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PEP2026: USGS MD Lake Serene at Edgewood Image Data

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Owners:		This resource does not have an owner who is an active HydroShare user. Contact CUAHSI (help@cuahsi.org) for information on this resource.
Type:	Resource
Storage:	The size of this resource is 884.9 MB
Created:	Mar 02, 2026 at 3:58 p.m. (UTC)
Last updated:	Mar 03, 2026 at 10:31 p.m. (UTC)
Citation:	See how to cite this resource

Sharing Status:	Public
Views:	29
Downloads:	4
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Abstract

This resource holds sample datasets and work products from USGS- 0158175720 Lake Serene at Edgewood site from groups participating in the PEP2026 Workshop. Pixels to Enviro Patterns 2026 (PEP2026), is a two-day workshop at the University of Nebraska–Lincoln (Nebraska), where cameras, AI, and storytelling converge for scientific discovery. Held March 7–8 at Hardin Hall on East Campus, PEP 2026 invites researchers, educators, and creatives to explore open imagery and dive into hands-on learning with GRIME AI software. Collaborate on mini-projects to turn pixels into environmental patterns that drive scientific inquiry and narratives. Whether you’re passionate about water, phenology, artificial intelligence, or communication, this is your chance to connect, create, and be inspired.

Datasets are curated for use with GRIME AI software, which is available as a Conda package (https://anaconda.org/channels/GRIMELab/packages/grime-ai/overview) with source code and Wiki on GitHub (https://github.com/JohnStranzl/GRIME-AI/wiki) GRIME AI is free, open-source software (Apache 2.0). GRIME AI leverages Meta's Segment Anything 2 (SAM2) model for image segmentation and also facilitates the entire data science workflow, from data retrieval to model deployment.

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Coverage

Spatial

Coordinate System/Geographic Projection:

WGS 84 EPSG:4326

Coordinate Units:

Decimal degrees

Place/Area Name:

Lake Serene at Edgewood

Longitude

-76.3106°

Latitude

39.4322°

Temporal

Start Date:
End Date:

Content

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Related Resources

This resource belongs to the following collections:

Title	Owners	Sharing Status	My Permission
PEP2026: GRIME AI Data and Products for the Pixels to Environmental Patterns Workshop	Troy Gilmore · Nawaraj Shrestha · John Stranzl · Zach Nickerson	Public & Shareable	Open Access

How to Cite

Shrestha, N., T. E. Gilmore, Z. Nickerson, J. Stranzl (2026). PEP2026: USGS MD Lake Serene at Edgewood Image Data, HydroShare, http://www.hydroshare.org/resource/dbe8fcf6b34f47be950721695e7ae166

This resource is shared under the Creative Commons Attribution CC BY.

http://creativecommons.org/licenses/by/4.0/

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