Geography Theses and Dissertations
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Item Land Use in Charles County(1962) Langen, John S.; Van Royen, W.; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, MD)The land use of Charles County does not basically differ from that in the past. Land in forest and land in farms are the two categories of land utilization. The great demand for tobacco on the overseas markets in the early days of the county's history, led to the introduction of this crop. Because of the favorable climate and soils, tobacco became soon the mainstay of the county's economy, a situation which still exists today. The purpose of the thesis was to determine which geographical factors and others accounted for the use of the land. In addition to field work, use was made of detailed statistical data. It was found, that the county could be divided into three sections. In the western section, land in forest was the dominating land use form. In the central section, land in forest and land in farms were about equal in areal extent, whereas in the eastern section, land in farms dominated. The reason was that soils in the western part became exhausted, and a shift to the eastern section took place. Landforms contributed much to the distribution of land in crops, especially for tobacco. Recently, a change in the use of the land is taking place. The encroachment of the Washington Metropolitan area, and the building of a major highway, connecting the North with the South, have induced farmers to sell their lands, which are converted into residential areas.Item Land Tenure, Property Ownership, and Home Mortgages in the Late Nineteenth Century: A Case Study of Baltimore's Germans(1976) Vill, Martha J.; Groves, Paul A.; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, MD)During the late nineteenth century the rapidly expanding urban population of the United States created an increased demand for housing. At the same time, mortgage money for the finance of home purchases was in short supply because of the availability of more lucrative investment opportunities elsewhere and because there were legal restrictions on the power of banks to lend money on real estate . Recent literature has emphasized the importance of property ownership among different components of the population, including immigrant groups. Little attention has been paid to the process of property acquisition or to the patterns of land tenure which resulted. An immigrant population, handicapped in numerous ways, was likely to have limited access to available mortgage financing, thereby limiting its ability to purchase property. Yet, the literature suggests that immigrants actively acquired property. This study examines some preliminary ideas about tenure patterns and home mortgages within immigrant residential areas, using a sample of Baltimore's Germans as a case study. The argument presented is that housing acquisition was facilitated by the activities of the immigrants themselves. In view of the restrictions on the supply of mortgage money, financing for property purchases had to come from sources independent of the city's major financial institutions, and the immigrants had to generate their own sources of capital. It was expected that tenants and landlords would have common national origins, another reflection of the immigrants' reliance on members of their own group for housing. Another expectation of the study was that Germans of different origins in Germany would exhibit different tenure patterns. Arguing that the term "German" was an imprecise indicator of national origins, and that the residential patterns of immigrants from different parts of Germany were distinct, it was expected that this diversity would also find expression in tenure patterns. The selection of the sample areas in the study was, therefore, conditioned by the need to isolate areas inhabited by Germans of diverse origins. Land tenure, property ownership, and relationships between landlords and tenants were analyzed. The hoped for differences in rates of property ownership did not materialize, and home ownership was not systematically related to age, income, or family employment. The findings do indicate, however, that home ownership was within the grasp of people with relatively low income. The mechanism which enabled home purchasers to obtain mortgages was the building and loan associations which were organized and directed by men whose origins, occupations, and residences reflected those of the associations' clientele. Thus, the hypothesis that immigrants generated their own mortgage funds was confirmed. The findings of the study concerning landlords and tenants further substantiate the argument that the provision of housing was accomplished by the immigrants themselves. Landlords' residences were close to the properties they rented, and there was a marked tendency for tenants to rent from landlords who shared their German origins.Item Washington, D.C. and the Growth of Its Early Suburbs : 1860-1920(1980) Levy, Anneli Moucka; Groves, Paul A.; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md)During the nineteenth century, the North American city greatly changed in size and internal structure. With the introduction of mass transportation, large scale suburbanization took place as one aspect of this change. Members of the evolving middle class not only wished to escape the pollution and congestion of the urban core, but also believed strongly in a 'rural ideal,' translated into a 'suburban ideal.' Urban changes and suburban growth were especially pronounced in industrial cities, and descriptions of conditions in these cities identify the accepted model of the spatial configuration of the metropolis existed in 1920. Examination of the growth of Washington D. C. between the Civil War and World War I indicates that the city shared few of the characteristics of the accepted urban model. Nevertheless, it exhibited distinct suburban movement connected with three major transport modes, including the steam railroad. The belief in the 'suburban ideal' was broadly based in Washington and therefore much variation was found among the city's suburban communities, even among those associated with the same transportation mode. Furthermore, in contrast to the suburban model, conditions in the suburban areas often did not compare favorably with those in the city. Even so, the suburbanization process accelerated from small beginnings, so that by 1920 the city displayed the local variant of the typical star-shaped pattern.Item Estimation of forest aboveground biomass and uncertainties by integration of field measurements, airborne LiDAR, and SAR and optical satellite data in Mexico(Springer Nature, 2018-02-21) Urbazaev, Mikhail; Thiel, Christian; Cremer, Felix; Dubayah, Ralph; Migliavacca, Mirco; Reichstein, Markus; Schmullius, ChristianeInformation on the spatial distribution of aboveground biomass (AGB) over large areas is needed for understanding and managing processes involved in the carbon cycle and supporting international policies for climate change mitigation and adaption. Furthermore, these products provide important baseline data for the development of sustainable management strategies to local stakeholders. The use of remote sensing data can provide spatially explicit information of AGB from local to global scales. In this study, we mapped national Mexican forest AGB using satellite remote sensing data and a machine learning approach. We modelled AGB using two scenarios: (1) extensive national forest inventory (NFI), and (2) airborne Light Detection and Ranging (LiDAR) as reference data. Finally, we propagated uncertainties from field measurements to LiDAR-derived AGB and to the national wall-to-wall forest AGB map. The estimated AGB maps (NFI- and LiDAR-calibrated) showed similar goodness-of-fit statistics (R2, Root Mean Square Error (RMSE)) at three different scales compared to the independent validation data set. We observed different spatial patterns of AGB in tropical dense forests, where no or limited number of NFI data were available, with higher AGB values in the LiDAR-calibrated map. We estimated much higher uncertainties in the AGB maps based on two-stage up-scaling method (i.e., from field measurements to LiDAR and from LiDAR-based estimates to satellite imagery) compared to the traditional field to satellite up-scaling. By removing LiDAR-based AGB pixels with high uncertainties, it was possible to estimate national forest AGB with similar uncertainties as calibrated with NFI data only. Since LiDAR data can be acquired much faster and for much larger areas compared to field inventory data, LiDAR is attractive for repetitive large scale AGB mapping. In this study, we showed that two-stage up-scaling methods for AGB estimation over large areas need to be analyzed and validated with great care. The uncertainties in the LiDAR-estimated AGB propagate further in the wall-to-wall map and can be up to 150%. Thus, when a two-stage up-scaling method is applied, it is crucial to characterize the uncertainties at all stages in order to generate robust results. Considering the findings mentioned above LiDAR can be used as an extension to NFI for example for areas that are difficult or not possible to access.Item TOWARDS OBJECT-BASED EVALUATION OF INDIVIDUAL FIRES AT GLOBAL SCALES(2019) Humber, Michael Laurence; Justice, Christopher O; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Fire is a complex biophysical variable that has shaped the land surface for over 400 million years and continues to play important roles in landscape management, atmospheric emissions, and ecology. Our understanding of global fire patterns has improved dramatically in recent decades, coincident with the rise of systematic acquisition and development of global thematic products based on satellite remote sensing. Currently, there are several operational algorithms which map burned area, relying on coarse spatial resolution sensors with high temporal frequencies to identify fire-affected surfaces. While wildfires have been analyzed over large areas at the pixel level, object-based methods can provide more detailed attributes about individual fires such as fire size, severity, and spread rate. This dissertation evaluates burned area products using object-based methods to quantify errors in burn shapes and to extract individual fires from existing datasets. First, a wall-to-wall intercomparison of four publicly available burned area products highlights differences in the spatial and temporal patterns of burning identified by each product. The results of the intercomparison show that the MODIS Collection 6 MCD64A1 Burned Area product mapped the most burned area out of the four products, and all products except the Copernicus Burnt Area product showed agreement with regard to temporal burning patterns. In order to determine the fitness of the MCD64A1 product for mapping fire shapes, a framework for evaluating the shape accuracy of individual fires was developed using existing object-based metrics and a novel metric, the “edge error”. The object-based accuracy assessment demonstrated that MCD64A1 preserves the fire shape well compared to medium resolution data. Based on this result, an algorithm for extracting individual fires from MCD64A1 data was developed which improves upon existing algorithms through its use of an uncertainty-based approach rather than empirically driven approaches. The individual fires extracted by this algorithm were validated against medium resolution data in Canada and Alaska using object-based metrics, and the results indicate the algorithm provides an improvement over similar datasets. Overall, this dissertation demonstrates the capability of coarse resolution burned area products to accurately identify individual fire shapes and sizes. Recommendations for future work include improving the quality assessment of burned area products and continuing research into identifying spatiotemporal patterns in fire size distributions over large areas.Item Characterizing tree species diversity in the tropics using full-waveform lidar data(2019) Marselis, Suzanne; Dubayah, Ralph; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Tree species diversity is of paramount value to maintain forest health and to ensure that forests are able to provide all vital functions, such as creating oxygen, that are needed for mankind to survive. Most of the world’s tree species grow in the tropical region, but many of them are threatened with extinction due to increasing natural and human-induced pressures on the environment. Mapping tree species diversity in the tropics is of high importance to enable effective conservation management of these highly diverse forests. This dissertation explores a new approach to mapping tree species diversity by using information on the vertical canopy structure derived from full-waveform lidar data. This approach is of particular interest in light of the recently launched Global Ecosystem Dynamics Investigation (GEDI), a full-waveform spaceborne lidar. First, successful derivation of vertical canopy structure metrics is ensured by comparing canopy profiles from airborne lidar data to those from terrestrial lidar. Then, the airborne canopy profiles were used to map five successional vegetation types in Lopé National Park in Gabon, Africa. Second, the relationship between vertical canopy structure and tree species richness was evaluated across four study sites in Gabon, which enabled mapping of tree species richness using canopy structure information from full-waveform lidar. Third, the relationship between canopy structure and tree species richness across the tropics was established using field and lidar data collected in 16 study sites across the tropics. Finally, it was evaluated how the methods and applications developed here could be adapted and used for mapping pan-tropical tree species diversity using future GEDI lidar data products.Item Parameterized and Machine Learning Methods for Estimating Evapotranspiration from Satellite Data(2019) Carter, Corinne Minette; Liang, Shunlin; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The studies in this dissertation present evaluation of and improvement to parametric and machine learning regression methods for estimating evapotranspiration from remote sensing. It includes three main parts. The first part is an assessment of parametric regression methods for obtaining evapotranspiration from vegetation index and other variables. It was found that including more variables tends to improve results, but the form of the regression formula does not make a large difference. Algorithm performance is not as good for wetland and agricultural sites as for other land cover types. Re-training of algorithms for those surface type results in some improvement. The second part consists of an evaluation of ten machine learning techniques for retrieval of evapotranspiration from surface radiation and several other variables. It is found that the best results are obtainable using all available input variables to train the bootstrap aggregation tree, random kernel, and two- and three- hidden layer neural network algorithms. Performance is again found to be weaker for wetland and agricultural surface types than for other surface types. However, separate training of the machine learning algorithms with data from those surface types does not significantly improve performance. The third part consists of further refinement to the machine learning algorithms and application of the bootstrap aggregation tree method to generate evapotranspiration maps of the continental United States for 2012. It is found that separating snow and non-snow data points improves performance. Performance for all tested algorithms was similar against the validation data set, but best for the bootstrap aggregation tree using an independent test data set. Monthly mean maps of the continental United States are generated for the drought year 2012 using the bootstrap aggregation tree. Evapotranspiration levels are lower than those shown in comparison data sets for the growing season in the eastern United States, resulting from a low bias at high evapotranspiration values. Retraining with the training data set weighted towards higher evapotranspiration values reduces this discrepancy but does not eliminate it. It is clear that machine learning evapotranspiration algorithm results have a significant dependence on training data set composition.Item Island Land Loss in the Chesapeake Bay: A Quantitative and Process Analysis(1992) Wray, Rachel Donham; Leatherman, Stephen P.; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md)The rates and processes of land loss were studied for seven islands in the Chesapeake Bay: Barren, Bloodsworth, Hooper, James, Poplar, Smith and South Marsh Islands. Rates and patterns of land loss were quantified for the years 1848 to 1987 with the Metric Mapping technique which utilizes digitized data from historical maps and vertical aerial photographs. Processes of land loss were determined through field surveys and correlated with environmental factors. Two distinct island types were identified which exhibited different, long-term patterns of land loss. Small, upland islands, termed the Northern Group, showed rapid land loss along the main stem of the Bay primarily due to wave action driven by the predominant westerly winds. Land loss appeared to accelerate during periods of high storm frequency. The long-term averaged land loss rate for Northern Group islands is 1.9 ha/yr. The averaged erosion rate on the western side of the islands is 4.9 m/yr, compared to 0.68 m/yr on the eastern side of the islands. In contrast, the large, marshy islands of the Southern Group experienced uniform marsh edge erosion and interior marsh degradation. The Southern Group islands lost land at an averaged rate of 5. 6 ha/yr, with an averaged rate of marsh edge erosion of 1.2 m/yr. Land loss appeared to be weakly correlated to storm frequency. Interior marsh loss was not quantified for this study, however, so this study provides an underestimation of total land loss of coastal wetlands.Item An Evolution of Land Use in Kent County, Maryland(1953) Singleton, Carey B. Jr; Van Royen, William; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md)The object of this study is to determine the land use changes that have taken place in Kent County, located on the Eastern Shore of Maryland (See Fig. 1) with emphasis on recent land use changes. The principal objectives of this study will be to ascertain, analyze, and review the evolution of land utilization in Kent County. A major trend within the past ten years has been toward a decreasing number of farms and, at the same time, a decreasing number of people gainfully employed in agriculture. This trend has resulted in the displacement of agricultural earners by fa.rm machinery and farm consolidations. An increase in the average size of farms is due to "outsiders" - business men from out-of-state -- who have established themselves in the county by buying and combining principally waterfront property. Thus large estates are formed along with the restoration of Colonial homes. This type of land tenure has been bringing about utilization of the land in the form of large dairy and beef herds. Kent County has the smallest number of farms of all the counties in Maryland but it has the largest average farm size in the state. This is an area of predominantly large dairy farms with highly mechanized machinery and equipment. The major trend in the last 25 years has been from cash grain to livestock raising which has resulted from the growth of dairying. The pattern of field crops has also changed from cash grains to feed grains for the large dairy herds. This study has been accomplished through the use of field work historical data, tables, maps, and photographs. The assumption can be made that greater permanency and stability in land use may be assured by utilizing the land for what it is best suited to produce. In an agricultural county, such as Kent, the retention of the soil, maintenance of its fertility, and the productivity are fundamental and therefore, the outstanding problems of optimum land utilization in the county. Land use adjusted into a pattern set by man should be utilized according to its capabilities. Optimum production and use of the land may be obtained by utilizing it for purposes to which it is best adapted. This is essentially a geographical problem in the final analysis and is manifested by a myriad of socio-economic factors that compose the gamut of land use implications. The author's interest in this area emanates from a field course in Geography and a number of trips through parts of this county. Field work was accomplished during the spring and summer of 1952 and constitutes the primary source of data for this thesis. The initials of the author appear where compilation of maps and graphs have been drawn from research and field data. All photographs have been taken by the author during his field work in the county.Item Local Information Landscapes: Theory, Measures, and Evidence(2019) Lee, Myeong; Butler, Brian S; Geography/Library & Information Systems; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)To understand issues about information accessibility within communities, research studies have examined human, social, and technical factors by taking a socio-technical view. While this view provides a profound understanding of how people seek, use, and access information, this approach tends to overlook the impact of the larger structures of information landscapes that constantly shape people’s access to information. When it comes to local community settings where local information is embedded in diverse material entities such as urban places and technical infrastructures, the effect of information landscapes should be taken into account in addition to particular strategies for solving information-seeking issues. However, characterizing the information landscape of a local community at the community level is a non-trivial problem due to diverse contexts, users, and their interactions with each other. One way to conceptualize local information landscapes in a way that copes with the complexity of the interplay between information, contexts, and human factors is to focus on the materiality of information. By focusing on the material aspects of information, it becomes possible to understand how local information is provided to social entities and infrastructures and how it exists, forming structures at the community level. Through an extensive literature review, this paper develops a theory of local information landscapes (LIL Theory) to better conceptualize the community-level, material structure of local information. Specifically, the LIL theory adapts a concept of the virtual as an ontological view of the interplay between technical infrastructures, spaces, and people as a basis for assessing and explaining community-level structures of local information. By complementing existing theories such as information worlds and information grounds, this work provides a new perspective on how information deserts manifest as a material pre-condition of information inequality. Using this framework, an empirical study was conducted to examine the explicit effects of information deserts on other community characteristics. Specifically, the study aims to provide an initial assessment of LIL theory by examining how the fragmentation of local information, a form of information deserts, is related to important community characteristics such as socio-economic inequality, deprivation, and community engagement. Building upon previous work in sociology and political science, this study shows that the fragmentation of local information (1) is shaped by socio-economic deprivation/inequality that is confounded with ethnoracial heterogeneity, (2) the fragmentation of local information is highly correlated to people's community gatherings, (3) the fragmentation of local information moderates the effects of socio-economic inequality on cultural activity diversity, and (4) the fragmentation of local information mediates the relationship between socio-economic inequality and community engagement. By making use of three local event datasets over 20 months in 14 U.S. cities (about two million records) and over 3 months in 28 U.S. cities (about 620K records), respectively, this study develops computational frameworks to operationalize information deserts in a scalable way. This dissertation provides a theorization of community-level information inequality and computational models that support the quantitative examination of it. Further theorizations of the conceptual constructs and methodological improvements on measurements will benefit information policy-makers, local information system designers, and researchers who study local communities with conceptual models, vocabularies, and assessment frameworks.