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R and Spatial Data
Citation:
Weber, M., M. McManus, AND S. Kopp. R and Spatial Data. AWRA Spring Specialty Conference Geographic Information Systems (GIS) and Water Resources X, Orlando, Florida, April 22 - 25, 2018.
Impact/Purpose:
This workshop provides an introduction to working with spatial data in R and doing exploratory spatial data analysis (ESDA). Examples of ESDA methods include lagged scatter plots, Moran scatter plots, and linked micromaps. We will briefly mention some R packages that have been specifically developed to meet the needs of monitoring and modeling aquatic resources, such as lakes, rivers, and streams. Lastly, we will show how R and ArcGIS software can be integrated. The objective of this workshop is to provide users with the fundamentals of reading, visualizing and analyzing spatial data in R. The workshop should provide useful information and techniques to ecologists and GIS specialists doing aquatic research and monitoring, and will incorporate examples using EPA National Aquatic Resource Surveys (NARS).
Description:
R is an open source language and environment for statistical computing and graphics that can also be used for both spatial analysis (i.e. geoprocessing and mapping of different types of spatial data) and spatial data analysis (i.e. the application of statistical descriptions and models to georeferenced data). The ability to accomplish these spatial tasks, alongside typical statistical and graphics tasks, in one environment is an asset of using R, along with the reproducibility and transparency of analyses done in an open source environment. This workshop provides an introduction to working with spatial data in R and doing exploratory spatial data analysis (ESDA). Examples of ESDA methods include lagged scatter plots, Moran scatter plots, and linked micromaps. We will briefly mention some R packages that have been specifically developed to meet the needs of monitoring and modeling aquatic resources, such as lakes, rivers, and streams. Lastly, we will show how R and ArcGIS software can be integrated. The objective of this workshop is to provide users with the fundamentals of reading, visualizing and analyzing spatial data in R.
