Major in Geographic Information Science
| Code | Title | Units |
|---|---|---|
| GEOG 101 | PHYSICAL GEOGRAPHY | 3 |
| GEOG 221 | INTRODUCTION TO GEOSPATIAL TECHNOLOGY | 3 |
| GEOG 321 | INTRODUCTION TO REMOTE SENSING AND PHOTOGRAMMETRY | 3 |
| GEOG 322 | INTRO TO GEOGRAPHIC INFORMATION SCIENCE | 4 |
| GEOG 323 | CARTOGRAPHY AND GRAPHICS I | 3 |
| GEOG 414 | GIS APPLICATIONS | 3 |
| or GEOG 465 | ADVANCED TECHNIQUES IN GIS | |
| GEOG 416 | ADVANCED REMOTE SENSING: DIGITAL IMAGE PROCESSING AND ANALYSIS | 3 |
| COSC 236 | INTRODUCTION TO COMPUTER SCIENCE I | 4 |
| CIS 211 | FUNDAMENTALS OF INFORMATION SYSTEMS & TECHNOLOGY | 3 |
| CIS 328 | INTRODUCTION TO DATA ANALYTICS | 3 |
| MATH 231 | BASIC STATISTICS | 3 |
| MATH 211 | CALCULUS FOR APPLICATIONS | 3 |
| or MATH 273 | CALCULUS I | |
| Electives | ||
| Select three from the following: | 9 | |
| GEOMORPHOLOGY | ||
| SOILS AND VEGETATION | ||
| QUANTITATIVE METHODS IN GEOGRAPHY | ||
| QUALITATIVE METHODS IN GEOGRAPHY | ||
| METEOROLOGY | ||
| NATURAL RESOURCES AND SOCIETY: A GEOGRAPHIC PERSPECTIVE | ||
| APPLICATION OF GIS IN EMERGENCY MANAGEMENT | ||
| GIS DATABASE DESIGN | ||
| PYTHON SCRIPTING FOR ARCGIS | ||
| GEOSPATIAL TECHNOLOGIES SPECIAL TOPICS | ||
| INDEPENDENT STUDY IN GEOGRAPHY GIS topic approved by program director | ||
| Selective two from the following: | 6 | |
| COMPUTING HARDWARE AND INFRASTRUCTURE | ||
| FUNDAMENTALS OF WEB TECHNOLOGIES | ||
| SELECTED TOPICS IN INFORMATION TECHNOLOGY | ||
| DATA AND INFORMATION MANAGEMENT | ||
| SCRIPTING LANGUAGES | ||
| ADVANCED DATA MANAGEMENT & ANALYSIS | ||
| DATA ORGANIZATION | ||
| ORGANIZATIONAL DATABASE MANAGEMENT | ||
| APPLIED DATA SCIENCE & MACHINE LEARNING | ||
| INTRODUCTION TO COMPUTER SCIENCE II | ||
| DATA STRUCTURES AND ALGORITHM ANALYSIS | ||
| ETHICAL AND SOCIETAL CONCERNS OF COMPUTER SCIENTISTS | ||
| DISCRETE MATHEMATICS | ||
| ELEMENTARY LINEAR ALGEBRA | ||
| CALCULUS II | ||
| INTRODUCTION TO STATISTICAL METHODS | ||
| PROBABILITY | ||
| MATHEMATICAL STATISTICS | ||
| APPLIED REGRESSION AND TIME SERIES PREDICTIVE MODELING | ||
| INTRODUCTION TO MACHINE LEARNING | ||
| MATHEMATICAL MODELS | ||
| EXPERIMENTAL MATHEMATICS | ||
| Total Units | 53 | |
Sample Four-Year Plan
The selected course sequence below is an example of the simplest path to degree completion. Based on course schedules, student needs, and student choice, individual plans may vary. Students should consult with their adviser to make the most appropriate elective choices and to ensure that they have completed the required number of units (120) to graduate.
| First Year | |||
|---|---|---|---|
| Term 1 | Units | Term 2 | Units |
| GEOG 101 (Core 8) | 3 | GEOG 221 | 3 |
| Core 1 (or Core 2) | 3 | MATH 231 (Core 3) | 3 |
| Core 4 | 3 | Core 2 (or Core 1) | 3 |
| Elective (COSC 111 recommended) | 3 | Core 6 | 3 |
| Elective | 3 | Core 7 | 4 |
| 15 | 16 | ||
| Second Year | |||
| Term 1 | Units | Term 2 | Units |
| GEOG 322 | 4 | GEOG 321 | 3 |
| MATH 273 | 4 | COSC 236 | 4 |
| Elective | 3 | GEOG Elective (1) | 3 |
| Core 5 | 3 | Core 11 | 3 |
| Core 10 | 3 | Core 13 | 3 |
| 17 | 16 | ||
| Third Year | |||
| Term 1 | Units | Term 2 | Units |
| CIS 211 | 3 | CIS 328 | 3 |
| GEOG Elective (2) | 3 | COSC / CIS Elective (1) | 3 |
| MATH Elective (1) | 3 | COSC / CIS Elective | 3 |
| Core 12 | 3 | GEOG 323 | 3 |
| Core 14 | 3 | Core 9 | 3 |
| 15 | 15 | ||
| Fourth Year | |||
| Term 1 | Units | Term 2 | Units |
| GEOG 414 or 465 | 3 | GEOG Elective (3) | 3 |
| GEOG 416 | 3 | Elective | 3 |
| Elective | 3 | Elective | 3 |
| Elective | 3 | Internship or Elective | 3 |
| Elective | 2 | ||
| 14 | 12 | ||
| Total Units 120 | |||
The overarching educational objective of the program is to create technically competent GIS technicians possessing the skills necessary for advanced GIS analysis and for supporting applications of GIS in a wide variety of private and public sector settings. The program learning outcomes (PLOs) are as follows (with the alignment to TU’s institutional student learning outcomes [ISLOs] indicated):
- Spatial Data Analysis (Critical Analysis and Reasoning): Students will be able to perform comprehensive analyses of geospatial data using professional geospatial software, spatial analysis techniques, and statistical methods.
- Data Mining and Management (Information Literacy and Technological Competency): Students will apply information systems and data science techniques, such as programming, data mining, big data processing, database management, algorithm development, workflow automation, and web development, to effectively manage, analyze, and visualize geospatial data and to address complex geospatial challenges in diverse industries.
- Data Visualization (Effective Communication): Students will be able to visualize and communicate geospatial data and results using various formats, such as maps, web mapping applications, story maps, charts, and professional presentations.
- Problem-Solving Skills (Working in Multifaceted Work Environments): Students will be able to integrate geospatial data with other types of data to address socio-economic, environmental, planning, and other real-world challenges, supporting decision-making processes.