Kevin Butler
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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
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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The Science of Where: A GIS Derived Climatology of Severe Weather Warnings, Watches and Advisories

A GIS Derived Climatology of Severe Weather Warnings, Watches and Advisories

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The Science of Where (and When): A GIS derived climatology of hail

Apply the science of where (and when) to build a climatology of severe hail events.

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The Science of Where: Discovering Alternate Climate Zones through Machine Learning

Combine the power of GIS, spatial machine learning and rich climate data to understand current and future climate patterns.

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Accessing Multidimensional Scientific Data using Python

  With the 10.3 release, a new Python library, netCDF4, began shipping as part of the ArcGIS platform.  netCDF4 allows you to easi...

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