Automated Detection of Cloud and Cloud Shadow in Single-Date Landsat Imagery Using Neural Networks and Spatial Post-Processing. - M. Joseph Hughes; Daniel J. Hayes (Remote. Sens., 2014)

The Use of Three-Dimensional Convolutional Neural Networks to Interpret LiDAR for Forest Inventory. - Elias Ayrey; Daniel J. Hayes (Remote. Sens., 2018)

A UAS Platform for Assessing Spectral, Structural, and Thermal Patterns of Arctic Tundra Vegetation. - Ran Meng; Dedi Yang; Andrew McMahon; Wouter Hantson; Dan Hayes 001; Amy L. Breen; Shawn P. Serbin (IGARSS, 2019)

A Multi-Sensor Unoccupied Aerial System Improves Characterization of Vegetation Composition and Canopy Properties in the Arctic Tundra. - Dedi Yang; Ran Meng; Bailey D. Morrison; Andrew McMahon; Wouter Hantson; Daniel J. Hayes; Amy L. Breen; Verity G. Salmon; Shawn P. Serbin (Remote. Sens., 2020)

Synthesizing Disparate LiDAR and Satellite Datasets through Deep Learning to Generate Wall-to-Wall Regional Inventories for the Complex, Mixed-Species Forests of the Eastern United States. - Elias Ayrey; Daniel J. Hayes; John Kilbride; Shawn Fraver; John A. Kershaw; Bruce D. Cook; Aaron Weiskittel (Remote. Sens., 2021)

Predicting Water Stress in Wild Blueberry Fields Using Airborne Visible and Near Infrared Imaging Spectroscopy. - Catherine Chan; Peter R. Nelson; Daniel J. Hayes; Yong-Jiang Zhang; Bruce Hall (Remote. Sens., 2021)