Spatiotemporal Analysis of Air Pollution and Its Application in Public Health reviews, in detail, the tools needed to understand the spatial temporal distribution and trends of air pollution in the atmosphere, including how this information can be tied into the diverse amount of public health data available using accurate GIS techniques. By utilizing GIS to monitor, analyze and visualize air pollution problems, it has proven to not only be the most powerful, accurate and flexible way to understand the atmosphere, but also a great way to understand the impact air pollution has in diverse populations. This book is essential reading for novices and experts in atmospheric science, geography and any allied fields investigating air pollution.

Full Product Details

Author:   Lixin Li (Professor, Department of Computer Sciences, Georgia Southern University) ,  Xiaolu Zhou (Assistant Professor, Department of Geography, Texas Christian University) ,  Weitian Tong (Assistant Professor, Department of Computer Science, Eastern Michigan University) ,  Lixin Li (Professor, Department of Computer Sciences, Georgia Southern University)
Publisher:   Elsevier Science Publishing Co Inc
Imprint:   Elsevier Science Publishing Co Inc
Weight:   0.660kg
ISBN:  

9780128158227


ISBN 10:   0128158220
Pages:   328
Publication Date:   13 November 2019
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

1. Introduction to Spatiotemporal Variations of Air Pollutants and related Public Health Impacts 2. Illustrations of Statistical Analysis for Air Pollution Data 3. Case Study: Does PM2.5 Contribute to the Incidence of Lung and Bronchial Cancers in the U.S.? 4. Bayesian Modeling for Linkage between Air Pollution and Population Health 5. Machine Learning for Spatiotemporal Big Data in Air Pollution 6. Integrate Machine Learning and Geostatistics for High Resolution Mapping of Gound-level PM2.5 Concentrations 7. Spatiotemporal Interpolation Methods for Air Pollution 8. Sensing Air Quality: Spatiotemporal Interpolation and Visualization of Real-time Air Pollution Data in the Contiguous U.S. 9. Assessment Methods for Air Pollution Exposure 10. Applying LUR Model to Estimate Spatial Variation of PM2.5 in Greater Bay Area, China 11. Analysis of Exposure to Ambient Air Pollution: the Link Between Environmental Exposure and Children’s School Performance in Memphis, TN 12. Concentrating Risk? The Geographic Concentration of Health Risk from Industrial Air Toxins Across America 13. Travel-related exposure to air pollution and its socio-environmental inequalities: Evidence from a week-long GPS-based travel diary dataset

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Author Information

Lixin Li is a tenured Professor in the Department of Computer Science at Georgia Southern University. She received her Ph.D. degree in Computer Science from the University of Nebraska-Lincoln in 2003. Her research focuses on spatiotemporal interpolation methods, air pollution, and GIS applications Xiaolu Zhou received his Ph.D. degree from University of Illinois at Urbana-Champaign in 2014. His research interests include geospatial analytics in spatial big data and human mobility analysis based on user generated content and smartphone sensing. Weitian Tong received his Ph.D. degree in Computer Science from the University of Alberta in 2015. His research interests include data science and optimization algorithm design.

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