ArcGIS Pro

Introducing updates and enhancements for the R-ArcGIS Bridge in ArcGIS Pro 3.0

Upgrading arcgisbinding when using ArcGIS Pro 3.0

The recent release of ArcGIS Pro 3.0 offers many exciting new features and functionalities. While many users are thrilled to upgrade to the new version, one of the most concerning questions for the R-ArcGIS Bridge users is: Can I still integrate ArcGIS Pro 3.0 with R? The answer is YES! To leverage the power of ArcGIS along with R data science packages, the only requirement is to upgrade R to 4.2.0+ and update arcgisbinding, the R-ArcGIS Bridge’s R package, to Version

There are two ways to update or check updates for the arcgisbinding.

Option 1: Upgrade through ArcGIS Pro > Settings

Pro 3.0 backstage
Opening the Pro 3.0 backstage

After opening the Pro 3.0 backstage, go to the ‘Settings’ tab on the left hand side. Then choose Options > Geoprocessing. Under the R-ArcGIS Support section, click on the icon and select ‘Install package from the Internet’.

Installing arcgisbinding from ArcGIS Pro > Settings > Options > Geoprocessing > R-ArcGIS Support

Option 2: Install within R

First, make sure you are on a supported R version (4.2.0 or later). Simply install arcgisbinding through: `install.packages(“arcgisbinding”, repos=””, type=”win.binary”)`

Unsupported versions of R in the R-ArcGIS Bridge

The R-ArcGIS Bridge provides R-based geoprocessing tool support for versions from 3.5.X, 3.6.X and 4.2.X. However, it does not support R versions 4.0.X and 4.1.X. For these unsupported R versions, we have released an arcgisbinding package that will inform you that running geoprocessing tools is not supported. In case you are working on any of the unsupported R versions mentioned above, and you are looking to install the arcgisbinding package through the ArcGIS Pro Geoprocessing tab, you don’t need to worry about the arcgisbinding version, as it will be automatically matched to the version that does not support geoprocessing execution. 

Installation message for arcgisbinding 301
Upgrading to arcgisbinding version 301 for R version 4.0.X and 4.1.X.
Installation through the Geoprocessing tab
Installing arcgisbinding from scratch with an unsupported R version will automatically install arcgisbinding 301.

If you still try to run a R-based geoprocessing tool on an unsupported version of R, the first time there will be a pop-up error message that will advise you to upgrade to another R version in which this functionality is supported, as shown in the screenshot below. 

Error message when using R script tool
Running a R-based geoprocessing tool for the first time will trigger a pop-up window with an error message if using R versions 4.0.X or 4.1.X.

This error message will only be shown once, and subsequent attempts of running a R-based geoprocessing tool will result in a runtime error.

Runtime error
Subsequent runs will throw a runtime error.

If your specific project requires R versions 4.0.X and 4.1.X, you can still use the R-ArcGIS bridge for all other functionalities, but if you need to create a geoprocessing tool from your R script, then we advise you to upgrade your R version to 4.2.0 or later.


The RArcGIS Bridge is fully functional in the newly released ArcGIS Pro 3.0. To integrate the R-ArcGIS Bridge with ArcGIS Pro 3.0, please make sure you upgrade your R version to 4.2.0 or later and install arcgisbinding version  

In addition, R-based geoprocessing tool execution is not supported in R versions within 4.0 and 4.1 and the corresponding arcgisbinding package version will advise you through a pop-up error message to upgrade your R version when attempting to run a geoprocessing tool. This error message will only be shown once, and later executions will result in a runtime error.  Therefore, we advise you to use the arcgisbinding package with R versions 4.2.0 or later. 

Learn more about the R-ArcGIS Bridge on our product page and let us know of any feedback you may have on our Esri Community page. 

About the authors

Tania Lopez-Cantu is a Senior Product Engineer in the Raster Analysis team at Esri. She works with raster and scientific multidimensional data to solve problems in water resources management and climate change impacts. Her role at Esri includes conducting research, building and maintaining tools for hydrological and terrain analysis. She holds a Ph.D. in Civil and Environmental Engineering from Carnegie Mellon University.

Stella(Xintian) Li is a Product Engineer on Esri's Spatial Statistics team. As an urban enthusiast who has a strong passion for spatial statistics and data science, Stella enjoys finding solutions to urban, social, and environmental problems with data-driven methods. Her role at Esri includes doing research, building and maintaining spatial data science tools and capabilities, and creating learning resources to help users better understand and utilize the tools.

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