Teaching

GIS Courses

Advanced Academic Programs

430.600 – Web GIS

Web GIS is an important foundation course in which students will become familiar with the current platforms available for delivering Web GIS and sharing geographic content over the web. Professionals in various industries often have to make information readily available and with current developments this has become easier than ever. The class offers a fundamental understanding of creating and designing web maps and web apps using various approaches and platforms. Capabilities such as editing, geoprocessing, geocoding, image analysis, 3D, mobile and real-time GIS in a web environment will be examined. Cloud-based and on premises infrastructure to deliver Web GIS will be utilized.

430.601 – Geographic Information Systems (GIS)

In this introductory course, students become familiar with the concepts and gain the experience necessary to appreciate the utility of Geographic Information Systems in decision making. Topics covered include the fundamentals of cartography, geo-referencing, data structures, querying, data classification, and basic spatial data analysis. The course provides an overview of the capabilities of GIS software and applications of GIS. Class time is divided between lectures and GIS exercises that reinforce critical concepts. Students must complete a term project as part of the course.

430.602 – Remote Sensing: Earth Observing Systems and Applications

This course introduces remote sensing as an important technology to further our understanding of Earth’s land, atmospheric, and oceanic processes. Students study remote sensing science, techniques, and satellite technologies to become familiar with the types of information that can be obtained and how this information can be applied in the natural and social sciences. Applications include assessment of land cover and land use, mapping and analysis of natural resources, weather and climate studies, pollution detection and monitoring, disaster monitoring, and identification of oceanographic features.

430.604 – Spatial Analysis with GIS

This course introduces students to statistical techniques for solving spatial problems. Students will learn to apply the principles of statistics to address the distributional and locational aspects of spatial data within a variety of situations. Examples and assignments are drawn from many GIS applications, such as urban planning, political science, public health, transportation and crime analysis. Topics include spatial sampling, measures of dispersion and central tendency in spatial analysis, spatial autocorrelation, regression analysis, hypothesis testing, and decision support analysis.

430.603 – Geospatial Data Modeling

This course moves beyond the fundamentals of GIS to explore the constraints surrounding data modeling as well as methods to model spatial data. Students review current research in the field, learn relevant modeling techniques, and utilize advanced software tools for analysis. The course involves the use and integration of a variety of data sources, including baseline data layers; x-y coordinates, and satellite imagery. Specific GIS techniques in spatial analysis are introduced and the course builds on former GIS software experience. Cloud computing is introduced as an Infrastructure-as-a-Service development platform model. Students develop a significant GIS project over the course of the semester and present their findings at the end.

430.605 –Development and Management of GIS Projects

This course imparts knowledge and skills for managing GIS projects within an enterprise development environment, including technical, legal, ethical, and institutional problems. Cloud computing is introduced as an Infrastructure-as-a-Service development platform model. Students will examine the role of data standards for development of geographic information systems and technologies, explore key issues in organizational management of GIS projects (planning,
staffing, budgeting), and develop skills to design and manage geospatial databases. Ethical and legal issues in data acquisition, sharing, and representation will also be explored.

Earth and Planetary Sciences

270.318 Remote Sensing of the Environment

This course is an introduction to the use of remote sensing technology to study Earth’s physical and biochemical processes. Topics covered include remote sensing of the atmosphere, land and oceans, as well as remote sensing as a tool for policy makers.

270.405 – Modeling the Hydrological Cycle

This course addresses the use of computer simulation to study hydrological processes and to generate predictions. The perspective of the class is, primarily, that of the earth system scientist: models will be approached as tools that we want to use and, on occasion, build ourselves, for the pragmatic purpose of representing processes of interest. In this context, we will study various approaches to “physically-based” model design and implementation, explore methods for model application, evaluation, and improvement, and consider what models can (and cannot) tell us about the hydrological system. Through weekly computer exercises, students will gain practical skills in designing simple models, applying more sophisticated models, and working with common data types. In the term project, students will be asked to perform an informed application of a model or model analysis technique to address a research question.

270.618 Remote Sensing of the Environment

This course is an introduction to the use of remote sensing technology to study Earth’s physical and biochemical processes. Topics covered include remote sensing of the atmosphere, land and oceans, as well as remote sensing as a tool for policy makers.

Geography and Environmental Engineering

575.440 Geographic Information Systems (GIS) and Remote Sensing for Environmental Applications

Through lectures and laboratory exercises, this course illustrates the fundamental concepts of GIS and remote sensing technologies in the context of environmental engineering. Topics include the physical basis for remote sensing, remote sensing systems, digital image processing, data structures, database design, and spatial data analysis. The course is not intended to provide students with extensive training in particular image processing or GIS packages. However, hands-on computer laboratory sessions re-enforce critical concepts. Working knowledge of personal computers and completion of a term project is required.

575.713 Field Methods in Habitat Analysis and Wetland Delineation

The course provides students with practical field experience in the collection and analysis of field data needed for wetland delineation, habitat restoration, and description of vegetation communities. Among the course topics are sampling techniques for describing plant species distributions and community structure and diversity, including the quadrant and transect-based, point-intercept, and plot-less methods; identification of common and dominant indicator plant species of wetlands and uplands; identification of hydric soils; use of soil, topographic, and geologic maps and aerial photographs in deriving a site description and site history; and graphic and statistical methods including GIS applications for analyzing and presenting the field data. The classes consist of field studies to regional and local sites.

575.727 – Environmental Monitoring and Sampling

This course covers fundamental algorithms for efficiently solving geometric problems, especially ones involving 2D polygons and 3D polyhedrons. Topics include elementary geometric operations; polygon visibility, triangulation, and partitioning; computing convex hulls; Voronoi diagrams and Delaunay triangulations with applications; special polygon and polyhedron algorithms such as point containment and extreme point determination; point location in a planar graph subdivision; and robot motion planning around polygon obstacles. The course covers theory to the extent that it aids in understanding how the algorithms work. Emphasis is placed on implementation, and programming projects are an important part of the course work.

605.727 – Computational Geometry

This course covers fundamental algorithms for efficiently solving geometric problems, especially ones involving 2D polygons and 3D polyhedrons. Topics include elementary geometric operations; polygon visibility, triangulation, and partitioning; computing convex hulls; Voronoi diagrams and Delaunay triangulations with applications; special polygon and polyhedron algorithms such as point containment and extreme point determination; point location in a planar graph subdivision; and robot motion planning around polygon obstacles. The course covers theory to the extent that it aids in understanding how the algorithms work. Emphasis is placed on implementation, and programming projects are an important part of the course work.

Near Eastern Studies

130.353 (H,N) Space Archaeology: An Introduction to Satellite Remote Sensing, GIS, and GPS

This course introduces technologies archaeologists use to map ancient landscapes. These include Geographic Information Systems (GIS) mapping software, advanced Global Positioning System (GPS) receivers, and various types of satellite imagery.

130.354 (H, S) Advanced Archaeological Method and Theory I

Reviews recent developments in archaeological thought and practice, Including landscape archaeology, Geographical Information Systems applications, geomorphology, and remote sensing. Previous coursework in archaeology or permission of instructor required.

School of Public Health

140.662.01 Spatial Analysis and GIS I

Examines the use of Arc View Geographic Information System (GIS) software as a tool for integrating, manipulating, and displaying public health­-related spatial data. Topics covered include mapping, geocoding, and manipulations related to data structures and topology. Uses selected case studies to demonstrate concepts. Focuses on using GIS to generate and refine hypotheses about public health­-related spatial data in reparation for a formal statistical analysis. Although spatial statistical modeling is not a required part of the curriculum, related topics are discussed throughout. Includes both lecture and lab formats with GIS concepts and software specific details demonstrated during the lab portions.

140.663.01 Spatial Analysis and GIS II

Introduces statistical techniques used to model, analyze, and interpret public health related spatial data. Analysis of spatially dependent data is cast into a general framework based on regression methodology. Topics covered include the geostatistical techniques of kriging and variogram analysis and point process methods for spatial case control and area-level analysis. Although the focus is on statistical modeling, students will also cover topics related to clustering and cluster detection of disease events. Although helpful, knowledge of specific GIS software is not required. Instruction in the public domain statistical package R, (to be used for analysis), is provided.

340.701.11 Epidemiologic Applications of GIS

Presents the methods and uses of epidemiology towards the development and application of Geographic Information Systems (GIS) in public health. Emphasizes the potential of GIS as an epidemiological analysis tool for describing the magnitude of priority health problems, identifying health determinants and supporting health decision-making. Specific topics include epidemiological risk assessment and GIS, thematic mapping of unmet health needs, malaria risk assessment and GIS application for identifying public health problems. Includes hands-on experience and laboratory exercises using public domain and ESRI software.