GIS101: Foundations of
Geographic Information Science

Dr. Abu Badruddin
Office: M274 Main Building
Live: (315) 255-1743
Fax : (315) 255-2117



Getting to Know ArcGIS, 2nd Edition, ESRI Press (required)

  1. GIS Fundamentals
    Paul Bolstad, Eider Press
  2. Geographic Information Systems and Science
    Longley, Goodchild, Maguire, and Rhind, John Wiley & Sons

Course Purpose:

This course is an introduction of geographic information science designed to provide students with the fundamental concepts of spatial understanding and analysis. This course is divided into lectures and lab sessions. The conceptual elements are explained and discussed in the lecture sessions while the labs are designed to provide hands-on training to reinforce the concepts and lessons learned in the lectures.

Course Objectives:

At the conclusion of the course, students will:

  1. be aware of the basic structures and functionality of GISs.
  2. learn how to use the technology, at the basic level, to collect, visualize, manipulate, analyze, and interpret geographic data from a diverse source
  3. be able use a desktop GIS package (ArcGIS) for typical spatial analysis.
Laboratory Exercise:

Each lab assignment will be considered as an exercise and is due following week. Late submission will not be accepted! Please see me if you have an emergency. Laboratory exercises will contribute substantially to your course grade. Students may be asked to repeat work that is not satisfactory.


*** The above grading is subject to change at the instructor's discretion ***


GIS:101 Foundations of GIS
Lecture Topics Outline
Week 1 Course introduction, What is GIS? What a GIS is not.
LAB: File management and network resources
Week 2 An overview of GIS data: spatial and attribute data, data vs. information
LAB: Introduction to ArcGIS
Week 3

Maps and its characteristics: Concept of scale, accuracy, and standards
LAB: Map reading/viewing and exploring spatial data

Week 4 Map composition and design
LAB: Designing your company LOGO
Week 5 Symbolizing and classifying spatial data
Lab: Working with map symbology & map classification
Week 6 Introduction to Global Positioning System (GPS)
Lab: GPS data collection and downloading
Week 7

Midterm Exam
Lab: Practice Exam

Week 8 Spatial & attribute query
Lab: Selecting features based on attributes
Week 9

Spatial & attribute query (cont.)
Lab: Selecting features based on spatial relationship

Week 10

Spatial data models (raster and vector), advantages, limitations, and examples
Lab: Working with image data

Week 11

Data Automation: creating and editing spatial data
Lab: Making a map of your neighborhood

Week 12

Data Automation: creating and editing spatial data (cont.)
Lab: Editing spatial data and adding attributes

Week 13 Thanksgiving
Lab: Joining and linking attribute data
Week 14

Spatial modeling with map overlay
Lab: GeoProcessing

Week 15

Advanced topic and review
Lab: Practice Exam

Week 16 FINAL!

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