Syllabus
Instructor email: [email protected]
Standard Course Outline prepared by Drs. S. Wechsler, C. Lee and V. Del Casino for California State University, Long Beach College of Liberal Arts, Department of Geography. Adapted for web (and slightly modified) by Alex Pakalniskis.
Course overview
Spatial information technologies including remote sensing are evolving rapidly and are being utilized in a wide variety of areas. This course focuses on Python-centric development and analytical approaches within remote sensing and GIS. The course contributes to the development of competencies that are essential to success in the geospatial and broader technology industry workforce.
Course Objectives and Measurable Outcomes
Upon successful completion of the course, the student will be able to:
Technical
Identify and assess relationships between geospatial technologies.
Comprehend theory and the application of geospatial technologies.
Develop technical literacy through hands-on training in geospatial technologies and their application.
Integrate primary and secondary data into GIS.
Perform various spatial analysis procedures.
Acquire theoretical and practical knowledge of remote sensing satellites and techniques.
Describe types and sources of satellites remote sensing systems, and multidisciplinary concepts of both photography and imagery analysis.
Demonstrate an appreciation of the role of remote sensing in geospatial science.
Integrate remotely sensed data with other geospatial techniques such as GIS
Analytical
Evaluate methods and approaches used to address a variety of GIScientific issues.
Examine a spatial question and analyze geospatial data using GIS tools and technologies.
Perform analyses using remote sensing and image analysis techniques.
Assess both the value and limitations of remotely sensed data for a variety of applications.
Business
Explain and evaluate the importance of professional ethics and rules of conduct.
Interpersonal
Develop and apply oral and written communication skills.
Methods of instruction
Lectures
Lectures will be comprised of two components: the presentation of theoretical and conceptual material essential to the understanding of particular geospatial techniques the linkage of this substantive information with practical application examples using GIS software
YouTube videos
Presentation of theoretical and practical materials related to geospatial programming
Group discussions
Open-ended chats to cover recent trends and developments in (spatial) technology.
Methods of Assessment
Computer Laboratory Exercises
The purpose of these exercises is to assess the students' ability to synthesize, evaluate, and apply the material presented in lecture in practice laboratory assignments. Students should illustrate their ability to combine multiple techniques in order to answer a spatial problem.
The instructor will assess the completeness of each student's lab assignments in both qualitative and quantitative ways.
A minimum of 6 computer lab exercises will be assigned. No individual lab assignment will be worth more than one-third of the final course grade.
The last lab will count as the final exam.
Extra credit opportunities
The instructor will provide no less than 3 extra credit opportunities throughout the semester. Example opportunities include attending a virtual conference and writing a brief summary or an independent coding project.
Grading policy
A
≥90%
B
≥80% & <90%
C
≥70% & <80%
D
≥60% & <70%
F
<60%
Late assignment policy
I'll deduct 0.2 points for each day late you submit an assignment. Please turn things in on time 😍.
1
0.2
5
1
10
2
20
4
Helpful links
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