GEOG 583
Geospatial System Analysis and Design

Course Overview

Course Overview

In this course, you will focus on developing a GIS system and designing a project proposal, as well as, investigating some existing and new technologies. The nature of this course allows you to explore a project of your own interest such as a work project, personal interest, hobby, etc. You will develop your term project throughout the semester following published design methodologies that will culminate in a final proposal consisting of 8 stages (Figure 1, below). The course will culminate in a peer reviewed presentation and final paper.

The design process diagram
The Design process followed in this course, beginning with the problem statement and ending with the Unified Modelling Language.
Credit: Brandi Gaertner © Penn State is licensed under CC BY-NC-SA 4.0

Course Objectives:

Upon successful completion of the course, students will be able to:

  • Design a GISystem that solves a spatial problem using the main stages of GIS Design
  • Write a proposal describing a GISystem Design
  • Justify the development, implementation, and evaluation of the GIS design
  • Complete and discuss a variety of geospatial technology lessons
  • Apply and discuss the different stages of GIS design.

Throughout the semester you will be exploring some existing and new technologies, including proprietary (ESRI) technology as well as open-source technology and data sources. The technology covered in the first 5 modules of the course will include WebGIS proprietary and open-source software, architecture, and data. Then, the last 5 technologies will focus on new technology trends including cloud computing, deep learning, 3D mapping, and GeoAI.

Diagram of the lessons covered in this course
Figure 2: The technology lessons covered in this course. The first five lessons are focused on Design Software including WebGIS, software, data, and enterprise design, and are seen in the leftmost column. The right column shows the last five lessons, which focus on new geospatial technology such as deep learning and GeoAI.
Credit: Brandi Gaertner © Penn State is licensed under CC BY-NC-SA 4.0