Using R for Spatial Analytics

Date and Time: 
Wednesday, April 6th, 2016
Center Green
Guido Cervone, Carolynne Hultquist and Elena Sava

R is a powerful open source and community supported programming environment first developed to satisfy the requirements of the Statistical community. Over the years R has developed into a general purpose language, and it has been applied to solve various problems across different disciplines. Powerful R packages are now available to analytically interact with spatial data in an efficient manner.

In this talk and tutorial, we present how R can be used to analyze and visualize spatial data, in particular remote sensing and atmospheric model data. We will utilize programs to analyze Landsat and MODIS imagery, and show how to prepare the data to be used in the WRF atmospheric model.

We will also address how to write multi-core programs that take advantage of today’s common multi-core CPUs. R is particularly suited to work in a multi-core environment, as parallel computations can be easily distributed across multiple cores.

The session aims to demonstrate scientific applications of how the R environment provides unique solutions for spatial data analysis

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