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Predicting fire-induced individual tree mortality at the landscape level using fire intensity and airborne laser scanning data

Journal :

Remote Sensing of Environment, 331, 115007

Authors:

Aaron M. Sparks, Ryan Armstrong, Alistair M.S. Smith, Steve Scharosch, Mark V. Corrao and Thomas Montzka

Predicting fire-induced individual tree mortality at the landscape level using fire intensity and airborne laser scanning data

Aaron M. Sparks, Ryan Armstrong, Alistair M.S. Smith, Steve Scharosch, Mark V. Corrao, Thomas Montzka, Predicting fire-induced individual tree mortality at the landscape level using fire intensity and airborne laser scanning data, Remote Sensing of Environment, Volume 331, 2025, 115007, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2025.115007.

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Journal:

Remote Sensing, 18(4), 547

Airborne Laser Scanning for Large-Scale Forest Carbon Quantification: A Comparison of LiDAR Single-Tree and Field- Based Methods

Comparison of Field Sampling- and Airborne Laser Scanning-Derived Stand-Level Inventories in a Mixed Conifer Forest and Volume Validation Using Log Scaling Data

Journal:

Remote Sens, 17, 1761

Predicting fire-induced individual tree mortality at the landscape level using fire intensity and airborne laser scanning data

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Airborne Laser Scanning for Large-Scale Forest Carbon Quantification: A Comparison of LiDAR Single-Tree and Field- Based Methods

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Comparison of a Continuous Forest Inventory to an ALS-Derived Digital Inventory in Washington State