Continental-scale mapping of forest tree density in North America using remote sensing and deep learning with uncertainty quantification

Link: https://hdl.handle.net/11681/50360

Report Number: ERDC/EL MP-26-39

Title: Continental-scale mapping of forest tree density in North America using remote sensing and deep learning with uncertainty quantification

By Mustak Ahmad, Yun Tang, Andrew J. Lister, Javier G.P. Gamarra, William G. Powell, Nathan R. Beane, Wook Jin Choi, Ankita Mitra, Amit Kumar, Anibal Cuchietti, Alain Paquette, Eric Searle, Jiaxin Chen, Han Y.H. Chen, Frans Bongers, Jorge A. Meave, Mario Guevara, Aylin Barreras, José Armando Alanís de la Rosa, Rafael Mayorga Saucedo, Rubi Angélica Cuenca Lara, César Moreno García, Carlos Isaías Godínez Valdivia, Carina Edith Delgado Caballero, Maria de los Ángeles Soriano Luna, Metzli Ileana Aldrete Leal, Sandra Liliana Medina Casillas, Johny Romero Correa, Sergio Armando Villela Gaytán, J. Javier Corral Rivas, José Daniel Vega-Nieva, Jaime Briseño-Reyes, Pablito Marcelo López-Serrano, Tom M. Fayle, Jan Altman, Daniel J. Johnson, and Jingjing Liang

Approved for Public Release; Distribution is Unlimited

August 2026

22 pages / 10.29 MB

*Journal: https://doi.org/10.1016/j.fecs.2026.100466