Checking for non-preferred file/folder path names (may take a long time depending on the number of files/folders) ...
This resource contains some files/folders that have non-preferred characters in their name. Show non-conforming files/folders.
This resource contains content types with files that need to be updated to match with metadata changes. Show content type files that need updating.
| Authors: |
|
|
|---|---|---|
| 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 1008.5 MB | |
| Created: | Feb 26, 2026 at 3:12 p.m. (UTC) | |
| Last updated: | Mar 03, 2026 at 10:24 p.m. (UTC) | |
| Citation: | See how to cite this resource | |
| Content types: | CSV Content |
| Sharing Status: | Public |
|---|---|
| Views: | 41 |
| Downloads: | 13 |
| +1 Votes: | Be the first one to this. |
| Comments: | No comments (yet) |
Abstract
This resource holds sample datasets and work products from NEON LEWI 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.
Subject Keywords
Coverage
Spatial
Temporal
| Start Date: | |
|---|---|
| End Date: |
Content
Additional Metadata
| Name | Value |
|---|---|
| Site Description | Lewis Run (LEWI) is an aquatic NEON field site located about 60 miles west of Washington, D.C. in Clarke County, Virginia. Lewis Run is a small wadeable stream that drains a 11.9 km2 (2940 acre) watershed. The majority of the stream reach flows past and through land managed by Casey Trees, a nonprofit organization that raises trees for planting in and around the Washington, D.C. area. The surrounding region is characterized by general land use types including successional fields, pastures, woodlands, and small ponds. This site is located within NEON's Mid-Atlantic Domain (D02), a densely populated region bounded by the Atlantic Ocean on the east and stretching down the Eastern Seaboard from southern New Jersey to northern Georgia. The Mid-Atlantic Domain includes one other aquatic site and two terrestrial sites. LEWI is located near the BLAN terrestrial site. Source:https://www.neonscience.org/field-sites/lewi |
Related Geospatial Features
This HydroShare resource is linked to the following geospatial features
Learn more about Related Geospatial Features
We highly recommend that you add Spatial Coverage to this resource before searching for related geospatial features. Otherwise query times can be excessive.
| ${value.text} | ${value.text} |
Click a point to search for features that overlap with that location.
Select a feature for more information.
Related Resources
| 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
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
Comments
There are currently no comments
New Comment