What's New for Spatial Analyst in ArcGIS Pro 3.5

JuanLaguna

The Spatial Analyst extension introduces new and enhanced capabilities in ArcGIS Pro 3.5. Highlights in this release include a new tool for surface analysis and some significant performance gains. Along with those comes several other improvements in capability. Read on to learn more

Where do I get it?

We released ArcGIS Pro 3.5 on May 13, 2025. Download and install it.

For an overview of the changes made for this release, have a look at the Your ArcGIS Pro Update (May 2025) blog post.

What’s changed for Spatial Analyst?

Here are the primary areas of improvements over the last release:

Distance analysis
Generalization analysis
Overlay analysis
Segmentation and Classification analysis
Surface analysis
Zonal analysis
Cell Size analysis environment
Suitability Modeler
Data conversion

Read on to learn more about the specific changes in various areas.

1. Distance analysis

For the Distance Accumulation and Distance Allocation tools, performance in some scenarios that use the Vertical Factor or Horizontal Factor parameters improved in ArcGIS Pro 3.5. In previous releases, while many scenarios performed well, certain input data characteristics could result in slow processing times. The changes we implemented in this release to address the issue resulted in those scenarios running up to 50 times faster.

The same updates made for the geoprocessing tools also apply to the corresponding raster functions.

2. Generalization analysis

The generalization tools Expand and Shrink have a small improvement that minimizes instances of cut-off cells appearing in the results for some narrow, wedge-shaped zones.

3. Overlay analysis

The Locate Regions tool now now runs on average twice as fast as before, and in some cases up to seven times faster. A primary application of this tool is to find the best locations from a suitability map that meets a subject's specific spatial requirements. However, this tool is CPU intensive, particularly as the number of seed locations and the resolution of growth parameters increase. For one input raster, the time taken to produce a result went from 28 minutes down to 4 minutes.

4. Segmentation and Classification analysis

A new parameter is available for the Create Accuracy Assessment Points tool, which you can use to create randomly sampled points for post classification accuracy assessment. The Minimum Point Distance parameter allows you to set a minimum distance between the reference points.

5. Surface analysis

Multiscale surface analysis

A new tool is available for the collection of tools that identify specific landscape characteristics of a surface raster at multiple scales. The Multiscale Surface Deviation tool calculates for each input cell the maximum surface deviation from the mean value across a range of spatial scales. The outputs from the tool record what this value is, and the other the scale at which it occurs. This new tool can also take advantage of GPU hardware, and could produce an output up to twice as fast compared to only using the CPU for calculations.

The following graphic illustrates the results from this new tool. The panel on the left is the input elevation surface raster. The middle panel is the output deviation raster. The ridges (darker blue shades) show larger positive deviations from the mean, while the valleys (darker brown shades) show larger negative deviation values. The panel on the right is the scale output. The white areas show locations of larger deviation values found at the larger scales. The darker areas show where larger deviation values are found at smaller scales.

You can use these deviations and scale raster to validate hydrologic features from your surface data.

Learn more in the Analyze terrain with the new Multiscale Surface tools in ArcGIS blog post by Sydney Walker.

Geomorphons

The Geomorphon Landforms surface tool is a very effective way to analyze terrain for applications from hydrologic studies to assessing landslide susceptibility. A new How Geomorphon Landforms works help topic provides more information to help you better understand how it calculates the output values and how to correlate those to common landform types.

6. Zonal analysis

For the Zonal Statistics and Zonal Statistics as Table tools, the default cell size behavior was updated.

These tools have an input that defines the shape of the zones, and an input that defines the values that will be measured within those zones. By default, these tools now apply the cell size of the value raster to a raster zone input. This follows a change made for feature zone inputs in an earlier release.

Since the value raster is the primary raster to drive the output results, this update will make the analysis more accurate. To modify the default behavior, use the Cell Size environment to specify a number, a raster dataset, or the Maximum of Inputs or Minimum of Inputs options.

7. Cell Size analysis environment

When doing raster analysis, it is important to pay attention to how the environment affects the analysis. In ArcGIS Pro 3.5, tools that honor the Cell Size environment support an empty option in both tool dialog boxes and the Python environment. This environment sets the output raster resolution in which the analysis will be performed.

It can be set to match another raster dataset, a numeric value, or to apply the maximum (coarsest) or minimum (finest) resolution of the inputs. The new default behavior enables tools that use Maximum of Inputs or another special setting as the default to continue to do so.

8. Suitability Modeler

While there is no new functionality specific to the Suitability Modeler, a new capability is available in ArcGIS Pro that you can apply to suitability analysis. Use the new Assign Weights by Pairwise Comparison tool in the Analysis toolbox to calculate weights for a series of input variables more objectively. You can then enter them as the weight criteria when preparing the suitability map.

9. Data conversion

While not a Spatial Analyst tool specifically, the Raster to Polygon tool is commonly used in workflows that produce an output as a polygon feature layer. This tool has enhanced performance when vectorizing large rasters. Depending on the data and the settings used, the conversion typically completes in less than half the time as before. In some cases, it can be dramatically faster. For example, the time the tool took to convert one raster went from 2 hours down to about 6 minutes. An upcoming blog post will cover this improvement in more detail.

Summary

We hope that you try out the new and improved things you can do with the Spatial Analyst toolbox for ArcGIS Pro 3.5.

If you have more questions, join in on the discussion on the Community page for Spatial Analyst here:

https://community.esri.com/t5/arcgis-spatial-analyst-questions/bd-p/arcgis-spatial-analyst-questions

To learn more about Spatial Analyst, here are some starting points:

The original blog was first published in the ArcGIS Blog, and can be found here:
https://www.esri.com/arcgis-blog/products/arcgis-pro/analytics/whats-new-for-spatial-analyst-in-arcg...