UMD Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/3
New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a given thesis/dissertation in DRUM.
More information is available at Theses and Dissertations at University of Maryland Libraries.
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Item Free Space: Envisioning the Low Earth Orbit Metropolis(2021) Mazer, Andrew Joseph; May, Lindsey; Dawkins, Casey; Architecture; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This thesis posits a permanent, free space settlement and a space-based regional plan as the first step in sustainable and ethical settlement beyond Earth. The settlement paradigm explores modular and redundant construction and planning techniques that could be scaled and replicated to achieve long-range missions of exploration and long-term space settlement. A systems-based strategy within Low Earth Orbit provides the first architectural steppingstone for humans to realize themselves as a multi-planetary species. Space hosts a plethora of untapped and un-realized resources that have yet to be imagined for the betterment of life on Earth. As a result, it is imperative to plan and to think about what the consequences a permanent settlement in outer space could mean for life on Earth. In exploration, this thesis sets forth a strategy to ensure outer space and its resources are used fairly, responsibly, and justly, and access is promoted equitably, ethically, and morally to all who have a hand in a globally collaborative human agenda.Item Avian/Human Architecture(2013) Atalig, Jane Rase; Ambrose, Michael A; Rockcastle, Garth; Architecture; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Belonging to the Commonwealth of the Northern Mariana Islands (CNMI), Rota, the southernmost island in the Northern Mariana Island archipelago, is home to a naturally protected avian sanctuary that hosts critically endangered species of birds found nowhere else in the world. The island's unique environment has attracted the interest of academic institutions and international visitors focused on learning more about the island's ecosystem. While attempting to address the CNMI's tourism issues, the most recent tourism master plan for the islands, NMI Tourism Master Plan 2012-2016, fails to recognize Rota as a major candidate for economic growth. This thesis proposes a solution to both address tourism issues as well as educate locals and visitors of the importance of ecological sustainability through critical and creative exploration of the interaction between avian and human architecture.Item DESIGNING FOR BIODIVERSITY TO INFLUENCE HABITAT ON A GREEN ROOF IN THE DISTRICT OF COLUMBIA(2012) Myers, Chris H.; Ellis, Christopher D.; Plant Science and Landscape Architecture (PSLA); Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This paper will discuss design elements to enhance pollinator and avian diversity on a green roof in the District of Columbia. Biodiversity trends on green roofs in Canada, the United Kingdom, Switzerland, and the United States are discussed. Focusing on North America, reconciliation ecology is explored through the use of case studies. The design process for designing a green roof is divided into three parts: identifying program goals, site analysis, and design concept. Design guidelines are extrapolated from conservation literature for the creation of green roofs that support pollinator and avian habitat. These "bioroofs" will be draped over the United States Coast Guard Headquarters building which will serve as a template for creating a green roof to target the least tern, the killdeer, the butterfly and the bee, in the District of Columbia.Item MAPPING FOREST STRUCTURE AND HABITAT CHARACTERISTICS USING LIDAR AND MULTI-SENSOR FUSION(2011) Swatantran, Anuradha; Dubayah, Ralph; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation explored the combined use of lidar and other remote sensing data for improved forest structure and habitat mapping. The objectives were to quantify aboveground biomass and canopy dynamics and map habitat characteristics with lidar and /or fusion approaches. Structural metrics from lidar and spectral characteristics from hyperspectral data were combined for improving biomass estimates in the Sierra Nevada, California. Addition of hyperspectral metrics only marginally improved biomass estimates from lidar, however, predictions from lidar after species stratification of field data improved by 12%. Spatial predictions from lidar after species stratification of hyperspectral data also had lower errors suggesting this could be viable method for mapping biomass at landscape level. A combined analysis of the two datasets further showed that fusion could have considerably more value in understanding ecosystem and habitat characteristics. The second objective was to quantify canopy height and biomass changes in in the Sierra Nevada using lidar data acquired in 1999 and 2008. Direct change detection showed overall statistically significant positive height change at footprint level (ΔRH100 = 0.69 m, +/- 7.94 m). Across the landscape, ~20 % of height and biomass changes were significant with more than 60% being positive, suggesting regeneration from past disturbances and a small net carbon sink. This study added further evidence to the capabilities of waveform lidar in mapping canopy dynamics while highlighting the need for error analysis and rigorous field validation Lastly, fusion applications for habitat mapping were tested with radar, lidar and multispectral data in the Hubbard Brook Experimental Forest, New Hampshire. A suite of metrics from each dataset was used to predict multi-year presence for eight migratory songbirds with data mining methods. Results showed that fusion improved predictions for all datasets, with more than 25% improvement from radar alone. Spatial predictions from fusion were also consistent with known habitat preferences for the birds demonstrating the potential of multi- sensor fusion in mapping habitat characteristics. The main contribution of this research was an improved understanding of lidar and multi-sensor fusion approaches for applications in carbon science and habitat studies.