GE 275 - Introduction to Geospatial Technologies and GIS

2. Recognize the practical applications of GISt in academic, professional, and everyday settings. 

3. Understand the capacity of GISt applications across disciplines and nonacademic setting, such as community-based, government, non-profit, and others. 

4. Identify issues that can be addressed and/or assisted with GISt. 

5. Demonstrate working knowledge of GIS software and platforms and geospatial technologies and devices.

6. Collect and create geospatial data for implementation and analysis. 

7. Organize geospatial data in GIS software.

8. Perform meaningful analyses utilizing GISt and geospatial data. 

9. Evaluate the validity and applicability of products and projects generated through GISt by self, peers, and others. 

10. Design a project that utilizes working knowledge of GISt. 

11. Present the results of an issue based, self-generated GISt project.

12. Effectively organize communications, ensuring there is a clear introduction and conclusion, the content is well-sequenced and there are appropriate transitions. 

13. Consider the context, costs, benefits and consequences of potential solutions to problems or issues. 

14. Create and/or organize data and information into meaningful patterns in order to interpret and draw inferences from it. 

15. Articulate the importance of and how to find opportunities to volunteer/serve in the community. 

16. Describe how knowledge and learning from the academic study/field/discipline relates to one’s participation in civic life, politics and government. 

17. Complete work accurately, with attention to detail. 
Course Outline:
I. Introduction to GIS

1. Geographical Approaches to Understanding Our World
2. Historical and Contemporary GISt Origins
3. Contemporary GISt Uses and Application Areas

II. Geospatial Data

1. Geodesy
2. Datums, Coordinate Systems, Projections
3. Data Sources
4. Data Collection in Situ
5. Spatial Data Accuracy and Quality

III. Data Models

1. Vector Data Model
2. Raster Data Model

IV. Attribute Data

1. Database Management
2. Types of Attribute Data
3. Relational Model
4. Joins and Relates
5. Attribute Data Editing and Manipulation

V. Cartography and Visualization

1. Quantitative and Qualitative Mapping
2. Thematic Map Types
3. Data Classification
4. Design and Symbology
5. Map Production and Evaluation

VI. Data Query in GIS

1. Descriptive Statistics and Data Visualization
2. SQL – Structured Query Language
3. Data Query with Vector Data
4. Data Query with Raster Data

VII. Data Analysis

1. Vector Data Analysis
2. Raster Data Analysis

VIII. GIS: Geospatial Solutions for Contemporary Issues

1. Environmental and Climate Issues
2. Demographic Issues
3. Social Justice and Resource Access
4. Interdisciplinary and Cross-Platform Issues

Lectures: 30-50%

Synchronous and/or Asynchronous Discussion: 10-30%
Mandatory Course Components:
None
Equivalent Courses:
None