The Master's in Applied Geospatial Analytics program is offered through the Graduate School in partnership with the College of Agriculture, College of Liberal Arts, and Polytechnic Institute at Purdue University. This interdisciplinary collaboration provides a level of academic quality that will help you distinguish yourself and advance your career.
This 30 credit-hour, five semester degree offers courses in 8-week periods. Courses are offered in spring, summer, and fall, allowing you to complete the master's degree in 20 months when taking one class each 8-week period.
The graduate degree leverages three existing, complimentary online graduate certificates at Purdue University and combines them to meet the professional and technical needs of students. Graduates can earn, in addition to their graduate degree, a graduate certificate in Applied Data Analytics, Spatial Data Science, and Strategic Communication Management.
Course Overview
| Course Number | Course Name | Credit Hours |
|---|---|---|
| ABE 65100 | Environmental Informatics | 3 credits |
| AGRY 54500 | Remote Sensing of Land Resources | 3 credits |
| ASM 54000 | Geographic Information System Application | 3 credits |
| CGT 57500 | Data Visualization Tools and Applications | 3 credits |
| CNIT 57500 | Data Analysis | 3 credits |
| CNIT 51000 | Data Literacy | 3 credits |
| COM 60111 | Seminar in Strategic Communication | 3 credits |
|
COM 60911 -OR- COM 60311 -OR- COM 62111 -OR- COM 65000 |
Strategic Public Relations
Seminar in Crisis Communication
Strategic Communication and Social Media
Communication and Leadership |
(Select 2 Courses)
6 credits |
| FNR 58700 | Advanced Spatial Ecology and GIS | 3 credits |
| Total Credit Hours: 30 |
Plan of Study Spring Start
| Spring | Summer | Fall | Spring | Summer |
|---|---|---|---|---|
|
CNIT 51000: Data Literacy COM Elective |
CNIT 57500: Data Analysis CGT 57500: Data Visualization Tools and Applications |
ASM 54000: Geographic Information System Application FNR 58700: Advanced Spatial Ecology and GIS |
ABE 65100: Environmental Informatics AGRY 54500: Remote Sensing of Land Resources |
COM 60111: Seminar in Strategic Communication COM Elective |
Plan of Study Fall Start
| Fall | Spring | Summer | Fall | Spring |
|---|---|---|---|---|
|
CNIT 51000: Data Literacy CNIT 57500: Data Analysis |
COM 60111: Seminar in Strategic Communication COM Elective |
CGT 57500: Data Visualization Tools and Applications COM Elective |
ASM 54000: Geographic Information System Application FNR 58700: Advanced Spatial Ecology and GIS |
ABE 65100: Environmental Informatics AGRY 54500: Remote Sensing of Land Resources |
Geospatial Course Descriptions
ABE 65100: Environmental Informatics
This course will educate students in the use, manipulation and analysis of environmental data by introducing them to scripting languages (e.g., C shell, Python), data types (e.g., ASCII, binary, NetCDF), databases (e.g., XML, DBF) and data visualization software (e.g., GMT, ArcMap) as well as techniques for checking data quality, working with missing data and handling large diverse sources of time series and spatial data.
Students will manipulate, check and insert data from a variety of sources, use that data as input to a distributed hydrologic model, analyze model output and learn methods for properly documenting their data use (creation of metadata) and long-term archival storage of those data. Skills learned should be applicable to most computer operating systems, but the majority of work for this class will be done within the Unix/Linux environment.
Students taking this course should have experience with one or more programming languages, including but not limited to C, Fortran, Perl, Python, Java, BASIC or two writing scripts or macros within programs such as MATLAB, S-PLUS, R or SAS.
AGRY 54500: Remote Sensing of Land Resources
This course introduces students to the principles of remote sensing and teaches methods for analysis and interpretation of remotely sensed data. The emphasis of the first half of the course is on passive optical technology and methodology for analysis of remotely sensed data.
The second half of the course introduces other sensing technologies and their application to the remote observation of soil, vegetation and water resources (together referred to as land resources) by airborne (manned and unmanned) and space-based sensors.
Students will be introduced to the latest developments in instrumentation and information technology in remote sensing and will learn how to utilize remotely sensed data to support research and decision making in agriculture, science and engineering.
ASM 54000: Geographic Information System Application
This course provides an introduction to fundamentals of geographic information systems (GIS) for spatially analyzing problems related to environmental, agricultural and engineering domains. You will learn key concepts of GIS, including data sources, projections, spatial analysis methods, data and metadata creation and conceptualization framework for solving spatial problems.
GIS is a powerful tool and most students find it to be interesting and enjoyable. The course will use Esri ArcGIS Pro software. At the end of the course we expect you to be an informed GIS user, as well as being reasonably competent using ArcGIS Pro.
CGT 57500: Data Visualization Tools and Applications
This course introduces modern visualization, techniques and methods useful for applying data analytics in technical environments. This will be achieved by focusing on a storytelling methodology to drive students to form effective communication styles for their data.
CNIT 57500: Data Analysis
This course examines Data Analytics tools useful for analyzing data sets to 1) ask better questions regarding the data and 2) find answers to those questions in order to improve decision making. Inherent in this process, students will gain an understanding of the uncertainty that exists whenever decisions about an entire population are made based upon a sample drawn from the population. This course will utilize a highly interactive, action-oriented series of assignments to engage students and help them develop the skills and confidence needed to analyze their own data sets.
CNIT 51000: Data Literacy
This course examines concepts, models and methods useful for applying data analytics in technical environments. Focusing on Hypothesis generation, the capturing, storage and expression of data for research analysis. This course will utilize a highly interactive, action-oriented agenda engaging students in hands on competency-based assignments.
COM 60111: Seminar in Strategic Communication
This course surveys the theories and processes of strategic communication and its practice by business, government, politicians and nonprofits – in domestic and international arenas. It also emphasizes the application of theory to provide an in-depth understanding of planning, executing and evaluating strategic communication plans.
COM 60911: Strategic Public Relations
Strategic communication is composed of integrated marketing communications (IMC), advertising, and public relations. As such, it builds on the general strategic communications course by providing an in depth understanding of public relations. Specifically, the class will cover public relations theories, ethics, concepts, principles, and applications.
COM 60311: Seminar in Crisis Communication
This course focuses on how to communicate in a time of crisis in order to manage threats to organizational identity, reputation or financial security.
COM 62111: Strategic Communication and Social Media
This course provides an overview of social media and its relationship to strategic communication. Students will learn about the available forms of social media (e.g., Blogs, Social Networks and Wikis) and they can help build and manage relationships with stakeholders. Students also analyze social media metrics as a framework for evaluating the effectiveness of social media strategies as tools for developing corporate, nonprofit, and governmental images and brands.
COM 65000: Communication and Leadership
Communication is the essence of leadership, and this course aims to identify how communication can fuel productivity, drive consensus and push the organization to a leadership position within a market.
FNR 58700: Advanced Spatial Ecology and GIS
Introduction to the principles of landscape ecology and biogeography with a laboratory devoted to the analysis of spatial data using geographic information systems (GIS) and other database tools.
Landscape ecology focuses on the important relationships of landscape structure (pattern, heterogeneity) and ecological processes (movement of animals, hydrologic dynamics) and how this information is used for natural resource management. Biogeography examines ecological patterns and processes at larger scales (generally at subcontinental to global) for the purposes of managing plants and animals of global importance.
In the last 15 years, tremendous efforts have been made to create spatial databases that help support research and management of natural resources at various scales. The lab will focus on the use and application of these databases that are common in natural resource management settings.