Book Image

Learning R for Geospatial Analysis

By : Michael Dorman
Book Image

Learning R for Geospatial Analysis

By: Michael Dorman

Overview of this book

Table of Contents (18 chapters)
Learning R for Geospatial Analysis
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
External Datasets Used in Examples
Cited References
Index

About the Reviewers

Dr. Amrinder Arora is an adjunct faculty member in the Department of Computer Science at the George Washington University. He teaches graduate and undergraduate courses in Computer Science, mostly related to the design and analysis of computer algorithms and the design of data structures. He is also the author of the book Analysis and Design of Algorithms, Cognella Academic Publishing. He has been conferred the Instructor of the Year Award by the Department of Computer Science at the George Washington University and has received a VIP Grants Award by the Bowie State University. You can read more about his research at http://www.standardwisdom.com.

As part of his industry experience, he has served in the management teams of leading technology companies, including BizMerlin, Edifecs, and NTELX. As part of the Affordable Care Act, Dr. Arora designed a health exchange connector, a leading product in the $200 million market to connect insurance companies (payers) to the health insurance exchanges. As a leading expert in risk targeting, Dr. Arora led the technical design for US FDA's PREDICT system, which currently screens more than 16 million imports a year. His efforts in supporting FDA's PREDICT program were recognized by the FDA commissioner, Dr. Margaret Hamburg. The transportation management system designed by Dr. Arora for the port of Aqaba in Jordan won the award for the most innovative product by the Intelligent Transportation Society of America.

Dr. Arora earned an undergraduate degree in Computer Science from the Indian Institute of Technology, Delhi, and a Master's degree and doctorate, both in Computer Science, from the George Washington University. He served as a reviewer for numerous journals and conferences and many of his reviews have also been published in ACM Computing Reviews.

Dan Hammer is a data scientist and environmental economist who served as a Presidential Innovation Fellow at NASA as part of the White House program. He is a PhD student at University of California, Berkeley, and was formerly the Chief Data Scientist at the World Resources Institute, where he led the technical team behind Global Forest Watch. Dan writes code in Python, R, and Clojure on subjects ranging from spatial econometrics to information theory. He is currently reviewing Clojure for Data Science, Packt Publishing.

Baburao Kamble is an assistant research professor of Remote Sensing and Geospatial Data Analytics at the University of Nebraska-Lincoln (UNL). Currently, he works at UNL on developing machine learning and data mining algorithms using Big Data tools and techniques for climate and weather data. He has been involved in teaching Geospatial Information Sciences, Data Analysis using R, Python for Geospatial Data Analytics, and MATLAB courses at the graduate level. He is also the author of the upcoming book Practical Data Analysis Cookbook, Packt Publishing. He likes to spend his free time with new and interesting data science developments.

Dr. Robin Lovelace is an environmental geographer with 5 years of experience using R for spatial analysis, map making, and statistics. He has coauthored the popular free and open source online tutorial Introduction to visualising spatial data in R (2014), and teaches R to a range of professional and academic audiences.

Robin's latest book Spatial microsimulation with R, CRC Press (which will be published in 2015) demonstrates methods to generate and analyze multilevel data. By combining individual and geographical-level data, the technique can provide new insights into complex behaviors, for example, as an input into agent-based models.

Robin believes passionately in using open source technology to empower people to create a sustainable, post-carbon world—one in which we no longer depend on burning fossil fuels for a high quality of life.

Dipanjan Sarkar is a data engineer at DataWeave, one of India's top Big Data analytics start-ups, where he works on data semantics, information extraction, natural language processing, and machine learning. Prior to joining DataWeave, he worked as a graduate technical intern at Intel and received a Master's degree in Information Technology from the International Institute of Information Technology, Bangalore. Dipanjan is a technology enthusiast and loves Python and the start-up culture.

Dr. Makhan Virdi is a researcher at the Oak Ridge National Laboratory. He received his PhD from the University of South Florida in 2013. His current research interests include management and visualization of geospatial and time series data from satellite imagery for biogeochemical dynamics.

Dr. Virdi is also an independent researcher with a passion for using embedded electronics, robotics, and knowledge discovery to create machine augmented intelligence systems. In his spare time, he works on robots, ambient intelligence, and smart homes. You can read more about his research at TheXLabs.com.