Introduction to GIScience courses
This is an introductory course that focuses on how the earth surface is visualized, explored, and analyzed in digital formats. It provides a systematic introduction of map‐based analytical approaches to understanding the Earth environment and human society. The topics cover the basics of cartography (map making and reading), aerial photography and satellite image interpretation, GIS, and map‐based reasoning and communication of spatial data. Through lectures and computer/field exercises, students will learn fundamental concepts of digital geographic data to understand vast quantities of geographic information in our ever‐changing world. Students will be exposed to leading edge trends in mapping technology — with examples from everyday life like web‐based maps and smartphone APPs — as their practical experiences.
(3 credits)
This course is an introduction to the use of small unmanned aerial systems (UAS) in collecting/processing imagery for mapping/information analysis. Course content includes UAS characteristics, small camera considerations, project planning and processing, and legal requirements in the United States and selected European countries.
(3 credits)
Introduction to the theory and principles of map construction including discussions of equipment and materials, lettering and symbolization, scale and generalization, data manipulation and representation. Presentation of geographic information on maps.
(3 credits)
Theory and use of basic photo interpretation instruments and methods. Practice in acquiring and interpreting data from aerial photography for use in the physical and social sciences.
(3 credits)
Geographic Information Systems (GISs) represent a major advancement in computer handling
of geographical data. These systems are used extensively throughout all levels of
government, private industry, and academia to provide support for spatial decision
making and problem solving. Principles and methods of Geographic Information Systems
are presented with an emphasis on modeling the Earth and abstracting geographical
data, collection of geographical data using modern techniques such as GPS, mapping
information, and analyzing patterns and spatial relationships.
Practical experience with GIS is provided during the lab exercises using a state‐of‐the‐art
GIS. Students are provided free copies of the GIS software. No prerequisites.
(3 credits)
Advanced GIScience courses
How do the flu activities in South Carolina vary over space? Are the activities randomly scattered throughout the state, or are there discernible geographic patterns? What are the effects of socioeconomic status on the evacuation decision making during Hurricane Matthew? Answering these questions needs to make use of quantitative methods(or statistical analysis) with geographic data. This course will deal with the nature of geographical datasets, statistical measures and spatial models commonly used by geographers to describe spatial variations and patterns, distributions, and relationships among geographical data. Each student will be given opportunities to apply these techniques to geographical datasets, with practice involving the use of computer-based exercises and written examinations.
(3 credits)
Fundamental concepts about remote sensing of environment: basics of electromagnetic radiation interacting with earth surfaces; technical backgrounds when aerial/satellite images are used as a source of earth observation; satellite systems and commonly applied images; and applications in natural and built environments.
(3 credits)
Theory and application of geographic information systems including discussions of automated input, storage, analysis, integration, and display of spatial data. Use of an operational geographic information system.
(3 credits)
Introduction to digital image processing techniques and applications. Image correction, enhancement, spatial and spectral transformation. Land use/land cover classification, and change detection.
(3 credits)
Topical Technologies and Applications of GIScience courses
Examination of the geo-spatial aspects of hazards analysis and planning with specific reference to disaster preparedness, recovery, mitigation, and resilience. This course 1) provides a historical overview of hazards assessment and planning within the United States including the legal frameworks such as the Disaster Mitigation Act of 2000 and its amendments; 2) introduces the conceptual and theoretical background to hazards analysis including scale, geospatial models, and metrics for vulnerability and resilience; 3) introduces analytical tools used in hazards and vulnerability assessments; and 4) illustrates the application of existing hazards research on planning and analysis into contemporary practice.
(3 credits)
How to find the centroid, perimeter, or area of a polygon? How can the system tell that two geographical features overlap each other? How to develop your own algorithms to extract information from spatial data? How to automate a series of tasks to solve a complex spatial problem? This course addresses these fundamental spatial questions from a programming perspective. With this course, students will be able to 1) develop fundamental programming skills with Python by working with spatial data in the context of GIS, 2) gain practical experience in designing and developing tools to solve specific spatial problems by programming with ArcGIS and other spatial packages, and 3) understand the principles of popular GIS data models and algorithms, and the internal operations of GIS software.
(3 credits)
By integrating GIS and web technologies, WebGIS brings the traditional GIS functionalities such as spatial analysis and mapping into the web environment in a way that was not possible before. This course is intended for advanced undergraduates and graduate students in Geography or related disciplines to 1) develop an understanding of WebGIS principles, and 2) gain necessary techniques, web and GIS programming skills, and hands-on experiences to develop high-quality web mapping applications for use in professional or research settings.
(3 credits)
Geographical information systems for modeling physical/human processes in space and time using raster and vector data. Cartographic modeling concepts, embedded models, and GIS-model coupling.
(3 credits)
Satellite-based information extraction; programming skills for digital image processing; self-developed modeling approaches; quantitative analysis of remote sensing data.
(3 credits)
Seminars in GIScience
Seminar theme may vary by semester. Past themes include:
- Geospatial big data analytics – innovations and applications
Massive volumes of geospatial data are being acquired at increasingly faster speeds from a variety of Earth observation platforms. These big geospatial data pose grand challenges for scientists in geography and other related geospatial domains, especially with regard to efficient data management, information extraction, spatial analysis, and visualization. Focusing on the emerging geospatial cloud computing and cyberinfrastructure, this seminar is organized to capture and discuss the latest innovations and cutting-edge technologies in GIScience for tackling data- and computational-intensive geospatial problems. - Big Earth Data – advanced image analytics
(3 Credits)