ArcGIS is the central tool to handle and derive geoinformation in many applications. However, the standard kriging capabilities only include a few covariance functions and hide the estimation and fit quality of the semivariogram to a large degree. R is less appealing for working with maps, but features a variety of statistical, i.e. geostatistical, extensions. In this showcase, we exploit the semivariogram modeling and kriging capabilities of the gstat R package. In order to give the user visual control over the estimation procedure and the model selection, we use the Shiny framework to realize an interactive graphical user-interface for the semivariogram fitting step. This tool hides the entire R implementation from the user, but delivers a good deal of the geostatistical power to perform kriging.more >
A final wrap up of the Google Summer of Code project: Trajectory Analysis in R can be found in RPubs here.
Trajectory analysis has a wide range of applications in various fields such as geoscience and social science. Use cases span across mobile phone users (see image below) e.g. for commuting analysis, ship and flight paths or animal tracking. With the avalanche of GPS-annotated data in the past few years capturing such data became much easier, so today there is a need for tools that are specifically tailored for analyzing large-scale trajectory data (example).
R, as a software environment for statistical computing and graphics, has been favored by researchers from various disciplines for its free access, rich statistical methods, and easy-to-share features. However, the classes and methods specifically developed for trajectory analysis are limited and domain-orientated in R. This project intends to address this issue by implementing and improving generic classes and methods for trajectory analysis.more >