Large-Scale Color Aerial Photography as a Tool in Sampling for Mortality Rates
This study explores how large-scale color aerial photography can help sample forest mortality more efficiently. It explains methods for identifying mortality and green trees from aerial images and how these observations feed mortality rate estimates.
In detailed field tests, researchers examine how accurately 1- and 2-year mortality can be detected on color photographs, and how well tree species can be identified from imagery. The work covers photography choices, ground checks, interpretation in stereo, and the way data is translated into mortality rates and stand statistics. The goal is to improve mortality prediction and align aerial observations with ground truth.
- Learn how aerial photo interpretation distinguishes recent mortality from older events.
- See how sampling plots and subplot design support robust counts of green trees and dead trees.
- Understand the workflow from image capture to ground verification and data analysis.
- Discover how mortality rate models can integrate with stand inventory systems.
Ideal for readers of forestry research and applied remote sensing who want practical methods for estimating mortality and related stand characteristics using aerial imagery.