Courses

Customizing GIS software to extend its built-in functionality and to automate repetitive tasks.

Theory and practice of cartographic design, emphasizing effective visual thinking and visual communication with geographic information systems. Technologies: ArcGIS Pro, Mapbox Studio, QGIS

Focuses on the science of analytical reasoning mediated through human-centered interactive geographic visualization and computational methods; provides students with hands-on experience solving complex problems through the design, implementation, and application of geovisual analytics tools.

Systematic approach to requirements acquisition, specification, design, and implementation of geospatial information systems.

Choosing and applying analytical methods for geospatial data, including point pattern analysis, interpolation, surface analysis, overlay analysis, and spatial autocorrelation.

Using imagery and terrain data in typical application scenarios faced by the geospatial professional.

Understanding lidar systems; design, operation, data processing techniques, and product generation to address typical application scenarios faced by the geospatial professional.

Case studies, student investigations, and projects reveal the scope, impact, and character of the Geospatial Revolution.

How geographic information systems facilitate data analysis and communication to address common geographic problems.

Database design, creation, maintenance, and data integration using desktop GIS software.

Learn advanced applications of Python for developing and customizing GIS software, designing user interfaces, and solving complex geoprocessing tasks using both proprietary and open source platforms. Technologies: ArcGIS Pro, ArcPy, Jupyter Notebooks, ArcGIS API for Python, QGIS, GDAL/OGR.

Design, development, and implementation of web mapping applications using OGC standards and open source software. Technologies: JavaScript, QGIS, GDAL, OGR, GeoServer, TileMill, Leaflet, and OpenStreetMap

Advanced topics in remote sensing and image processing, including new sensors, applications, and decision-making.

Explores three important topics related to georeferenced data: datums, map projections, and grid systems.

Focuses on how geospatial professionals can create applications using industry-related geospatial APIs. Students will build applications using the core web technologies of HTML, CSS, and JavaScript. Technologies: JavaScript, ArcGIS API for JavaScript, ArcGIS Online, CSS

Theory and practical applications of using cloud computing and server resources to solve geospatial problems. Technologies: ArcGIS Server, Portal for ArcGIS, ArcGIS Online, GeoServer, CARTO, Amazon Web Services, Mapbox, Google Fusion Tables Theory.

Advanced topics in the storage, management, and retrieval of geospatial data using common proprietary and open-source relational database technologies. Technologies: SQL, PostGIS, ArcSDE/Multiuser Geodatabases, QGISAdvanced.

Understanding remote sensing systems' operation, data products, and processing techniques to address typical problem scenarios faced by the GEOINT professional.

The course highlights the tradecraft of integrating spatial data science with geospatial intelligence methods; students practice this integration by preparing intelligence reports requiring GIS tools.

Prepares current and aspiring geospatial intelligence professionals to apply and interpret results of non-quantitative analysis and modeling techniques.

Common platforms, analytical strategies, and policy dimensions of Unmanned Aerial Systems (UAS) in public, private, defense, and humanitarian applications.

This course will explore the development of analytics systems and the application of best practices and established software design principles using the Python programming language and its several toolkits.

This course provides a foundation in the principles, concepts, techniques, and tools for visualizing large data sets.

Survey course on the key topics in predictive analytics. Students will learn methods associated with data analytics techniques and apply them to real examples using the R statistical system.

Descriptive statistics, hypothesis testing, power, estimation, confidence intervals, regression, one- and two-way ANOVA, chi-square tests, diagnostics.

Data mining tools are exploring data with regression, PCA, discriminate analysis, cluster analysis, and classification and regression trees (CART).

Examines the nexus of geospatial intelligence analysis with cyberspace, the geopolitics of cyber threats, the politics of censorship and hacking, public safety, disaster response, and humanitarian relief; students will utilize a range of cyber data, systems, and spatial sciences to examine human social networks of the internet.

Real-world applications of GIS and spatial analysis to investigate a variety of current environmental issues.

The application of cultural geography in the intelligence analysis and synthesis process by identifying prominent threats to civil security.

Conservation GIS applies geospatial problem-solving to ecological research and resource management issues to enhance conservation planning.

The role of geographic information systems in understanding disease, including relevant spatial analysis and cartographic visualization techniques.

Understanding location technology and geospatial analysis to support an efficient and effective pathway to better business decisions.

This course examines the use of GIS principles, data, and applications that have been developed for the field of transportation.

Requirements analysis and proposal writing to plan and implement GIS solutions supporting emergency management activities of government agencies and contractors.

Prepares current and aspiring professionals to recognize, analyze, and address ethical problems in the GIS&T (geospatial) field.

Principles of effective project management applied to the design and implementation of geospatial information systems.

Orientation to the geographic foundations of geospatial intelligence and its applications in national security, international relief work, and disaster management.

This course provides an overview of key demographic data sets, and promotes familiarity with, and appropriate use of, these data.

This graduate course will expose students to spatial analysis tools and analytical methods applied to demographic research.

Students study the theory and principles of geospatially based design by investigating the methods and collaborative nature of the geodesign process.

The principles, inherent values, and practical applications of evaluation and decision models as implemented within the geodesign framework.

Students will learn a variety of methods for accessing appropriate weather and climate datasets available from government and research institutions. Working with very large datasets in a computationally efficient manner will be stressed, as will consideration of factors that affect data reliability.

A semester project that demonstrates the student's ability to apply advanced knowledge and skills related to applying spatial data science principles in a way that makes a substantial contribution to research in Spatial Data Science.

Thesis Research