Assessing North American forest disturbance from the landsat archive. - Jeffrey G. Masek; Robert E. Wolfe; Forrest G. Hall; Samuel Goward; Chengquan Huang; Warren B. Cohen; Robert E. Kennedy; Scott Powell; Sean Healey; Gretchen Moisen (IGARSS, 2007)

Consistency Of Forest Presence And Biomass Predictions Modeled Across Overlapping Spatial And Temporal Extents. - Mark D. Nelson; Sean Healey; Warren Keith Moser; Jeffrey G. Masek; Warren B. Cohen (Math. Comput. For. Nat. Resour. Sci., 2011)

Evaluating the Remote Sensing and Inventory-Based Estimation of Biomass in the Western Carpathians. - Magdalena Main-Knorn; Gretchen G. Moisen; Sean P. Healey; William S. Keeton; Elizabeth A. Freeman; Patrick Hostert (Remote. Sens., 2011)

Implementation of the LandTrendr Algorithm on Google Earth Engine. - Robert E. Kennedy; Zhiqiang Yang; Noel Gorelick; Justin Braaten; Lucas Cavalcante; Warren B. Cohen; Sean Healey (Remote. Sens., 2018)

Generalized Hierarchical Model-Based Estimation for Aboveground Biomass Assessment Using GEDI and Landsat Data. - Svetlana Saarela; Sören Holm; Sean P. Healey; Hans-Erik Andersen; Hans Petersson; Wilmer Prentius; Paul L. Patterson; Erik Næsset; Timothy G. Gregoire; Göran Ståhl (Remote. Sens., 2018)

Diversity of Algorithm and Spectral Band Inputs Improves Landsat Monitoring of Forest Disturbance. - Warren B. Cohen; Sean P. Healey; Zhiqiang Yang; Zhe Zhu; Noel Gorelick (Remote. Sens., 2020)

Highly Local Model Calibration with a New GEDI LiDAR Asset on Google Earth Engine Reduces Landsat Forest Height Signal Saturation. - Sean P. Healey; Zhiqiang Yang; Noel Gorelick; Simon Ilyushchenko (Remote. Sens., 2020)

A Comprehensive Forest Biomass Dataset for the USA Allows Customized Validation of Remotely Sensed Biomass Estimates. - James Menlove; Sean P. Healey (Remote. Sens., 2020)