GEOG 150 - Geographic Information Science and Spatial Reasoning
Fall Semester 2015
Basic Course Information
Courses numbered 1 - 49 are remedial or college preparatory courses which do not apply toward an A. A. Degree and are not intended for transfer. Courses numbered 50-99 apply toward an AA Degree, but are not intended for transfer. Courses numbered 100 and higher apply toward an AA Degree and/or are intended for transfer to a four-year college or university.
D - Credit - Degree Applicable
GEOG
Geographic Information Science and Spatial Reasoning
Units and Hours
3
3
Grade/Pass/No Pass
Hour Type
Units
Weekly Hours
Semester Hours x 16 Weeks
Semester Hours x 18 Weeks
Lecture Category -
3.00
3.00
x 16 Weeks - 48.00
x 18 Weeks - 54.00
Lab Category -
0.00
0.00
x 16 Weeks - 0.00
x 18 Weeks - 0.00
Subtotal -
3.00
x 16 Weeks - 48.00
x 18 Weeks - 54.00
Out of Class Hour -
6.00
x 16 Weeks - 96.00
x 18 Weeks - 108.00
Totals -
9.00
x 16 Weeks - 144.00
x 18 Weeks - 162.00
Hour Type
Units
Weekly Hours
Semester Hours x 16 Weeks
Semester Hours x 18 Weeks
Lecture Category -
3.00
3.00
x 16 Weeks - 48.00
x 18 Weeks - 54.00
Lab Category -
0.00
0.00
x 16 Weeks - 0.00
x 18 Weeks - 0.00
Subtotal -
3.00
x 16 Weeks - 48.00
x 18 Weeks - 54.00
Out of Class Hour -
6.00
x 16 Weeks - 96.00
x 18 Weeks - 108.00
Totals -
9.00
x 16 Weeks - 144.00
x 18 Weeks - 162.00
Requisites
To satisfy a prerequisite, the student must have earned a letter grade of A, B, C or P(Pass) in the prerequisite course, unless otherwise stated.
Prerequisite: MATH 60
Catalog Description
An introduction to spatial analyses and spatial distribution theories within the field of Geographic Information Science (GISci). Students will learn about fundamentals of cartography, GIS theory, global positioning systems, spatial relationships, and remote sensing in this course. Students will analyze environmental problems and the human landscape by using open-source GIS software packages to visualize, query, manipulate, and interpret temporal and spatial data.
Student Learning Outcomes
Outcome
Student will describe the scientific method, including the formulation of a problem, the collection of data through observation and experiment, and the formulation and testing of a hypothesis.
Students should be able to interpret the output from ordinary least squares regression.
Specific Course Objectives
Objective
Upon successful completion of the course, the student will be able to:
Explain the components of different coordinate systems and map projections;
Identify and analyze the spatial distribution of environmental problems by integrating Geographic Information Science theories with geospatial technologies;
Identify and analyze the spatial distribution of anthropogenic features by integrating Geographic Information Science theories with geospatial technologies;
Describe the different components of a Geographic Information System, and their functions;
Describe the different components of a Global Positioning System, and their limitations;
Describe the different components of Remote Sensing, and potential sources of data collection and analytical errors;
Create, edit, and validate simple geographic and attribute data;
Create effective maps that comply with the theories of Visual Hierarchy and Intellectual Hierarchy;
Identify trends, patterns, and relationships found in spatial and temporal data;
Analyze, compute, and interpret mathematical solutions to spatial problems using spatial statistics and algebra.
Methods of Instruction
Methods of Instruction may include, but are not limited to, the following:
Demonstration
Discussion
Lab
Learning Modules
Lecture
Videos/Film
Content in Terms of Specific Body of Knowledge
Geographic Information Science (GISci)
Scientific Method
Map Scale and Data Resolution
Cartography
Intellectual and Visual Hierarchy theories
Coordinate Systems and Projections
Geographic coordinate systems
Projected coordinate systems
Conversion between coordinate systems
Reprojection and datum transformations
Georeferencing and root mean square error calculation
Spatial Analysis and Coordinate Geometry
Structured Query Language (SQL)
Locational query
Attribute query
Basic Spatial Statistics and Regression
Hypothesis testing
Assumptions and frequency distributions (e.g. normal, Poisson)
Calculation and interpretation of statistical measures in geography (Trends, Patterns, and Clusters)
Geographic mean center
Geographic median center
Central feature
Standard distance deviation
Standard deviational ellipse
Ordinary least squares regression
Limitations and assumption violations (e.g. misspecification, autocorrelation)
Modifiable Areal Unit Problem
Spatial Data and Geospatial Technologies
Origin of spatial data and data types
Nominal
Ordinal
Ratio
Interval
Data accuracy vs. data precision
Metadata
Geographic Information Systems
Global Positioning Systems
Remote Sensing
Open source systems
Proprietary systems
Analysis with GISci and Geospatial Technologies
Analysis of physical landscapes and natural hazards
Concentration of environmental problems and Tragedy of the Commons
Spatial distribution of biodiversity hotspots and anthropogenic impacts
Analysis of human population growth and demography
Spatial distribution of industries and economic geography
Trends and spatial clustering of crimes.
Textbooks/Resources
Textbook
Schoenherr, Allan
A Natural History of California
University of California Press
1995
Krygier, John; Wood, Denis
Making Maps, Second Edition: A Visual Guide to Map Design for GIS
2nd
The Guilford Press
2011
Middleton, Nick
The Global Casino: An Introduction to Environmental Issues
4th
Oxford University Press
2008
Mitchell, Andy
The ESRI Guide to GIS Analysis: Volume 2: Spatial Measurements and Statistics
1st
ESRI Press
2005
Mitchell, Andy
The ESRI Guide to GIS Analysis Volume 1: Geographic Patterns & Relationships
1st
ESRI Press
1999
Software
Google Earth
v.6
Google
ArcGIS Explorer
1500
ESRI
ArcGIS Explorer Online
Online
ESRI
ImageJ
1.44
National Institutes of Health
Used for remote sensing analysis.
Assignments
Journal articles and text on Geographic Information Science theories and spatial analysis. Case studies on the applications of geospatial technologies (GIS, GPS, Remote Sensing) in analyzing environmental problems and anthropogenic features will also be required in this course.
One or more assignments chosen from the following options:
- Weekly laboratory write-ups (2 - 3 page report of results and conclusions)
- Case Study Analysis (2 - 3 page essay)
- Semester Project (8 - 10 page term paper)
Students will complete laboratory exercises that require them to integrate Geographic Information Science and geospatial technologies in order to solve spatial problems (e.g. finding point sources of river contaminants). In their semester projects, students must demonstrate a clear understanding of the applications of mathematics in spatial analysis.
Students are expected to research novel applications of geospatial technologies in other disciplines by reading trade publications (e.g. ArcUser) or by interviewing industry professionals.