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Full-Text Articles in Forest Sciences
How Do Long-Term Above-Ground Biomass Dynamics Vary Between Different Forest Stand Types At Harvard Forest?, Maya Y. Chandar-Kouba
How Do Long-Term Above-Ground Biomass Dynamics Vary Between Different Forest Stand Types At Harvard Forest?, Maya Y. Chandar-Kouba
Honors Projects
Monitoring forest carbon storage is necessary in accurately modelling the global carbon cycle. In the Northeast, terrestrial forests represent a major carbon sink with above-ground biomass (AGB) accounting for 40% of stored forest carbon. Therefore, understanding how AGB varies spatiotemporally is essential in predicting future carbon storage. Repeated measurements in permanent, long-term plots provide an opportunity to examine how carbon stored in AGB is changing over time. I used 29 years of data from the Harvard Forest Environmental Monitoring Systems (HF EMS) Site to determine how stand composition, intrinsic factors, and extrinsic environmental factors influenced rates of carbon storage in …
Discrete Return Lidar-Based Prediction Of Leaf Area Index In Two Conifer Forests, Jennifer L.R. Jensen, Karen S. Humes, Lee A. Vierling, Andrew T. Hudak
Discrete Return Lidar-Based Prediction Of Leaf Area Index In Two Conifer Forests, Jennifer L.R. Jensen, Karen S. Humes, Lee A. Vierling, Andrew T. Hudak
USDA Forest Service / UNL Faculty Publications
Leaf area index (LAI) is a key forest structural characteristic that serves as a primary control for exchanges of mass and energy within a vegetated ecosystem. Most previous attempts to estimate LAI from remotely sensed data have relied on empirical relationships between field-measured observations and various spectral vegetation indices (SVIs) derived from optical imagery or the inversion of canopy radiative transfer models. However, as biomass within an ecosystem increases, accurate LAI estimates are difficult to quantify. Here we use lidar data in conjunction with SPOT5-derived spectral vegetation indices (SVIs) to examine the extent to which integration of both lidar and …