Webinar: Getting Started with Spatial Data Analysis with R

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I am glad to announce that I shall be presenting a live webinar with Domino Data Labs on February 24, 2016 from 11:00 – 11:30 AM PST: Getting Started with Spatial Data Analysis with R. If you are interested or know someone interested in learning how to manipulate spatial and spatial-temporal data with R, please send them along. Here is the abstract:

Synopsis

Spatial and spatial-temporal data have become pervasive. We are generating spatial data from route planners, sensors, mobile devices, and computers in different fields like transportation, agriculture, and social media. These data need to be analyzed to generate hidden insights that can improve business processes, help fight crime in cities, and much more.

Simply creating static maps is not enough. In this webinar we shall look at techniques of importing and exporting spatial data into R; understanding the foundation classes for spatial data; manipulation of spatial data; and techniques for spatial visualization. This webinar is meant to provide introductory knowledge of spatial data analysis in R needed to understand more complex spatial data modeling techniques.

We will cover the following topics:

  1. Why use R for spatial analysis
  2. Packages for spatial data analysis
  3. Types of spatial data
  4. Classes and methods in R for spatial data analysis
  5. Importing and exporting spatial data
  6. Visualizing spatial data in R

About the Speaker

Daniel Emaasit, Ph.D Student at University of Nevada, Las Vegas

Daniel is a Ph.D Student of Transportation Engineering at UNLV where his research involves application of statistical machine learning to developing Activity-Based Travel Demand Models using Big Data from mobile phones. The objective of his research is to improve Transportation Planning by developing methods that model urban mobility patterns and trends.

He is an organizer of several Data Science and R meetup groups and actively contributes to open-source technologies in the R community.

Click this link to register for the webinar. I look forward to seeing you there and answering your questions.


Tagged: Data Science, Data Visualization, R, Webinar

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