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dc.contributor.advisorDubayah, Ralphen_US
dc.contributor.authorTang, Haoen_US
dc.date.accessioned2015-06-26T05:33:05Z
dc.date.available2015-06-26T05:33:05Z
dc.date.issued2015en_US
dc.identifierhttps://doi.org/10.13016/M2D626
dc.identifier.urihttp://hdl.handle.net/1903/16593
dc.description.abstractLeaf Area Index (LAI) and Vertical Foliage Profile (VFP) are among the most important forest structural parameters, and characterization of those parameters in high biomass forests remains a major challenge in passive remote sensing due to signal saturation problem. Recently an active remote sensing technology, light detection and ranging (lidar), has shown a great promise in this task recognizing its accuracy in measuring aboveground biomass and canopy height. This dissertation further expands current application of lidar on ecosystem monitoring, and explores the capacity of deriving LAI and VFP from lidar data in particular. The overall goal of this study is to derive large scale forest LAI and VFP using data from the Geoscience Laser Altimeter System (GLAS) on board of ICESat, and provide a framework of validating such LAI products from plot level to global scale. To achieve this goal, a physically based Geometry Optical and Radiative Transfer (GORT) model was first developed using high quality airborne waveform lidar data over a tropical rainforest in La Selva, Costa Rica. The excellent agreement between lidar data and field destructively sampled data demonstrated the effectiveness of the Lidar-LAI model and suggested large footprint waveform lidar can provide accurate vertical LAI profile estimates that do not saturate even at the highest possible LAI levels. Next, an intercomparative study of ground-based, airborne and spaceborne retrievals of total LAI was conducted over the conifer-dominated forests of Sierra Nevada in California. Good relationships were discovered in their comparisons, following a scaling-up validation strategy where ground-based LAI observations were related to aircraft observations of LAI, which in turn were used to validate GLAS LAI derived from coincident data. Successful implementation of this strategy can pave the way for the future recovery of vertical LAI profiles globally. LAI and VFP products were then derived over both the entire state of California and Contiguous United States as an efficacy demonstration of the method. These products were the first ever attempts to obtain large scale estimates of LAI and VFP from lidar observations. Such forest structural measurement can be used not only to quantify carbon stock and flux of terrestrial ecosystem, but also to provide spatial information of specie abundance in biodiversity. Results from this study can also greatly help broaden scientific applications of future spaceborne lidar missions (e.g. ICESat-2 and GEDI).en_US
dc.language.isoenen_US
dc.titleLidar Remote Sensing of Vertical Foliage Profile and Leaf Area Indexen_US
dc.typeDissertationen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.contributor.departmentGeographyen_US
dc.subject.pqcontrolledRemote sensingen_US
dc.subject.pqcontrolledGeographyen_US
dc.subject.pquncontrolledForest Structureen_US
dc.subject.pquncontrolledLAIen_US
dc.subject.pquncontrolledLidaren_US
dc.subject.pquncontrolledRemote Sensingen_US


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