Kevin Butler

Kevin Butler is a Product Engineer on Esri’s Analysis and Geoprocessing Team working as a liaison to the science community. He holds a Ph.D. in Geography from Kent State University. Over the past decade he has worked on strategic projects, partnering with customers and other members of the science community to assist in the development of large ecological information products such as the ecological land units, ecological marine units and ecological coastal units. His research interests include a thematic focus on spatial statistical analytical workflows, a methodological focus on spatial clustering techniques and a geographic focus on Puerto Rico and midwestern cities.

Posts by this author
Introducing Create Spatial Sampling Locations tool in ArcGIS Pro 3.3

The Create Spatial Sampling Locations tool allows you to create a continuous spatial sampling design using various sampling designs.

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Warmest ocean ever

Warmest ocean temperatures on record.

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SAS®-ArcGIS Bridge: Why Can’t I Find My SAS Data?

Define custom SAS libraries for use with the SAS®-ArcGIS Bridge geoprocessing tools.

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Looking to the future: Using GIS to model and predict population

We’ll share a source of historical county population data and introduce a set of exciting, easy-to-use forecasting tools available in ArcGIS Pro.

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The Science of Where: Workflows for exploring environmental security

In this three (or more) part blog series, I present examples of workflows in ArcGIS Pro to explore the many dimensions of environmental security.

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Targeting Areas for Conservation: New Biomass and Vulnerability Layers in Living Atlas

Analysis of biomass and the vulnerability of the landscape to change may serve as an initial way to survey for conservation areas.

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A Workflow for Creating Discrete Voxels

Perform nearest-neighbor interpolation to create discrete voxels.

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The Science of Where: A voxel visualization of smoke plume rise and dispersion

A voxel visualization of smoke plume rise and dispersion

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Evaluate County Readiness for Relaxing Stay-at-Home Measures

Proposed data-driven approach for mapping locations where relaxing COVID-19 stay-at-home measures might be appropriate.

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