Postgraduate taught 

Archaeology MSc

Remote Sensing for Human Ecology and Archaeology ARCH5102

  • Academic Session: 2021-22
  • School: School of Humanities
  • Credits: 20
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Either Semester 1 or Semester 2
  • Available to Visiting Students: Yes
  • Available to Erasmus Students: Yes

Short Description

Airborne and satellite remote sensing is essential to investigating the human dimensions of global change, and understanding interactions between human activities and the environment in the past and the present. Students will complete individual exercises and group projects in order to learn to process, analyse and interpret airborne and satellite remote sensing data in the context of human ecology and archaeology research. They will also prepare project applications to practice research design for archaeology and human ecology projects integrating airborne and satellite remote sensing components.

Timetable

This is a blended course, with self-paced online and in-classroom components. The course includes 11 practical modules that run online and 4x4hr workshops and 1x4 hour seminar that will run during the semester as scheduled in MyCampus. In addition, students will be expected to meet with the instructor twice during the semester to discuss their project.

Excluded Courses

ARCH4069 Remote Sensing

Co-requisites

None

Assessment

Essay (2,000 words) - 30%

Project Application (1,000 words) - 10% 

Set Exercises (1-3 hours per set of recorded lectures and exercises, completed at student's own pace online) - 30% 

Project (1,500 words+ data analysis files and website link) - 30%

Main Assessment In: April/May

Course Aims

This course will provide the opportunity to:

■ gain practical, hands-on experience working with data and software.

■ apply practical skills to respond to domain specific questions

■ participate in the informed discussion of the intersection of the practice of remote sensing analysis and key theoretical frameworks in interdisciplinary landscape studies

■ develop transferable skills in digital data analysis, digital data management, and web communication

■ develop the ability to plan and undertake increasingly independent work

Intended Learning Outcomes of Course

By the end of this course, students will be able to:

■ Identify and apply the set of techniques needed to solve a given problem in applied remote sensing

■ Critically assess data quality and evaluate the requirements for complex projects

■ Analyse and interpret digital topographic and spectral data to address questions in human ecology and archaeology

■ Create effective data visualizations to present the results of complex analyses and interpretations 

■ Employ transferable skills in digital data management and web communication in a research context

Minimum Requirement for Award of Credits

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.