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March 15, 2018 Previous day Next day

Esri and the National Science Foundation (NSF)-funded initiative known as EarthCube have today signed an informal Memorandum of Agreement (MOA). EarthCube was initiated by the NSF in 2011 to "transform geoscience research by developing cyberinfrastructure to improve access, sharing, visualization, and analysis of all forms of geosciences data and related resources." It is also a "quickly growing community of scientists across all geoscience domains, as well as geoinformatics researchers and data scientists."


As Esri Chief Scientist I have been pleased to serve on the EarthCube Liaison Team since 2014 and have built a "Mapping the Landscape" story map for the team which has been presented at several EarthCube-related meetings. We hope that this project will continue and merge with similar efforts at ESIP (Federation of Earth Science Information Partners), AGU (American Geophysical Union), and RDA (Research Data Alliance). The MOA was developed and signed by way of the Liaison Team and joint activities to be pursued include: 


  • mapping the larger geo/ cyberinfrastructure landscape and community (e.g., the story map) and further updating such a “landscape” map with organizations, initiatives, agencies, data facilities, etc., as well as assessing where EarthCube fits into this landscape;
  • semantic search, data mining-based metadata enrichment, persistent identifiers, geo-ontologies, and where possible, Linked Open Data;
  • more efficient access to data once found within searches, including the building of data publishing and geoprocessing services in the cloud to make data more accessible; and
  • removing barriers to data integration and interoperability, error and uncertainty of observations, spatial and temporal gaps in observations, and the related issues of user involvement and capacity building.


Toward this end, there will be the free exchange of emails, literature, computer code, and data where appropriate between Esri and the EarthCube community.

Esri Product Engineers/Data Scientists Shaun Walbridge, Noah Slocum, and Marjean Pobuda led the charge on a new peer-reviewed journal article about the open-source extension from Esri known as the Benthic Terrain Modeler (BTM). The paper describes the tools provided with the current release of BTM (v 3.0), highlighting powerful analytical workflows that combine ArcGIS with the Python scientific stack (aka SciPy), and the R statistical programming language (including the R-ArcGIS Bridge). BTM is used by scores of researchers around the world, and has been accessible for some time via ArcGIS Online at (nearly 7500 views).



High resolution remotely sensed bathymetric data is rapidly increasing in volume, but analyzing this data requires a mastery of a complex toolchain of disparate software, including computing derived measurements of the environment. Bathymetric gradients play a fundamental role in energy transport through the seascape. Benthic Terrain Modeler (BTM) uses bathymetric data to enable simple characterization of benthic biotic communities and geologic types, and produces a collection of key geomorphological variables known to affect marine ecosystems and processes. BTM has received continual improvements since its 2008 release; here we describe the tools and morphometrics BTM can produce, the research context which this enables, and we conclude with an example application using data from a protected reef in St. Croix, US Virgin Islands.


The paper is open access (#openscience) and part of a special issue on Marine Geomorphometry - - featuring other studies that use GIS, including ArcGIS, as well.