Effective Term: Fall 2015
COURSE OUTLINE FOR CREDIT COURSE
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 5099 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 fouryear college or university.
Discipline:
GEOG
Course Number: 150
Title: Geographic Information Science and Spatial Reasoning
Course Number: 150
Title: Geographic Information Science and Spatial Reasoning
Units and Hours
Units: 3.00
Grade Option:
Grade/Pass/No Pass
Course Length in Weeks:
Min Weeks  16 Max Weeks  18
Min Semester Hours
Hour Type
Hours
Min Semester Hours
Max Semester Hours
Lecture Category
3.00
48.00
54.00
Lab Category
0.00
0.00
0.00
Subtotal
3.00
48.00
54.00
Out of Class Hour
6.00
96.00
108.00
Totals
9.00
144.00
162.00
Max Semester Hours
Hour Type
Hours
Min Semester Hours
Max Semester Hours
Max Lecture Category
3.00
48.00
54.00
Max Lab Category
0.00
0.00
0.00
Max Subtotal
3.00
48.00
54.00
Max Out of Class Hour
6.00
96.00
108.00
Max Totals
9.00
144.00
162.00
Grading Basis:
Grade/Pass/No Pass
Basic Skills Requirements: Appropriate Language and/or Computational Skills.
Basic Skills Requirements: Appropriate Language and/or Computational Skills.
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  
Corequisite (Course required to be taken concurrently): None  
Prerequisite: (Completion of, or concurrent enrollment in): None  
Recommended Preparation: None  
Limitation on Enrollment (e.g. Performance tryout or audition): None 
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 opensource GIS software packages to visualize, query, manipulate, and interpret temporal and spatial data.Student Learning Outcomes
Upon successful completion of the course, the student will be able to: 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
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 Discussion
 Lab
 Learning Modules
 Lecture
 Videos/Film
 Demonstration
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
 Origin of spatial data and data types
 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
Textbooks  


Software  

Assignments
Required Reading:
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.
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.
Required Writing:
One or more assignments chosen from the following options:  Weekly laboratory writeups (2  3 page report of results and conclusions)  Case Study Analysis (2  3 page essay)  Semester Project (8  10 page term paper)
Critical Thinking:
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.
Outside Assignments:
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.
Students are expected to spend a minimum of three hours per unit per week in class and on outside assignments, prorated for shortterm classes.
Methods of Assessment
Methods of Assessment may include, but are not limited to, the following: Class Participation
 Class Work
 Demonstration
 Exams/Tests
 Field Trips
 Homework
 Lab Activities
 Papers
 Projects
 Research Projects