The scientist’s investigation covers issues in Remote sensing, Lidar, Vegetation, Canopy and Tree canopy. His biological study spans a wide range of topics, including Tree, Woodland, Leaf area index and Normalized Difference Vegetation Index. His Lidar study incorporates themes from Biomass, Ecology, Forest management and Ecosystem.
His Vegetation study combines topics in areas such as Biomass and Air pollution. His Canopy research integrates issues from Photosynthesis, Chlorophyll and Chlorophyll a. His study looks at the intersection of Tree canopy and topics like Understory with Snag, Wildlife, Wildlife management and Forest ecology.
Lee A. Vierling mainly investigates Remote sensing, Vegetation, Ecology, Lidar and Canopy. His studies in Remote sensing integrate themes in fields like Shrub, Ecosystem, Leaf area index and Normalized Difference Vegetation Index. His Leaf area index research focuses on Enhanced vegetation index and how it relates to Tree canopy.
His Vegetation study integrates concerns from other disciplines, such as Hydrology, Terrain, Thematic Mapper and Satellite imagery. His work in Lidar tackles topics such as Forest inventory which are related to areas like Basal area. His Canopy research includes elements of Photosynthesis, Photosynthetically active radiation, Atmospheric sciences and Crown.
His primary areas of study are Remote sensing, Ecology, Lidar, Tundra and Vegetation. His Remote sensing research is multidisciplinary, incorporating perspectives in Forest management, Terrain, Ecosystem and Leaf area index. His study in Ecosystem is interdisciplinary in nature, drawing from both Deforestation and Normalized Difference Vegetation Index.
He combines subjects such as Tree and Forest inventory with his study of Lidar. The Tundra study combines topics in areas such as Shrub, Canopy, Ecotone and Photosynthesis. His work deals with themes such as Spatial heterogeneity, Agronomy and Chlorophyll fluorescence, which intersect with Vegetation.
Lee A. Vierling spends much of his time researching Lidar, Remote sensing, Ecology, Biomass and Shrub. His research investigates the connection with Lidar and areas like Forest inventory which intersect with concerns in Mean squared error. His research in Remote sensing intersects with topics in Leaf area index, Terrain, Ecosystem and Vegetation.
Many of his research projects under Ecology are closely connected to Environmental niche modelling with Environmental niche modelling, tying the diverse disciplines of science together. Lee A. Vierling has included themes like Regression analysis, Grain quality, Crop yield and Phenology in his Biomass study. His research investigates the connection between Shrub and topics such as Tundra that intersect with issues in Canopy, Atmospheric sciences and Biome.
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Putting the "landscape" in landscape genetics.
Lidar: shedding new light on habitat characterization and modeling
Kerri T Vierling;Lee A Vierling;William A Gould;Sebastian Martinuzzi.
Frontiers in Ecology and the Environment (2008)
A simple and effective radiometric correction method to improve landscape change detection across sensors and across time
Xuexia Chen;Lee Vierling;Don Deering.
Remote Sensing of Environment (2005)
Effects of habitat on GPS collar performance: using data screening to reduce location error
Jesse S. Lewis;Janet L. Rachlow;Edward O. Garton;Lee A. Vierling.
Journal of Applied Ecology (2007)
Mapping snags and understory shrubs for a LiDAR-based assessment of wildlife habitat suitability
Remote Sensing of Environment (2009)
Automated estimation of individual conifer tree height and crown diameter via two-dimensional spatial wavelet analysis of lidar data
Canadian Journal of Remote Sensing (2006)
Quantifying aboveground forest carbon pools and fluxes from repeat LiDAR surveys
Remote Sensing of Environment (2012)
Isoprene emission estimates and uncertainties for the central African EXPRESSO study domain
Alex Guenther;Bill Baugh;Guy Brasseur;Jim Greenberg.
Journal of Geophysical Research (1999)
Broadband, red-edge information from satellites improves early stress detection in a New Mexico conifer woodland
Beyond 3-D: The New Spectrum of Lidar Applications for Earth and Ecological Sciences
Remote Sensing of Environment (2016)
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