Geography
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Item ENHANCEMENT OF A CANOPY REFLECTANCE MODEL FOR UNDERSTANDING THE SPECULAR AND SPECTRAL EFFECTS OF AN AQUATIC BACKGROUND IN AN INUNDATED TIDAL MARSH(2012) Turpie, Kevin Ross; Kearney, Michael S.; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The presence of water produces unique specular and spectral characteristics in an inundated tidal marsh canopy. The aquatic substrate can affect conventional attempts to retrieve canopy characteristics, such as structure information (e.g., canopy height, leaf area index, etc.) or plant species composition. The background reflectance can also influence spectral analysis of plant characteristics based on hyperspectral data. A model to account for the aquatic substrate would be useful to understanding spectral field measurements and remote sensing of this type of land cover. To that end, an existing vegetation canopy reflectance model is combined with an aquatic background model to account for the effects of an aquatic substrate on the top-of-canopy bidirectional reflectance. The aquatic background model attempts to account for the optical effects of an inundated marsh substrate through the inclusion of first-principle models of water reflectance. The enhanced model is applied to multi-angular reflectance measured along transects of a brackish marsh canopy. This allows us to explore whether the enhanced model can be used in retrieving the leaf area index (LAI) using non-destructive, above- canopy measurements. Then the original and the enhanced canopy reflectance models are compared with multi-angular reflectance data to test whether the change is effective in capturing specular effects of an inundated canopy. Furthermore the reflectance data and model are used to identify the influence of the background on the spectral characteristics of the canopy pertaining to vegetation. The spectral signature produced by the aquatic background model is quite different from the spectra of dry or unsaturated soil, which would be associated with terrestrial applications. The aquatic background model signature is used to explain the features seen in a field spectroscopy experiment, where canopy inundation levels were artificially raised. This project demonstrates the utility of developing a vegetation canopy model with an aquatic background and identifies challenges and directions for improved performance.Item Idenfitying and Understanding North American Carbon Cycle Perturbations from Natural and Anthropogenic Disturbances(2008-05-05) Neigh, Christopher Sean; Townshend, John R.G.; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Carbon dioxide accumulating in our atmosphere is one of the most important environmental threats of our time. Humans and changing climate, separately or in concert, have affected global vegetation, biogeochemical cycles, biophysical processes, and primary production. Recent studies have found temporary carbon stores in North American vegetation due to land-cover land-use change, but have yet to characterize regional mechanisms across the continent. This research implemented multi-resolution remote sensing data, coupled with ecosystem simulations, to determine the importance of fine-scale disturbance in our understanding of dynamics that drove and/or perturbed carbon sequestration in North America from 1982 through 2005. The research involved three components: 1) identified large regions with natural and anthropogenic vegetation disturbances; 2) determined causes of disturbances with high-spatial resolution data and mapped associative fine-scale land cover dynamics; and 3) used prior empirical observations in simulations to quantify mechanisms that altered carbon pathways. Investigation of normalized difference vegetation index data from the NOAA series of Advanced Very High Resolution Radiometers found regions in North America that experienced marked increases in photosynthetic capacity at various times from 1982 to 2005. Inspection of anomalies with multi-resolution data from Landsat, IKONOS, aerial photography, and ancillary data revealed a wide range of causes: climatic influences; severe drought and subsequent recovery; irrigated agriculture expansion; insect outbreaks followed by logging and subsequent regeneration; and forest fires with subsequent regeneration. Fine-scale land cover change dynamics were included in Carnegie-Ames-Stanford approach simulations to enhance replication of carbon cycle processes found in empirical observations. Integration of multi-resolution remote sensing data, with carbon ecosystem process modeling, improved regional understanding and accounting of dynamic fine-scale spatial-temporal North American ecosystem carbon balance by a total of ~10 − 250 teragrams of carbon. Coarse resolution simulations could fail to identify important local scale drivers which impact regional carbon balance.