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Integrating spatial data analysis functionalities in a GIS environment: Spatial Analysis using ArcGIS Engine and R (SAAR).

Hyeongmo KooYongwan ChunDaniel Griffith
Published in: Transactions in GIS : TG (2018)
Spatial data analysis (SDA) tools to efficiently handle and explore spatial data have become readily available. Although these SDA tools have their own strengths and purposes, they suffer from limited support in terms of a development environment offering easy customization and high extensibility, a strength of open source software. This paper presents a stand-alone software package for SDA in a geographic information systems (GIS) environment, called Spatial Analysis using ArcGIS Engine and R (SAAR), which provides an integrated GIS and SDA environment. A set of SDA tools in SAAR utilize functions in R using R.NET, while other tools were developed in .NET independent of R. SAAR provides an efficient working environment for both general and advanced GIS users. For general GIS users with limited programming skills, SAAR furnishes advanced SDA tools in a popular ArcGIS environment with graphical user interfaces. For advanced GIS users, SAAR offers an extensible GIS platform to help them customize and implement SDA functions with relatively little development effort. This paper demonstrates some functionalities of SAAR using census data for Texas counties.
Keyphrases
  • data analysis
  • healthcare
  • electronic health record
  • deep learning
  • machine learning
  • high throughput
  • health information
  • social media