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.

Discipline: GEOG
Course Number: 132
Title: Database Management and Data Acquisition

Units and Hours

Units: 4.00
Grade Option: Grade/Pass/No Pass
Course Length in Weeks: Min Weeks - 16 Max Weeks - 18
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Grading Basis: Grade/Pass/No Pass
Basic Skills Requirements: Appropriate Language and/or Computational Skills.


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: None
Corequisite (Course required to be taken concurrently): None
Prerequisite: (Completion of, or concurrent enrollment in): GEOG 120
Recommended Preparation: None
Limitation on Enrollment (e.g. Performance tryout or audition): None

Catalog Description

Course provides students with knowledge and practical experience in the fundamentals of database management, and the acquisition, conversion, and creation of spatial data within Geographic Information Systems (GIS). Topics to include strategic design, querying, modeling techniques, data appropriateness and accuracy, hardware and software requirements, conversion of digital data, creating digital data using digitizers, scanners and Global Positioning Systems (GPS), and utilization of remote sensing, photogrammetry, and web-based data. This course provides hands-on experience with database management and data acquisition using ArcGIS software.

Student Learning Outcomes

Upon successful completion of the course, the student will be able to:
  1. Students should be able to distinguish geographic coordinate systems from projected coordinate systems.
  2. Students should be able to explain the functions of configuring an attribute domain.

Specific Course Objectives

Upon successful completion of the course, the student will be able to:
  1. Identify portals of spatial data from governmental, nonprofit, and private sources.
  2. Create vector datasets using manual, interactive, and heads-up digitization techniques.
  3. Analyze remote sensing images and their attributes.
  4. Convert and transfer remote sensing data into a geographic information system.
  5. Operate a GPS receiver and download the acquired data to a geographic information system.
  6. Evaluate the quality, reliability, and functionality of acquired data sets.
  7. Apply skills in converting digital data from one format to another (e.g. vectorization, rasterization).
  8. Demonstrate skills in interpreting and utilizing remote sensing data.
  9. Identify and describe the components of a file geodatabase and a personal geodatabase.
  10. Construct and manipulate data within existing databases.
  11. Create databases used for storing and organizing raster and vector data.
  12. Construct basic spatial and attribute query statements within a GIS.
  13. Construct and analyze spatial networks.
  14. Create raster datasets using scanners and georeferenced remote sensing images.
  15. Analyze field data (e.g. from GPS) and troubleshoot potential importation issue.
  16. Appreciate the importance and implementation of topology in feature datasets.
  17. Define basic remote sensing terminologies (e.g. temporal, spatial, spectral resolutions).
  18. Describe the process that goes into creating selective GIS datasets that are currently in the public domain.
  19. Perform intermediate-level geoprocessing tasks.

Methods of Instruction

Methods of Instruction may include, but are not limited to, the following
  1. Demonstration
  2. Discussion
  3. Group Projects/Activities
  4. Learning Modules
  5. Lecture

Content in Terms of Specific Body of Knowledge

  1. Introduction to database management
    1. Spatial database concepts and considerations
      1. Data types
      2. Tuning
      3. Indexing
      4. Security
    2. Structured query language in GIS
  2. Data conversion between CAD and GIS
    1. Georeferencing
      1. Linear transformation
    2. Attributes
      1. Query
      2. Object loader
  3. Creation of domains and subtypes
    1. Domains
      1. Coded value
      2. Range
    2. Subtypes
    3. Default values
  4. Spatial analyses
    1. Spatial statistics
      1. Mean center
      2. Standard deviational ellipse
      3. Hotspot analysis
    2. Spatial data mining
  5. Geodatabase
    1. Creation and maintenance of geodatabases
    2. Components of geodatabases
      1. Feature dataset
      2. Feature classes
  6. Data collection and creation
    1. Remote sensing
      1. UAV
      2. Photogrammetry 
    2. Sources of census, landcover, and hydrologic data
    3. Geocoding addresses
    4. Field survey techniques with GPS
      1. ArcPad
      2. Collector App
      3. Web App
    5. Cost considerations associated with acquiring and creating data
    6. Open source and web-based GIS
    7. Data digitization
      1. Automated digitization
      2. Interactive digitization


  1. Arctur, Michael; Zeiler, Michael. Designing Geodatabases: Case Studies in GIS Data Modeling. ESRI Press, 2004.
  2. Allen, David; Coffey Jeffery. GIS Tutorial 3: Advanced Workbook. Esri Press, 2010.
  3. Zeiler, Michael. Modeling Our World: The ESRI Guide to Geodatabase Design. 2nd ESRI Press, 2010.
  4. Konecny, Gottfried. Remote Sensing, Photogrammetry and Geographic Information Systems. Taylor and Francis, 2002.
  5. Calvo, Kike. So You Want to Create Maps Using Drones. Blurb, 2016.


Required Reading:
Students will read professional case studies that have successfully created, implemented, and maintained geodatabases. In addition, journal articles will also be assigned in order to help students decide on their semester projects.

Suggested Reading:
Students are encouraged to actively conduct independent research and review online resources in order to stay current with the technology.

Required Writing:
One or more assignments chosen from the following options: -Article Review (2 - 3 page essay) -Case Study Analysis (2 - 3 page essay) -Semester Project (5 - 6 page term paper)

Critical Thinking:
Students will be required to critically review a case study/project that exemplified the usage of a geodatabases or relational database management system. In addition, students are asked to evaluate the appropriateness of various data sources for their semester projects.

Outside Assignments:
Outside assignments will include reading texts, review of lecture notes, writing assignments, GIS computer lab assignments, and exam preparation. 8 hours per week.

Students are expected to spend a minimum of three hours per unit per week in class and on outside assignments, prorated for short-term classes.

Methods of Assessment

Methods of Assessment may include, but are not limited to, the following:
  1. Exams/Tests
  2. Homework
  3. Papers
  4. Research Projects

Open Entry/Open Exit

Not Open Entry/Open Exit


Course is Repeatable for Reasons other than a Deficient Grade? No

Contact Person

Wing H. Cheung