A tree-based approach to biomass estimation from remote sensing data in a tropical agricultural landscape
Due to increased global dominance of agricultural lands in the tropics, methods to establish biomass and carbon in agricultural areas are necessary for monitoring and modeling global C stocks. Since tropical agriculture often includes some tree cover, the study seeks to develop above ground biomass estimates using landscape-scale surveys with LiDAR in comparison to plot-level data.
research goals & methods
The study uses high-resolution (1.12m) LiDAR data across 9280 Ha of Panama’s Azuero Peninsula to model above ground biomass held in trees. These estimates are compared to estimates from plot studies (Asner et al, 2013).
conclusions & takeaways
Since tree cover may be 10% or lower in agricultural areas, plots are less able to capture a representative sample of trees than landscape-scale surveys. These methods are potentially more effective in areas of low canopy cover than in dense or stratified forest due to the limitations of digital segmentation of the canopy.
A tree-based approach to biomass estimation from remote sensing data in a tropical agricultural landscape. Remote Sensing of Environment. 2018;218:32–43. doi:10.1016/j.rse.2018.09.009..
- School of Forest Resources and Conservation, University of Florida
- Nelson Institute for Environmental Studies, University of Wisconsin-Madison
- Department of Biological Sciences, Boise State University
- Department of Global Ecology, Carnegie Institution for Science
- Smithsonian Tropical Research Institute, Panama