Bridging the R gap for South African Environmentalists

Esri South Africa is working with emerging business partner M.A.P Scientific Services to highlight to environmentalists the synergies of using R and ArcGIS together via the R – ArcGIS Bridge. Benefits to users include harnessing the powers of machine learning for enhanced statistical, spatial and imagery analysis of vast datasets.

19 February 2019

Bridging the R gap for South African environmentalists

R, a powerful tool for statistical computing and graphics, is increasingly being used by South African environmental scientists to analyse and interpret complex ecological datasets. It is a free integrated suite of software applications for data manipulation, calculation and graphical display.

However, while R is widely used by scientists and statisticians for complex data analysis, it has limited data management and mapping capabilities. Noting this gap, Esri encouraged integration of its ArcGIS mapping platform with R and, over time, feedback from ArcGIS and R users regarding needs and integration techniques was used to develop a bridge between the two technologies.

Developed by Esri, the R – ArcGIS Bridge is a free, open source R package which enables ArcGIS and R users to successfully synergise the two systems. R developers can quickly access ArcGIS datasets from within R, save R results back to ArcGIS datasets and tables, and easily convert between ArcGIS datasets and their equivalent representations within R.

The bridge improves the performance and scalability of projects which combine R and ArcGIS while providing R users with a familiar developer experience and ArcGIS users with a familiar end-user experience. It also allows developers to create custom tools and toolboxes that integrate ArcGIS and R. They can do this for their own use or to share with other users within their organisations or with other ArcGIS users.

Among the benefits that Esri brings to this relationship is its combining of machine learning (ML) and geographic information systems (GIS).

ML refers to a set of data-driven algorithms and techniques that automate the prediction, classification, and clustering of data. It can play a critical role in spatial problem-solving in a wide range of application areas from multivariate prediction to image classification to spatial pattern detection.

Blending ML and GIS provides greater opportunities to obtain spatial understanding of complex problems. This enables scientists to take advantage of the immense amount of spatial and spatiotemporal data being collected within their organisations and around the world.

The R – ArcGIS Bridge enables users benefit from this intertwining of ML and GIS. It also allows users to integrate R into their workflows without having to learn the R programming language and it allows non-GIS people to directly access ArcGIS data without needing to know ArcGIS. Ultimately it is about helping the ArcGIS and R user communities to more successfully combine two cutting-edge technologies.

Areas where environmentalists will appreciate immediate use of the bridge include statistical analysis of remotely sensed data, analysis and illustration of animal location data, and image analysis and data sorting techniques for camera trapping.