Vertical structure and aboveground biomass of tropical forests from lidar remote sensing

摘要: approved: _____________________________________________________ Beverly E. Law Methods for obtaining accurate, spatially explicit estimates of biomass density in tropical forests are required to reduce uncertainties the global carbon cycle, and support international climate agreements emerging markets. Threedimensional (3-D) remote sensing techniques sensitive vertical structure vegetation provide a unique opportunity mapping monitoring forest stocks across large areas tropics. However, approaches estimation from remotely sensed have yet be fully developed deliver accuracy. In this research, we use airborne laser scanning (ALS), space-based lidar observations (ICESat/GLAS), detailed situ measurements made at Tapajos National Forest, Brazil, advance methods regions structure. The overall objectives were (1) test refine extraction structural information data; (2) determine accuracy relation field structure; (3) develop validate structure-based models optimal prediction aboveground biomass. Because begin with biomass, plot data collected also used gain better understanding uncertainty associated plot-level obtained specifically calibration data. This included an evaluation error resulting spatial disagreement between (i.e., co-location error), introduced when accounting temporal differences acquisition. Results show that new approach based on Fourier transforms profiles significantly improves predictions ranging 2 538 Mg ha primary secondary forests. Data two different Amazon demonstrate method range conditions. improvement performance was consistent sites integrated multi-stage scaling strategy produce wall-to-wall map area Amazon. ©Copyright by Fabio Guimaraes Goncalves November 21, 2014 All Rights Reserved Vertical Structure Aboveground Biomass Tropical Forests Lidar Remote Sensing