13 resultados para geographic tongue

em Digital Commons at Florida International University


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Geographic Information Systems (GIS) is an emerging information technology (IT) which promises to have large scale influences in how spatially distributed resources are managed. It has had applications in the management of issues as diverse as recovering from the disaster of Hurricane Andrew to aiding military operations in Desert Storm. Implementation of GIS systems is an important issue because there are high cost and time involvement in setting them up. An important component of the implementation problem is the "meaning" different groups of people who are influencing the implementation give to the technology. The research was based on the theory of (theoretical stance to the problem was based on the) "Social Construction of Knowledge" systems which assumes knowledge systems are subject to sociological analysis both in usage and in content. An interpretive research approach was adopted to inductively derive a model which explains how the "meanings" of a GIS are socially constructed. The research design entailed a comparative case analysis over two county sites which were using the same GIS for a variety of purposes. A total of 75 in-depth interviews were conducted to elicit interpretations of GIS. Results indicate that differences in how geographers and data-processors view the technology lead to different implementation patterns in the two sites.

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Land use and transportation interaction has been a research topic for several decades. There have been efforts to identify impacts of transportation on land use from several different perspectives. One focus has been the role of transportation improvements in encouraging new land developments or relocation of activities due to improved accessibility. The impacts studied have included property values and increased development. Another focus has been on the changes in travel behavior due to better mobility and accessibility. Most studies to date have been conducted in metropolitan level, thus unable to account for interactions spatially and temporally at smaller geographic scales. ^ In this study, a framework for studying the temporal interactions between transportation and land use was proposed and applied to three selected corridor areas in Miami-Dade County, Florida. The framework consists of two parts: one is developing of temporal data and the other is applying time series analysis to this temporal data to identify their dynamic interactions. Temporal GIS databases were constructed and used to compile building permit data and transportation improvement projects. Two types of time series analysis approaches were utilized: univariate models and multivariate models. Time series analysis is designed to describe the dynamic consequences of time series by developing models and forecasting the future of the system based on historical trends. Model estimation results from the selected corridors were then compared. ^ It was found that the time series models predicted residential development better than commercial development. It was also found that results from three study corridors varied in terms of the magnitude of impacts, length of lags, significance of the variables, and the model structure. Long-run effect or cumulated impact of transportation improvement on land developments was also measured with time series techniques. The study offered evidence that congestion negatively impacted development and transportation investments encouraged land development. ^

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Annual average daily traffic (AADT) is important information for many transportation planning, design, operation, and maintenance activities, as well as for the allocation of highway funds. Many studies have attempted AADT estimation using factor approach, regression analysis, time series, and artificial neural networks. However, these methods are unable to account for spatially variable influence of independent variables on the dependent variable even though it is well known that to many transportation problems, including AADT estimation, spatial context is important. ^ In this study, applications of geographically weighted regression (GWR) methods to estimating AADT were investigated. The GWR based methods considered the influence of correlations among the variables over space and the spatially non-stationarity of the variables. A GWR model allows different relationships between the dependent and independent variables to exist at different points in space. In other words, model parameters vary from location to location and the locally linear regression parameters at a point are affected more by observations near that point than observations further away. ^ The study area was Broward County, Florida. Broward County lies on the Atlantic coast between Palm Beach and Miami-Dade counties. In this study, a total of 67 variables were considered as potential AADT predictors, and six variables (lanes, speed, regional accessibility, direct access, density of roadway length, and density of seasonal household) were selected to develop the models. ^ To investigate the predictive powers of various AADT predictors over the space, the statistics including local r-square, local parameter estimates, and local errors were examined and mapped. The local variations in relationships among parameters were investigated, measured, and mapped to assess the usefulness of GWR methods. ^ The results indicated that the GWR models were able to better explain the variation in the data and to predict AADT with smaller errors than the ordinary linear regression models for the same dataset. Additionally, GWR was able to model the spatial non-stationarity in the data, i.e., the spatially varying relationship between AADT and predictors, which cannot be modeled in ordinary linear regression. ^

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3D geographic information system (GIS) is data and computation intensive in nature. Internet users are usually equipped with low-end personal computers and network connections of limited bandwidth. Data reduction and performance optimization techniques are of critical importance in quality of service (QoS) management for online 3D GIS. In this research, QoS management issues regarding distributed 3D GIS presentation were studied to develop 3D TerraFly, an interactive 3D GIS that supports high quality online terrain visualization and navigation. ^ To tackle the QoS management challenges, multi-resolution rendering model, adaptive level of detail (LOD) control and mesh simplification algorithms were proposed to effectively reduce the terrain model complexity. The rendering model is adaptively decomposed into sub-regions of up-to-three detail levels according to viewing distance and other dynamic quality measurements. The mesh simplification algorithm was designed as a hybrid algorithm that combines edge straightening and quad-tree compression to reduce the mesh complexity by removing geometrically redundant vertices. The main advantage of this mesh simplification algorithm is that grid mesh can be directly processed in parallel without triangulation overhead. Algorithms facilitating remote accessing and distributed processing of volumetric GIS data, such as data replication, directory service, request scheduling, predictive data retrieving and caching were also proposed. ^ A prototype of the proposed 3D TerraFly implemented in this research demonstrates the effectiveness of our proposed QoS management framework in handling interactive online 3D GIS. The system implementation details and future directions of this research are also addressed in this thesis. ^

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This research presents several components encompassing the scope of the objective of Data Partitioning and Replication Management in Distributed GIS Database. Modern Geographic Information Systems (GIS) databases are often large and complicated. Therefore data partitioning and replication management problems need to be addresses in development of an efficient and scalable solution. ^ Part of the research is to study the patterns of geographical raster data processing and to propose the algorithms to improve availability of such data. These algorithms and approaches are targeting granularity of geographic data objects as well as data partitioning in geographic databases to achieve high data availability and Quality of Service(QoS) considering distributed data delivery and processing. To achieve this goal a dynamic, real-time approach for mosaicking digital images of different temporal and spatial characteristics into tiles is proposed. This dynamic approach reuses digital images upon demand and generates mosaicked tiles only for the required region according to user's requirements such as resolution, temporal range, and target bands to reduce redundancy in storage and to utilize available computing and storage resources more efficiently. ^ Another part of the research pursued methods for efficient acquiring of GIS data from external heterogeneous databases and Web services as well as end-user GIS data delivery enhancements, automation and 3D virtual reality presentation. ^ There are vast numbers of computing, network, and storage resources idling or not fully utilized available on the Internet. Proposed "Crawling Distributed Operating System "(CDOS) approach employs such resources and creates benefits for the hosts that lend their CPU, network, and storage resources to be used in GIS database context. ^ The results of this dissertation demonstrate effective ways to develop a highly scalable GIS database. The approach developed in this dissertation has resulted in creation of TerraFly GIS database that is used by US government, researchers, and general public to facilitate Web access to remotely-sensed imagery and GIS vector information. ^

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The Bahamas is a small island nation that is dealing with the problem of freshwater shortage. All of the country’s freshwater is contained in shallow lens aquifers that are recharged solely by rainfall. The country has been struggling to meet the water demands by employing a combination of over-pumping of aquifers, transport of water by barge between islands, and desalination of sea water. In recent decades, new development on New Providence, where the capital city of Nassau is located, has created a large area of impervious surfaces and thereby a substantial amount of runoff with the result that several of the aquifers are not being recharged. A geodatabase was assembled to assess and estimate the quantity of runoff from these impervious surfaces and potential recharge locations were identified using a combination of Geographic Information Systems (GIS) and remote sensing. This study showed that runoff from impervious surfaces in New Providence represents a large freshwater resource that could potentially be used to recharge the lens aquifers on New Providence.

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Beginning in the era of the Spanish conquest and taking the reader right up to the present day, this book focuses on how the landscape of Cuba has changed and evolved into the environment we see today. It illustrates the range of factors – economic, political and cultural – that have determined Cuba’s physical geography, and explores the shifting conservation measures which have been instituted in response to new methods in agriculture and land management. The text uses historical documents, fieldwork, Geographic Information System (GIS) data and remotely-sensed satellite imagery to detail Cuba’s extensive land-use history as well as its potential future. The author goes further to analyze the manner, speed and methods of landscape change, and examines the historical context and governing agendas that have had an impact on the relationship between Cuba’s inhabitants and their island. Gebelein also assesses the key role played by agricultural production in the framework of international trade required to sustain Cuba’s people and its economy. The book concludes with a review of current efforts by Cuban and other research scientists, as well as private investors, conservation managers and university professors who are involved in shaping Cuba’s evolving landscape and managing it during the country’s possible transition to a more politically diverse, enfranchised and open polity.

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With the exponential increasing demands and uses of GIS data visualization system, such as urban planning, environment and climate change monitoring, weather simulation, hydrographic gauge and so forth, the geospatial vector and raster data visualization research, application and technology has become prevalent. However, we observe that current web GIS techniques are merely suitable for static vector and raster data where no dynamic overlaying layers. While it is desirable to enable visual explorations of large-scale dynamic vector and raster geospatial data in a web environment, improving the performance between backend datasets and the vector and raster applications remains a challenging technical issue. This dissertation is to implement these challenging and unimplemented areas: how to provide a large-scale dynamic vector and raster data visualization service with dynamic overlaying layers accessible from various client devices through a standard web browser, and how to make the large-scale dynamic vector and raster data visualization service as rapid as the static one. To accomplish these, a large-scale dynamic vector and raster data visualization geographic information system based on parallel map tiling and a comprehensive performance improvement solution are proposed, designed and implemented. They include: the quadtree-based indexing and parallel map tiling, the Legend String, the vector data visualization with dynamic layers overlaying, the vector data time series visualization, the algorithm of vector data rendering, the algorithm of raster data re-projection, the algorithm for elimination of superfluous level of detail, the algorithm for vector data gridding and re-grouping and the cluster servers side vector and raster data caching.

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Cotton is the most abundant natural fiber in the world. Many countries are involved in the growing, importation, exportation and production of this commodity. Paper documentation claiming geographic origin is the current method employed at U.S. ports for identifying cotton sources and enforcing tariffs. Because customs documentation can be easily falsified, it is necessary to develop a robust method for authenticating or refuting the source of the cotton commodities. This work presents, for the first time, a comprehensive approach to the chemical characterization of unprocessed cotton in order to provide an independent tool to establish geographic origin. Elemental and stable isotope ratio analysis of unprocessed cotton provides a means to increase the ability to distinguish cotton in addition to any physical and morphological examinations that could be, and are currently performed. Elemental analysis has been conducted using LA-ICP-MS, LA-ICP-OES and LIBS in order to offer a direct comparison of the analytical performance of each technique and determine the utility of each technique for this purpose. Multivariate predictive modeling approaches are used to determine the potential of elemental and stable isotopic information to aide in the geographic provenancing of unprocessed cotton of both domestic and foreign origin. These approaches assess the stability of the profiles to temporal and spatial variation to determine the feasibility of this application. This dissertation also evaluates plasma conditions and ablation processes so as to improve the quality of analytical measurements made using atomic emission spectroscopy techniques. These interactions, in LIBS particularly, are assessed to determine any potential simplification of the instrumental design and method development phases. This is accomplished through the analysis of several matrices representing different physical substrates to determine the potential of adopting universal LIBS parameters for 532 nm and 1064 nm LIBS for some important operating parameters. A novel approach to evaluate both ablation processes and plasma conditions using a single measurement was developed and utilized to determine the "useful ablation efficiency" for different materials. The work presented here demonstrates the potential for an a priori prediction of some probable laser parameters important in analytical LIBS measurement.

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This research analyzed the spatial relationship between a mega-scale fracture network and the occurrence of vegetation in an arid region. High-resolution aerial photographs of Arches National Park, Utah were used for digital image processing. Four sets of large-scale joints were digitized from the rectified color photograph in order to characterize the geospatial properties of the fracture network with the aid of a Geographic Information System. An unsupervised landcover classification was carried out to identify the spatial distribution of vegetation on the fractured outcrop. Results of this study confirm that the WNW-ESE alignment of vegetation is dominantly controlled by the spatial distribution of the systematic joint set, which in turn parallels the regional fold axis. This research provides insight into the spatial heterogeneity inherent to fracture networks, as well as the effects of jointing on the distribution of surface vegetation in desert environments.

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This thesis research describes the design and implementation of a Semantic Geographic Information System (GIS) and the creation of its spatial database. The database schema is designed and created, and all textual and spatial data are loaded into the database with the help of the Semantic DBMS's Binary Database Interface currently being developed at the FIU's High Performance Database Research Center (HPDRC). A friendly graphical user interface is created together with the other main system's areas: displaying process, data animation, and data retrieval. All these components are tightly integrated to form a novel and practical semantic GIS that has facilitated the interpretation, manipulation, analysis, and display of spatial data like: Ocean Temperature, Ozone(TOMS), and simulated SeaWiFS data. At the same time, this system has played a major role in the testing process of the HPDRC's high performance and efficient parallel Semantic DBMS.

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The objective of this study was to develop a GIS-based multi-class index overlay model to determine areas susceptible to inland flooding during extreme precipitation events in Broward County, Florida. Data layers used in the method include Airborne Laser Terrain Mapper (ALTM) elevation data, excess precipitation depth determined through performing a Soil Conservation Service (SCS) Curve Number (CN) analysis, and the slope of the terrain. The method includes a calibration procedure that uses "weights and scores" criteria obtained from Hurricane Irene (1999) records, a reported 100-year precipitation event, Doppler radar data and documented flooding locations. Results are displayed in maps of Eastern Broward County depicting types of flooding scenarios for a 100-year, 24-hour storm based on the soil saturation conditions. As expected the results of the multi-class index overlay analysis showed that an increase for the potential of inland flooding could be expected when a higher antecedent moisture condition is experienced. The proposed method proves to have some potential as a predictive tool for flooding susceptibility based on a relatively simple approach.

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Cotton is the most abundant natural fiber in the world. Many countries are involved in the growing, importation, exportation and production of this commodity. Paper documentation claiming geographic origin is the current method employed at U.S. ports for identifying cotton sources and enforcing tariffs. Because customs documentation can be easily falsified, it is necessary to develop a robust method for authenticating or refuting the source of the cotton commodities. This work presents, for the first time, a comprehensive approach to the chemical characterization of unprocessed cotton in order to provide an independent tool to establish geographic origin. Elemental and stable isotope ratio analysis of unprocessed cotton provides a means to increase the ability to distinguish cotton in addition to any physical and morphological examinations that could be, and are currently performed. Elemental analysis has been conducted using LA-ICP-MS, LA-ICP-OES and LIBS in order to offer a direct comparison of the analytical performance of each technique and determine the utility of each technique for this purpose. Multivariate predictive modeling approaches are used to determine the potential of elemental and stable isotopic information to aide in the geographic provenancing of unprocessed cotton of both domestic and foreign origin. These approaches assess the stability of the profiles to temporal and spatial variation to determine the feasibility of this application. This dissertation also evaluates plasma conditions and ablation processes so as to improve the quality of analytical measurements made using atomic emission spectroscopy techniques. These interactions, in LIBS particularly, are assessed to determine any potential simplification of the instrumental design and method development phases. This is accomplished through the analysis of several matrices representing different physical substrates to determine the potential of adopting universal LIBS parameters for 532 nm and 1064 nm LIBS for some important operating parameters. A novel approach to evaluate both ablation processes and plasma conditions using a single measurement was developed and utilized to determine the “useful ablation efficiency” for different materials. The work presented here demonstrates the potential for an a priori prediction of some probable laser parameters important in analytical LIBS measurement.