Restricted Access for Students in:
Lectures/Labs SAL

 

 

Spatial Information Technologies

Ocean 452/Fish453

Ocean502/Fish502:

 

Monday - Lecture, 2:30 - 3:50
Ocean Science Building: Room 425

Wednesday - Labs:
   Morning, 9:00 - 10:20
      or
  Afternoon, 2:30 - 3:50
Ocean Science Building: Room 111

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Course Overview :

 

The Spatial Information Technologies of GPS (Global Positioning Systems), GIS (Geographic Information Systems) and Remote Sensing have made major advances in both the theoretical and applied basis for studies in the earth sciences. These technologies have become key components of interdisciplinary research and resources management practice. This course is designed to introduce the use of GPS, GIS and Remote Sensing in the ecosystem sciences. In this course each student will participate in the collection of georeferenced field measurements and observations (GPS), importing those spatial data into a GIS, classifying the landcover over the spatial extent of those data from remotely sensed imagery, and analyzing their spatial variability. This applied course is intended to integrate these technologies in an applied setting, and to motivate students to incorporate these tools and techniques in their future work.

 

At the conclusion of this course the student will be able to:

Global Positioning Systems:

  • Identify sources of error in position accuracy

  • Conduct a survey plan that insures position accuracy requirements

  • Use the industry standard interface settings to mark, import, and export data.

Geographic Information Systems:

  • Identify the options for spatial representation of objects

  • Create a geodatabase from observational data

  • Create and manage basic spatial metadata

  • Work effectively with both vector and raster spatial data

  • Generate surface data from point samples

  • Generate spatial pattern metrics from classified or thematic data

  • Create cartographic products (maps).

Remotely Sensed Satellite Image and/or Shipboard Multibeam Sonar data Processing:

  • Describe the properties of the electromagnetic spectrum used in remote sensing

  • Identify spectral signature characteristics which distinguish various surfaces

  • Describe basic clustering algorithms used to classify multidimensional data

  • Discuss the principles of error propagation in remotely sensed data.

Spatial Patten Analysis:

  • Describe the criteria for appropriate metric selection 

  • Generate spatial composition and configuration metrics


Grading policy

Undergraduate student grades will be based upon two exams (70%), a team project (20%), and completeness of a lab journal (10%).  The labs, while not graded, are to be completed by each individual and reviewed each week with the teaching assistant or instructor and must be complete and well documented.

 

Graduate student grades will be based upon two exams (60%), a team project (10%), and an “individual project” complimenting the student’s graduate plan of study (20%).  The labs, while not graded, are to be completed by each individual and reviewed each week with the teaching assistant or instructor and must be complete and well documented.


Field Trips

There is one scheduled field trip to the Big Beef Creek Field Station on Hood Canal (or other suitable field site).  While this trip is not "required" it is highly recommended that students make every effort to participate in this outing.  During this field trip students will sample a suite of environmental variables which are later correlated to surface reflectance values measured at the satellite sensor and represented as a digital multispectral image.  Similarly, example multibeam sonar data will be verified. Strategies for optimizing spatial sample design and remote sensing ground truth and accuracy assessments will be tested. 


Time Requirements and Expectations

In the past, we've found that students spend about 1.5 hours each week outside of class in the lab working on the lab exercises.  This increases to about 2+ hours during the last few weeks when working to complete their projects.  Our expectation is that students will put more time into "labs" when the skills they are developing meet some need they have for their individual research or other class assignments.  Therefore, some students will spend a good deal of time in the lab and their projects will often go well beyond what is required for the course.  The instructors are always available to help students complete the labs and design and complete an individual project that matches with the skill level the student hopes to achieve.