Data Science MPS: Spatial Analytics Pathway

The Spatial Analytics pathway focuses on data analytics techniques dealing with spatial (location) data. Spatial data are increasingly relevant to the goals of many organizations, yet spatial data have unique dimensions that require specialized data models, visualization, and analytic procedures. There is increasing demand for spatially skilled data scientists to exploit the ever-expanding sources of spatial and location-based data.

The courses in this pathway focus on geographic and spatial data, and the robust spatial data management, analysis, and visualization capabilities present in common data science platforms (R and Python). Many analytic capabilities only previously present in Geographic Information Systems (GIS) software have now been migrated to these open source environments where the value of spatial data integrated with non-spatial data sources can be most effectively realized. The pathway is a partnership between UMBC’s Department of Geography and Environmental Science and Department of Computer Science and Electrical Engineering.

Professor at the board explaining calculations


Admission into the Data Science graduate program
Proficiency with R and/or Python

GES 773: GIS Modeling Techniques

This course addresses the concepts, tools, and techniques of GIS modeling, and presents modeling concepts and theory as well as provides opportunities for hands-on model design, construction, and application. The focus is given to model calibration and validation.

GES 774: Spatial Statistics

This course investigates statistical techniques for exploring and characterizing spatial phenomena. The course covers local/global cluster analysis, spatial autocorrelation, interpolation, kriging, as well as exposure to prominent GIS statistical packages. An emphasis is placed on exploratory spatial data analysis (ESDA) to develop spatial cognition and analytical skills with practical applications to modeling spatial phenomena in computer environments.

GES 778: Advanced Visualization and Presentation

Web technologies are providing increasingly sophisticated environments for visualization of spatial data. This course explores advanced techniques for visualizing multivariate and multidimensional data. Topics include advanced cartographic techniques, 3D, dynamic data update, and temporal modeling. Students will learn to create geospatial data-driven Web apps with modern technologies and open source software, including HTML5, JavaScript, and D3. Project-based learning will allow students to advance through the course at a pace that’s tailored to their backgrounds. Although the course requires no advanced knowledge of Web technologies, students with previous programming experience will have a wider range of project options.

GES 770: Special Topics in Enterprise GIS

This course is to introduce the concept of geoprocessing and how to use Python to automate the process. Students will learn the basic syntax of Python, available system tools in ArcToolbox, model and ModelBuilder. They will also learn how to build a model and how to create a model tool. The core of the class is ArcPy site package. Students will work with the embedded ArcGIS Python window to write and execute scripts. They will also use the more advanced IDE tool Eclipse with PyDev plug-in. Students will write scripts using tools from ArcPy to perform various tasks, such as managing maps and layers, performing data editing, executing geoprocessing tools and creating custom geoprocessing tools. They will develop Python scripts in Eclipse. Once the Python scripts are developed, the student will learn how to convert it to a script tool so it will be available for other Geoprocessing models. In the end of the class, the students will be able to implement a geoprocessing solution for a complex geospatial problem.

GES 775: Advanced GIS Application Development

This course is designed for students who wish to pursue advanced application development skills. Its main focus is web based GIS application development. Therefore, students need to have basic programming skills and also need to understand HTML and internet. This course have three focuses: ArcGIS Online as convenient GIS map/data services in the Cloud, GIS web application development using ArcGIS Javascript API and ArcGIS Server. The students will explore the services provided by ArcGIS Online, create a map using their own data and set up different sharing privileges. They will use ArcGIS Javascript API to develop a GIS web application. They will learn Javascript as a client side programming language, using AJAX to communicate to server, the structure of JSON and the popular dojo kit. They will use ArcGIS server to set up their own service and then use Javascript API to develop a web application to consume the service. In the end, the students will be able to build a robust enterprise GIS web application using the skills learned in the class.

Career Outlook

Spatial Analytics is an emerging field with high job growth. While a subset of the broader discipline of Data Science and Analytics, leveraging location information is fundamental to many corporations (e.g. Uber, UPS, Walmart). Mobile devices, UAV-based sensing and delivery services, and any Location Based Service (LBS) is dependent on spatial data and analytics. According to Labor Insight, an employer-demand tool, employers in the Washington DC and Baltimore metropolitan areas seeking employees with skills in spatial analytics include Booz Allen Hamilton, Vencore, Leidos, and the National Geospatial-Intelligence Agency (NGA).

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