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Title: SPATIAL ANALYSIS OF NORTH ATLANTIC STORM TRAJECTORIES.
Creator: Lazar, Austin J., Li, Yang, Florida Atlantic University, Department of Mathematical Sciences, Charles E. Schmidt College of Science
Abstract/Description: Storms in the North Atlantic Ocean are observed on a continual basis yearly. Storm trajectories exhibit random behavior and are costly to society. Data from the National Oceanic and Atmospheric Administration (NOAA) contains every storm’s track from the year 1851 to 2022. Data of each storm’s track can aid in decision making regarding their behavior. In this article, data analysis is performed on historical storm tracks during the years 1966 to 2022, where access to satellite information is...
Show moreStorms in the North Atlantic Ocean are observed on a continual basis yearly. Storm trajectories exhibit random behavior and are costly to society. Data from the National Oceanic and Atmospheric Administration (NOAA) contains every storm’s track from the year 1851 to 2022. Data of each storm’s track can aid in decision making regarding their behavior. In this article, data analysis is performed on historical storm tracks during the years 1966 to 2022, where access to satellite information is available. Analysis on this data will be used to determine if the storms’ trajectory is statistically dependent on other storm’s trajectories at varying distances in space. The proposed model is a spatial statistical model that is fitted on an in-sample data set to determine the spatial relationship for storm trajectories at all pairwise directions or orientations. Afterwards, the model is assessed on an out-of-sample test data set for performance evaluation.
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Date Issued: 2023
PURL: http://purl.flvc.org/fau/fd/FA00014227
Subject Headings: Spatial analysis (Statistics), Storms, North Atlantic Ocean
Format: Document (PDF)

Title: Optimization and inductive models for continuous estimation of hydrologic variables.
Creator: Brown, Ricardo Eric., College of Engineering and Computer Science, Department of Civil, Environmental and Geomatics Engineering
Abstract/Description: This thesis develops methodologies for continuous estimation of hydrological variables which infill missing daily rainfall data and the forecast of weekly streamflows from a watershed. Several mathematical programming formulations were developed and used to estimate missing historical rainfall data. Functional relationships were created between radar precipitation and known rain gauge data then are used to estimate the missing data. Streamflow predictions models require highly non-linear...
Show moreThis thesis develops methodologies for continuous estimation of hydrological variables which infill missing daily rainfall data and the forecast of weekly streamflows from a watershed. Several mathematical programming formulations were developed and used to estimate missing historical rainfall data. Functional relationships were created between radar precipitation and known rain gauge data then are used to estimate the missing data. Streamflow predictions models require highly non-linear mathematical models to capture the complex physical characteristics of a watershed. An artificial neural network model was developed for streamflow prediction. There are no set methods of creating a neural network and the selection of architecture and inputs to a neural network affects the performance. This thesis addresses this issue with automated input and network architecture selection through optimization. MATLABª scripts are developed and used to test many combinations and select a model through optimization.
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Date Issued: 2012
PURL: http://purl.flvc.org/FAU/3342036
Subject Headings: Hydorlogic models, Mathematics, Fuzzy logic, Spatial analysis (Statistics), Stream measurements
Format: Document (PDF)

Title: Statistics preserving spatial interpolation methods for missing precipitation data.
Creator: El Sharif, Husayn., College of Engineering and Computer Science, Department of Civil, Environmental and Geomatics Engineering
Abstract/Description: Deterministic and stochastic weighting methods are commonly used methods for estimating missing precipitation rain gauge data based on values recorded at neighboring gauges. However, these spatial interpolation methods seldom check for their ability to preserve site and regional statistics. Such statistics and primarily defined by spatial correlations and other site-to-site statistics in a region. Preservation of site and regional statistics represents a means of assessing the validity of...
Show moreDeterministic and stochastic weighting methods are commonly used methods for estimating missing precipitation rain gauge data based on values recorded at neighboring gauges. However, these spatial interpolation methods seldom check for their ability to preserve site and regional statistics. Such statistics and primarily defined by spatial correlations and other site-to-site statistics in a region. Preservation of site and regional statistics represents a means of assessing the validity of missing precipitation estimates at a site. This study evaluates the efficacy of traditional interpolation methods for estimation of missing data in preserving site and regional statistics. New optimal spatial interpolation methods intended to preserve these statistics are also proposed and evaluated in this study. Rain gauge sites in the state of Kentucky are used as a case study, and several error and performance measures are used to evaluate the trade-offs in accuracy of estimation and preservation of site and regional statistics.
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Date Issued: 2012
PURL: http://purl.flvc.org/FAU/3355568
Subject Headings: Numerical analysis, Meteorology, Statistical methods, Spatial analysis (Statistics), Data processing, Atmospheric physics, Statistical methods, Geographic information systems, Mathematical models
Format: Document (PDF)

Title: Contextual Modulation of Competitive Object Candidates in Early Object Recognition.
Creator: Islam, Mohammed F., Barenholtz, Elan, Florida Atlantic University, Charles E. Schmidt College of Science, Department of Psychology
Abstract/Description: Object recognition is imperfect; often incomplete processing or deprived information yield misperceptions (i.e., misidentification) of objects. While quickly rectified and typically benign, instances of such errors can produce dangerous consequences (e.g., police shootings). Through a series of experiments, this study examined the competitive process of multiple object interpretations (candidates) during the earlier stages of object recognition process using a lexical decision task paradigm....
Show moreObject recognition is imperfect; often incomplete processing or deprived information yield misperceptions (i.e., misidentification) of objects. While quickly rectified and typically benign, instances of such errors can produce dangerous consequences (e.g., police shootings). Through a series of experiments, this study examined the competitive process of multiple object interpretations (candidates) during the earlier stages of object recognition process using a lexical decision task paradigm. Participants encountered low-pass filtered objects that were previously demonstrated to evoke multiple responses: a highly frequented interpretation (“primary candidates”) and a lesser frequented interpretation (“secondary candidates”). When objects were presented without context, no facilitative effects were observed for primary candidates. However, secondary candidates demonstrated evidence for being actively suppressed.
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Date Issued: 2017
PURL: http://purl.flvc.org/fau/fd/FA00004836, http://purl.flvc.org/fau/fd/FA00004836
Subject Headings: Pattern recognition systems., Information visualization., Artificial intelligence., Spatial analysis (Statistics), Latent structure analysis.
Format: Document (PDF)

Title: The Manteño of the Cloud Forest: Settlement Patterns and Spatial Analysis of Manteño Stone Architecture in the Las Tusas River Valley in Manabí, Ecuador.
Creator: Garzón-Oechsle, Andrés E., Brown, Clifford T., Florida Atlantic University, Dorothy F. Schmidt College of Arts and Letters, Department of Anthropology
Abstract/Description: The present study identifies settlement patterns of the Manteño culture within the cloud forest of southern Manabí by surveying, recording and analyzing the stone architecture found within the drainage basin of the Las Tusas River, Ecuador. The statistical methods used were: Triangulated Irregular Networks or TIN (for topography interpretations), K-means (to determine natural groups for structures based on their dimensions, shape, and wall thickness), Ripley’s K (to determine spatial nature...
Show moreThe present study identifies settlement patterns of the Manteño culture within the cloud forest of southern Manabí by surveying, recording and analyzing the stone architecture found within the drainage basin of the Las Tusas River, Ecuador. The statistical methods used were: Triangulated Irregular Networks or TIN (for topography interpretations), K-means (to determine natural groups for structures based on their dimensions, shape, and wall thickness), Ripley’s K (to determine spatial nature of these groups) and Kernel Density (to visualize their spatial organization). The cloud forest ecotone of southern Manabí was an anthropogenic landscape during the late Integration period. The alluvial valleys of the upper Rio Blanco drainage basin do not represent a hinterland or a periphery occupation but a series of Manteño nucleated settlements raised on terraces and interconnected by strings of linear settlements and dispersed settlements throughout the rugged terrain of this landscape.
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Date Issued: 2018
PURL: http://purl.flvc.org/fau/fd/FA00013001
Subject Headings: Manabí (Ecuador), Archaeology--Ecuador--Antiquities, Land settlement patterns, Spatial analysis (Statistics), Manteño
Format: Document (PDF)

Title: The cave as a cosmogram: The use of GIS in an intrasite spatial analysis of the main chamber of Actun Tunichil Muknal, a Maya ceremonial cave in Western Belize.
Creator: Moyes, Holley., Florida Atlantic University, Fradkin, Arlene
Abstract/Description: This study is a spatial analysis conducted in the Main Chamber of Actun Tunichil Muknal, a Terminal Classic Maya ceremonial cave (A.D. 830--950), located in Western Belize. The research examines ancient Maya ritual cave use by analyzing artifact deposition patterns. Using a Geographical Information System (GIS), it provides a methodology for the development of comparative models of spatial organization. The system facilitated data visualization, exploration, and generation. The GIS was...
Show moreThis study is a spatial analysis conducted in the Main Chamber of Actun Tunichil Muknal, a Terminal Classic Maya ceremonial cave (A.D. 830--950), located in Western Belize. The research examines ancient Maya ritual cave use by analyzing artifact deposition patterns. Using a Geographical Information System (GIS), it provides a methodology for the development of comparative models of spatial organization. The system facilitated data visualization, exploration, and generation. The GIS was instrumental in the analysis of the proximity of artifacts to natural morphological features of the cave. Artifact deposition patterns were correlated with known ritual behavior patterns from the region. Using this method, boundary markers, artifact pathways, and a centrally located symbolic three-stone-hearth feature were identified. This study suggests that, within the cave, the ancient Maya employed a cognitive model of spatial organization similar to that witnessed by ethnographers in other venues, or reported in ethnohistorical texts in rites of foundation.
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Date Issued: 2001
PURL: http://purl.flvc.org/fcla/dt/12851
Subject Headings: Caves--Belize., Mayas--Balize--Antiquities., Spatial analysis (Statistics), Geographic information systems.
Format: Document (PDF)

Title: GIS and spatial data analysis: A case study using MODFLOW and ARC/INFO.
Creator: Hinton, Matthew Alfred., Florida Atlantic University, Shaw, Shih-Lung, Charles E. Schmidt College of Science, Department of Geosciences
Abstract/Description: GIS is expected to differ from other digital spatial data handling packages by virtue of its emphasis on spatial analysis and modeling, yet major limitations of spatial analytical capabilities are still observed. To identify the types of spatial analysis which are desirable and appropriate to GIS, this thesis proposes a systematic 'building-blocks' approach for the identification of data models and spatial analytical tools to develop a flexible and powerful GIS spatial analysis and modeling...
Show moreGIS is expected to differ from other digital spatial data handling packages by virtue of its emphasis on spatial analysis and modeling, yet major limitations of spatial analytical capabilities are still observed. To identify the types of spatial analysis which are desirable and appropriate to GIS, this thesis proposes a systematic 'building-blocks' approach for the identification of data models and spatial analytical tools to develop a flexible and powerful GIS spatial analysis and modeling environment. The building-blocks approach will be demonstrated in this thesis by examining a ground water flow model in MODFLOW, an SDA package designed specifically for this purpose. Procedures in MODFLOW will be disassembled into their primitive component functions, or building-blocks, which will then be sought out in ARC/INFO, representing a modern, general-purpose GIS. In the process, the levels of integration between GIS and SDA will be encountered and discussed.
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Date Issued: 1994
PURL: http://purl.flvc.org/fcla/dt/15007
Subject Headings: Geographic information systems, Spatial analysis (Statistics)--Data processing, Information storage and retrieval systems--Geography
Format: Document (PDF)

Title: Assessment of Changes in Precipitation Data Characteristics due to Infilling by Spatially Interpolated Estimates.
Creator: Hachmi, Mohammad, Teegavarapu, Ramesh, Florida Atlantic University, College of Engineering and Computer Science, Department of Civil, Environmental and Geomatics Engineering
Abstract/Description: Spatial and temporal interpolation methods are commonly used methods for estimating missing precipitation rain gauge data based on values recorded at neighboring gauges. However, these interpolation methods have not been comprehensively checked for their ability to preserve time series characteristics. Assessing the preservation of time series characteristics helps achieving a threshold criteria of length of gaps in a data set that is acceptable to be filled. This study evaluates the efficacy...
Show moreSpatial and temporal interpolation methods are commonly used methods for estimating missing precipitation rain gauge data based on values recorded at neighboring gauges. However, these interpolation methods have not been comprehensively checked for their ability to preserve time series characteristics. Assessing the preservation of time series characteristics helps achieving a threshold criteria of length of gaps in a data set that is acceptable to be filled. This study evaluates the efficacy of optimal weighting interpolation for estimation of missing data in preserving time series characteristics. Rain gauges in the state of Kentucky are used as a case study. Several model performance measures are also evaluated to validate the filling model; followed by time series characteristics to evaluate the accuracy of estimation and preservation of precipitation data characteristics. This study resulted in a definition of region-specific threshold of the maximum length of gaps allowed in a data set at five percent.
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Date Issued: 2016
PURL: http://purl.flvc.org/fau/fd/FA00004783, http://purl.flvc.org/fau/fd/FA00004783
Subject Headings: Precipitation (Meteorology), Spatial analysis (Statistics), Geographic information systems--Mathematical models., Climatic changes--Environmental aspects., Functions of real variables.
Format: Document (PDF)

Title: System Level Modeling and Simulation with MLDesigner.
Creator: Kovalski, Fabiano, Aalo, Valentine A., Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: System modeling has the potential to enhance system design productivity by providing a platform for system performance evaluations. This model must be designed at an abstract level, hiding system details. However, it must represent any subsystem or its components at any level of specification details. In order to model such a system, we will need to combine various models-of-computation (MOC). MOC provide a framework to model various algorithms and activities, while accounting for and...
Show moreSystem modeling has the potential to enhance system design productivity by providing a platform for system performance evaluations. This model must be designed at an abstract level, hiding system details. However, it must represent any subsystem or its components at any level of specification details. In order to model such a system, we will need to combine various models-of-computation (MOC). MOC provide a framework to model various algorithms and activities, while accounting for and exploiting concurrency and synchronization aspects. Along with supporting various MOC, a modeling environment should also support a well developed library. In this thesis, we have explored various modeling environments. MLDesigner (MLD) is one such modeling environment that supports a well developed library and integrates various MOC. We present an overview and discuss the process of system modeling with MLD. We further present an abstract model of a Network-on-Chip in MLD and show latency results for various customizable parameters for this model.
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Date Issued: 2006
PURL: http://purl.flvc.org/fau/fd/FA00012531
Subject Headings: High performance computing, Electronic data processing--Distributed processing, Information technology--Management, Spatial analysis (Statistics), System design
Format: Document (PDF)

Title: A GIS approach to linking spatial patterns and trip generation/trip distribution modeling.
Creator: Harris, David Michael., Florida Atlantic University, Shaw, Shih-Lung, Charles E. Schmidt College of Science, Department of Geosciences
Abstract/Description: Geographic information systems (GIS) have been increasingly used in urban transportation planning and modeling. One key advantage of GIS is its ability to integrate and analyze various kinds of geographically referenced data. Modeling and analysis tools used to predict travel patterns should be shaped by changes in spatial organization that are currently taking place. Utilizing the detailed data made available by GIS, this study investigates the potential improvements offered to the...
Show moreGeographic information systems (GIS) have been increasingly used in urban transportation planning and modeling. One key advantage of GIS is its ability to integrate and analyze various kinds of geographically referenced data. Modeling and analysis tools used to predict travel patterns should be shaped by changes in spatial organization that are currently taking place. Utilizing the detailed data made available by GIS, this study investigates the potential improvements offered to the conventional trip generation and trip distribution models by explicitly referencing the spatial land use and street network patterns within traffic analysis zones (TAZs).
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Date Issued: 1995
PURL: http://purl.flvc.org/fcla/dt/15174
Subject Headings: Geographic information systems, Spatial analysis (Statistics)--Data processing, Urban transportation--United States--Mathematical models
Format: Document (PDF)

Title: Data Fusion of LiDAR and Aerial Imagery to Map the Campus of Florida Atlantic University.
Creator: Gamboa, Nicole, Zhang, Caiyun, Florida Atlantic University, Charles E. Schmidt College of Science, Department of Geosciences
Abstract/Description: Reliable geographic intelligence is essential for urban areas; land-cover classification creates the data for urban spatial decision making. This research tested a methodology to create a land-cover map for the main campus of Florida Atlantic University in Boca Raton, Florida. The accuracy of nine separate land-cover classification results were tested; the one with the highest accuracy was chosen for the final map. Object-based image segmentation was applied to fused and LiDAR point cloud ...
Show moreReliable geographic intelligence is essential for urban areas; land-cover classification creates the data for urban spatial decision making. This research tested a methodology to create a land-cover map for the main campus of Florida Atlantic University in Boca Raton, Florida. The accuracy of nine separate land-cover classification results were tested; the one with the highest accuracy was chosen for the final map. Object-based image segmentation was applied to fused and LiDAR point cloud (elevation and intensity) data and aerial imagery. These were classified by Random Forest, k-Nearest Neighbor and Support Vector Machines classifiers. Shadow features were reclassified hierarchically in order to create a complete map. The Random Forest classifier used with the fused data set gave the highest overall accuracy at 82.3%, and a Kappa value at 0.77. When combined with the results from the shadow reclassification, the overall accuracy increased to 86.3% and the Kappa value improved to 0.82.
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Date Issued: 2016
PURL: http://purl.flvc.org/fau/fd/FA00004595, http://purl.flvc.org/fau/fd/FA00004595
Subject Headings: Spatial analysis (Statistics), Geographic information systems., Cartography--Remote sensing., Thematic maps., Geospatial data--Mathematical models., Criminal justice, Administration of., African Americans, Violence against.
Format: Document (PDF)

Title: Mapping urban land cover using multi-scale and spatial autocorrelation information in high resolution imagery.
Creator: Johnson, Brian A., Charles E. Schmidt College of Science, Department of Geosciences
Abstract/Description: Fine-scale urban land cover information is important for a number of applications, including urban tree canopy mapping, green space analysis, and urban hydrologic modeling. Land cover information has traditionally been extracted from satellite or aerial images using automated image classification techniques, which classify pixels into different categories of land cover based on their spectral characteristics. However, in fine spatial resolution images (4 meters or better), the high degree of...
Show moreFine-scale urban land cover information is important for a number of applications, including urban tree canopy mapping, green space analysis, and urban hydrologic modeling. Land cover information has traditionally been extracted from satellite or aerial images using automated image classification techniques, which classify pixels into different categories of land cover based on their spectral characteristics. However, in fine spatial resolution images (4 meters or better), the high degree of within-class spectral variability and between-class spectral similarity of many types of land cover leads to low classification accuracy when pixel-based, purely spectral classification techniques are used. Object-based classification methods, which involve segmenting an image into relatively homogeneous regions (i.e. image segments) prior to classification, have been shown to increase classification accuracy by incorporating the spectral (e.g. mean, standard deviation) and non-spectral (e.g. te xture, size, shape) information of image segments for classification. One difficulty with the object-based method, however, is that a segmentation parameter (or set of parameters), which determines the average size of segments (i.e. the segmentation scale), is difficult to choose. Some studies use one segmentation scale to segment and classify all types of land cover, while others use multiple scales due to the fact that different types of land cover typically vary in size. In this dissertation, two multi-scale object-based classification methods were developed and tested for classifying high resolution images of Deerfield Beach, FL and Houston, TX. These multi-scale methods achieved higher overall classification accuracies and Kappa coefficients than single-scale object-based classification methods., Since the two dissertation methods used an automated algorithm (Random Forest) for image classification, they are also less subjective and easier to apply to other study areas than most existing multi-scale object-based methods that rely on expert knowledge (i.e. decision rules developed based on detailed visual inspection of image segments) for classifying each type of land cover.
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Date Issued: 2012
PURL: http://purl.flvc.org/FAU/3342110
Subject Headings: Image processing, Digital techniques, Remote sensing, Mathematics, Remote-sensing images, Computational intelligence, Cities and towns, Remote sensing, Environmental sciences, Remote sensing, Spatial analysis (Statistics)
Format: Document (PDF)

Title: High Resolution Population Distribution Estimates for Improved Decision Making, With a Case Study of Sea-Level Rise Vulnerability in Boca Raton, Florida.
Creator: Ziegler, Hannes Moritz, Xie, Zhixiao, Florida Atlantic University, Charles E. Schmidt College of Science, Department of Geosciences
Abstract/Description: Planners and managers often rely on coarse population distribution data from the census for addressing various social, economic, and environmental problems. In the analysis of physical vulnerabilities to sea-level rise, census units such as blocks or block groups are coarse relative to the required decision-making application. This study explores the benefits offered from integrating image classification and dasymetric mapping at the household level to provide detailed small area population...
Show morePlanners and managers often rely on coarse population distribution data from the census for addressing various social, economic, and environmental problems. In the analysis of physical vulnerabilities to sea-level rise, census units such as blocks or block groups are coarse relative to the required decision-making application. This study explores the benefits offered from integrating image classification and dasymetric mapping at the household level to provide detailed small area population estimates at the scale of residential buildings. In a case study of Boca Raton, FL, a sea-level rise inundation grid based on mapping methods by NOAA is overlaid on the highly detailed population distribution data to identify vulnerable residences and estimate population displacement. The enhanced spatial detail offered through this method has the potential to better guide targeted strategies for future development, mitigation, and adaptation efforts.
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Date Issued: 2016
PURL: http://purl.flvc.org/fau/fd/FA00004670
Subject Headings: City planning -- Remote sensing, Community development, Urban -- Florida -- Boca Raton, Geographic information systems, Population -- Geographic information systems -- Florida -- Boca Raton, egional planning -- Florida -- Boca Raton, Spatial analysis (Statistics), Urban geography -- Remote sensing
Format: Document (PDF)

Title: Spatial and Temporal Mapping of the Evolution of the Miami-Fort Lauderdale-West Palm Beach Metropolitan Statistical Area (MSA).
Creator: Rochelo, Mark, Roberts, Charles, Florida Atlantic University, Charles E. Schmidt College of Science, Department of Geosciences
Abstract/Description: Urbanization is a fundamental reality in the developed and developing countries around the world creating large concentrations of the population centering on cities and urban centers. Cities can offer many opportunities for those residing there, including infrastructure, health services, rescue services and more. The living space density of cities allows for the opportunity of more effective and environmentally friendly housing, transportation and resources. Cities play a vital role in...
Show moreUrbanization is a fundamental reality in the developed and developing countries around the world creating large concentrations of the population centering on cities and urban centers. Cities can offer many opportunities for those residing there, including infrastructure, health services, rescue services and more. The living space density of cities allows for the opportunity of more effective and environmentally friendly housing, transportation and resources. Cities play a vital role in generating economic production as entities by themselves and as a part of larger urban complex. The benefits can provide for extraordinary amount of people, but only if proper planning and consideration is undertaken. Global urbanization is a progressive evolution, unique in spatial location while consistent to an overall growth pattern and trend. Remotely sensing these patterns from the last forty years of space borne satellites to understand how urbanization has developed is important to understanding past growth as well as planning for the future. Imagery from the Landsat sensor program provides the temporal component, it was the first satellite launched in 1972, providing appropriate spatial resolution needed to cover a large metropolitan statistical area to monitor urban growth and change on a large scale. This research maps the urban spatial and population growth over the Miami – Fort Lauderdale – West Palm Beach Metropolitan Statistical Area (MSA) covering Miami- Dade, Broward, and Palm Beach counties in Southeast Florida from 1974 to 2010 using Landsat imagery. Supervised Maximum Likelihood classification was performed with a combination of spectral and textural training fields employed in ERDAS Image 2014 to classify the images into urban and non-urban areas. Dasymetric mapping of the classification results were combined with census tract data then created a coherent depiction of the Miami – Fort Lauderdale – West Palm Beach MSA. Static maps and animated files were created from the final datasets for enhanced visualizations and understanding of the MSA evolution from 60-meter resolution remotely sensed Landsat images. The simplified methodology will create a database for urban planning and population growth as well as future work in this area.
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Date Issued: 2017
PURL: http://purl.flvc.org/fau/fd/FA00004904, http://purl.flvc.org/fau/fd/FA00004904
Subject Headings: Geographic information systems., Sustainable urban development--Florida--Miami--Planning., Sustainable urban development--Florida--Fort Lauderdale--Planning., Sustainable urban development--Florida--West Palm Beach--Planning., Urbanization--Florida--Miami-Dade County., Urbanization--Florida--Broward County., Urbanization--Florida--Palm Beach County., Remote sensing., Spatial analysis (Statistics)
Format: Document (PDF)

Spatial analysis (Statistics) (12)	+ -
Geographic information systems (4)	+ -
Geographic information systems. (3)	+ -
Mathematics (2)	+ -
Spatial analysis (Statistics)--Data processing (2)	+ -

African Americans, Violence against. (1)	+ -
Archaeology--Ecuador--Antiquities (1)	+ -
Artificial intelligence. (1)	+ -
Atmospheric physics (1)	+ -
Cartography--Remote sensing. (1)	+ -
Caves--Belize. (1)	+ -
Cities and towns (1)	+ -
City planning -- Remote sensing (1)	+ -
Climatic changes--Environmental aspects. (1)	+ -
Community development, Urban -- Florida -- Boca Raton (1)	+ -
Computational intelligence (1)	+ -
Criminal justice, Administration of. (1)	+ -
Data processing (1)	+ -
Digital techniques (1)	+ -
Electronic data processing--Distributed processing (1)	+ -
Environmental sciences (1)	+ -
Functions of real variables. (1)	+ -
Fuzzy logic (1)	+ -
Geographic information systems--Mathematical models. (1)	+ -
Geospatial data--Mathematical models. (1)	+ -
High performance computing (1)	+ -
Hydorlogic models (1)	+ -
Image processing (1)	+ -
Information storage and retrieval systems--Geography (1)	+ -
Information technology--Management (1)	+ -

Florida Atlantic University (11)	+ -
Charles E. Schmidt College of Science (8)	+ -
Department of Geosciences (6)	+ -
College of Engineering and Computer Science (4)	+ -
Department of Civil, Environmental and Geomatics Engineering (3)	+ -

Shaw, Shih-Lung (2)	+ -
Aalo, Valentine A. (1)	+ -
Barenholtz, Elan (1)	+ -
Brown, Clifford T. (1)	+ -
Brown, Ricardo Eric. (1)	+ -
Department of Anthropology (1)	+ -
Department of Computer and Electrical Engineering and Computer Science (1)	+ -
Department of Mathematical Sciences (1)	+ -
Department of Psychology (1)	+ -
Dorothy F. Schmidt College of Arts and Letters (1)	+ -
El Sharif, Husayn. (1)	+ -
Fradkin, Arlene (1)	+ -
Gamboa, Nicole (1)	+ -
Garzón-Oechsle, Andrés E. (1)	+ -
Hachmi, Mohammad (1)	+ -
Harris, David Michael. (1)	+ -
Hinton, Matthew Alfred. (1)	+ -
Islam, Mohammed F. (1)	+ -
Johnson, Brian A. (1)	+ -
Kovalski, Fabiano (1)	+ -
Lazar, Austin J. (1)	+ -
Li, Yang (1)	+ -
Moyes, Holley. (1)	+ -
Roberts, Charles (1)	+ -
Rochelo, Mark (1)	+ -

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