The buttons below provide links to the following datasets and tools:
WV Elevation and LiDAR Download Tool, which provides access to LiDAR data cross West Virginia using a web map/app.
2016 Land cover data for West Virginia derived from National Agriculture Imagery Program (NAIP) orthophotography using geographic objected-based image analysis and machine learning. This product is associated with the following Publication: "Large-Area, High Spatial Resolution Land Cover Mapping using Random Forests, GEOBIA, and NAIP Orthophotography: Findings and Recommendations".
R-based assessment tool, instructions, and example data associated with "Thematic Classification Accuracy Assessment with Inherently Uncertain Boundaries: An Argument for Center-Weighted Accuracy Assessment Metrics".
Data associated with "Semantic Segmentation Deep Learning for Extracting Surface Mine Extents from Historic Topographic Maps". The associated code can be found on GitHub (see link below).
Data associated with "Mapping the Topographic Features of Mining-Related Valley Fills using Mask R-CNN Deep Learning and Digital Elevation Data". An explanation of the data can be found here.
Data associated with our GitHub slope failure probabilistic occurence mapping repo, which provides example code in Python and R.
The following buttons link to GitHub repos associated with our projects.
Semantic Segmentation Topo Maps
Center-Weighted Accuracy Assessment
ML-Based Slope Failure Modeling
DL Tools in R
TLS Summarize on Sphere
This section provides links to data resources in West Virginia and across the country and globe.