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DRPS : Course Catalogue : Edinburgh College of Art : Architecture and Landscape Architecture

Undergraduate Course: Landscape Fieldwork Lab (ARCH10049)

Course Outline
SchoolEdinburgh College of Art CollegeCollege of Arts, Humanities and Social Sciences
Credit level (Normal year taken)SCQF Level 10 (Year 3 Undergraduate) AvailabilityNot available to visiting students
SCQF Credits20 ECTS Credits10
SummaryThe Landscape Fieldwork Lab is a course dedicated to exploring digital tools that have uses in landscape fieldwork. Part seminar, part workshop, it introduces students to technologies suitable for in-situ sensing and recording information beyond just the visual. Without the pressure of "moving on" to design, participants are free(r) to experiment with tools, methods and workflows that will enhance their design skills.
Course description Many tools commonly used in desktop research in the field of landscape architecture and allied disciplines work with information that originates in remote-sensing, e.g. satellite imagery or lidar surveys. While the data that these tools (such as GIS) allow us to access is site-specific and undoubtedly powerful, it often has limitations related to coverage, scale and resolution - alongside other more hidden issues.

Fieldwork is crucial in understanding the spatial qualities and realities of a place. The 'outcome' is typically a mix of impressions, photographs and perhaps some sketches or samples that usually speak a different language than cartographic research. At the same time, virtually everyone carries a device capable of geolocation as well as sensing and recording various other types of data; commercial UAVs (drones) are now commonplace; microcontrollers such as Arduino and single-board computers such as Raspberry Pi make it possible to set up a mini weather station anywhere, and so on. Because of their ability to facilitate in-situ ('in place') sensing, these tools have a lot of potential in landscape fieldwork.

The Landscape Fieldwork Lab offers the chance to explore and develop tools and workflows that can help lessen or close the gap between fieldwork and cartographic research. Through seminars and practical work, students will build an understanding of what technologies can help designers get 'more' out of their fieldwork - in terms of the type, quality, quantity and degree of precision of information gathered.

Self-directed experiments supported by tutorials will allow students to test not only different digital tools (such as an Arduino equipped with sensors) and fieldwork methods but also sensing different 'things'. The emphasis will be on making systematic observations that not only register the characteristics and sensory experience of a space but are also compatible with GIS/CAD.

The course strives to create a laboratory-like environment: a place for experimentation, discovery and exchange. This requires active engagement, curiosity and a willingness to carry out independent research. In return, students get a chance to develop valuable skills that industry doesn't know to ask for yet, as well as gain more autonomy as practitioners by transitioning from simply consuming spatial data to producing it themselves.

The Landscape Fieldwork Lab runs through weeks 1-11. A weekly half-day of contact teaching (seminar/workshop or tutorials) supports more self-directed fieldwork experiments.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Course Delivery Information
Academic year 2023/24, Not available to visiting students (SS1) Quota:  15
Course Start Semester 1
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 200 ( Seminar/Tutorial Hours 20, Supervised Practical/Workshop/Studio Hours 18, Fieldwork Hours 12, Feedback/Feedforward Hours 1, Formative Assessment Hours 1, Summative Assessment Hours 1, Programme Level Learning and Teaching Hours 4, Directed Learning and Independent Learning Hours 143 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) This course comprises of 3 assessment components:
Experiment 1 (10-minute presentation) 30%, due in week 6
Experiment 2 (10-minute presentation) 30%, due in week 11
Course log (1000 words) 40%, due in the exam period

The two unconnected 'experiments' will test the student's ability to plan and execute fieldwork, and to process and present its results in a review setting using a combination of digital or analogue media and verbal communication.

The course 'log' will be a collection of materials that evidence the research, process and reflection undertaken by the student during the semester. This should be tied together by an introductory text and a conclusion.

More specific instructions on assessment components will be given in the course syllabus.
Feedback Formative feedback/feedforward on the work-in-progress experiments will be given verbally in tutorials throughout the semester.

Summative feedback for the experiments will be given verbally during reviews (in weeks 6 and 11). For the log, written summative feedback will be provided after the final submission as per University regulations.
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. Understand and critique ways of producing spatial data and how different (digital) tools can be used for in-situ sensing.
  2. Select appropriate tools for carrying out fieldwork in a systematic way, and produce original and creative datasets that are relevant for design purposes.
  3. Process self-produced data, and present both fieldwork and its results with clarity and sophistication.
Reading List
Ferrari, M., Pasqual, E. & Bagnato, A. (2019) Italian Limes: Project Report. In: A Moving Border. Alpine Cartographies of Climate Change. New York: Columbia, pp. 174-193.

Girot, C. & Hurkxkens, I. (eds.). (2015) Field Instruments of Design: Pamphlet 19. Zurich: gta Verlag.

Jenkins, K. (2018) Field exercises. In: Journal of Landscape Architecture, 13(1), pp. 6-21.

Melsom, J. Fraguada, L. & Hurkxkens, I. (2017) Onsite Analysis: Developing a Flexible Software Fieldkit for Landscape Architecture and Spatial Design. In: Journal of Digital Landscape Architecture, 2017(2), pp. 262-270.

Pirokka, M., Ellis, E. C. & Tredici, P. D. (2015) Personal Remote Sensing: Computer Vision Landscapes. In: Fard, A. & Meshkani, T. (eds.), New Geographies 07: Geographies of Information. Cambridge, MA: Harvard Graduate School of Design, pp. 178-187.
Additional Information
Graduate Attributes and Skills Research and Enquiry - apply critical understanding of some of the ways in which geospatial data can be produced and used

Personal and Intellectual Autonomy - apply autonomy in gathering geospatial data/information that is relevant in the context of landscape design

Personal Effectiveness - bridge the gap between desktop research (GIS mapping in particular) and fieldwork by using in-situ sensing, as well as present data with clarity and sophistication using digital and physical material, images and words
Keywordslandscapes,fieldwork,in-situ sensing,geospatial data
Course organiserMs Milja Tuomivaara
Course secretaryMrs Abbie Humphreys
Tel: (01316) 502306
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