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Plant Sciences

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USDA Forest Service / UNL Faculty Publications

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Lidar

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Evaluation Of The Modis Lai Product Using Independent Lidar-Derived Lai: A Case Study In Mixed Conifer Forest, Jennifer L.R. Jensen, Karen S. Humes, Andrew T. Hudak, Lee A. Vierling, Eric Delmelle Jan 2011

Evaluation Of The Modis Lai Product Using Independent Lidar-Derived Lai: A Case Study In Mixed Conifer Forest, Jennifer L.R. Jensen, Karen S. Humes, Andrew T. Hudak, Lee A. Vierling, Eric Delmelle

USDA Forest Service / UNL Faculty Publications

This study presents an alternative assessment of the MODIS LAI product for a 58,000 ha evergreen needleleaf forest located in the western Rocky Mountain range in northern Idaho by using lidar data to model (R2=0.86, RMSE=0.76) and map LAI at higher resolution across a large number of MODIS pixels in their entirety. Moderate resolution (30 m) lidar-based LAI estimates were aggregated to the resolution of the 1-km MODIS LAI product and compared to temporally-coincident MODIS retrievals. Differences in the MODIS and lidar-derived values of LAI were grouped and analyzed by several different factors, including MODIS retrieval algorithm, sun/sensor …


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 Jan 2008

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 …