Remote Sensing

Course manual 2023/2024

Course content

Remote Sensing - sensing our environment from a distance -  includes a powerful set of computational techniques and methods for storing,  analyzing and visualizing information retrieved from satellite imagery, aerial photographs or other means of remote sensing, such as geophysical prospecting, like Light Detection and Ranging (LiDAR). Here, techniques will be introduced to guide students through the basics of remote sensing using the ArcGIS Pro software environment.

In nine self-tuition assignments we offer GIS-based tools and techniques, such as various pre-processing techniques, suitability analyses, raster-based analysis, model building,  and path-distance analysis. The remote sensing tools and techniques include, for example, supervised classification techniques, change analysis, band-ratio analysis, image enhancement and computing of vegetation and other spectral indices which can be used in food production, and/or land use and land cover change applications.

Images and datasets used are highly diverse and range from Digital Elevation Models (DEMs), Landsat imagery, SPOT imagery, Sentinel imagery,  orthophotos to thematic layers such as digital soil, geomorphological, Land Use Land Cover and other data.

The techniques and skills are applied in the assignments to a wide variety of landscapes and environments, and to diverse situations and/or topics such as flooding in Bangladesh, geodiversity and coffee growth in Hawaii, Land Use and Land Cover change in China, burial mounts in the Netherlands, and more.

After finishing 9 mandatory individual assignments, students continue with a project in teams of two. This results of the research project is documented in a technical remote sensing report with accompanying digital products.  

Study materials

Literature

• Various scientific papers which will be available via links on Canvas

• A remote sensing tutorial focussing on theory is available via: https://www.nrcan.gc.ca/sites/www.nrcan.gc.ca/files/earthsciences/pdf/resource/tutor/fundam/pdf/fundamentals_e.pdf 

Practical training material

• 9 Quizzes, available on Canvas, datasets, tutorials

Software

• ArcGIS Pro - to be installed on own laptops before the course starts

Other

• 2 Lectures - remote sensing introduction, and information on the project

Objectives

• The student can explain the basic concepts of remote sensing such as: wavelengths, spatial/temporal/spectral resolution, absorption & reflection, band ratios, NDVI, supervised classification.
• The student can select, download and pre-process satellite images for use in spatial analyses.
• The student can apply remote sensing tools and techniques using ArcGIS Pro software for the identification, mapping and quantification of information from satellite images.
• The student can analyze geodiversity by computing an index based on derivatives from a digital elevation models and thematic datasets such as geology and soils.
• The student can design and execute a remote sensing project to analyze and interpret Land Use and Land Cover change.
• The student can write a technical remote sensing report and manage digital remote sensing (meta)data.

Teaching methods

• Lecture
• Self-study
• Computer lab session/practical training

The lecture is an introduction into the course set-up and the theory of remote sensing and helps you to understand the theory, relevance, but also the complexity of remote sensing tools and techniques. The laptop computer lab sessions / practical training offer a wide range of skills and examples remote sensing applications and its products using the ArcGIS software.

Learning activities

Attendance

Programme's requirements concerning attendance (OER-B):

• Participation in fieldwork is compulsory and cannot be replaced by assignments or other courses.
• In case of practical sessions, the student is obliged to attend at least of 90% of the sessions and to prepare himself adequately, unless indicated otherwise in the course manual. In case the student attends less than 90%, the practical sessions should be redone entirely.
• In case of tutorials/seminars with assignments, the student is obliged to attend at least 7 out of 8 seminars and to prepare thoroughly for these meetings, unless indicated otherwise in the course manual. If the course has more than 8 seminars, the student can miss up to 1 extra meeting for every (part of) 8 tutorials/seminars. If the students attends less than the mandatory tutorials/seminars, the course cannot be completed.

Additional requirements for this course:

The course is on campus, the presence and absence rules are as follows:

• Participation in the practical sessions is mandatory.
• Presence / absence is registered by the teachers. In case of absence, always inform the teacher of your group
• You are allowed to miss 1 of the practical sessions, that is registered as: one (1) absence (see OER). Note: the related quiz of that day should be made finished and handed in before the end of the course.
• If you miss more than one laptop session without a valid reason, you can be excluded from the course.

Attending lectures is strongly advised. By doing so, you actively contribute to a lively learning community and significantly improve your chances of successfully completing the course.

The designated mandatory practical sessions play a crucial role in achieving the course objectives and are essential for your overall progress. In addition, Remote Sensing and GIS skills are crucial for follow-up courses in your curriculum.

By registering for this course, you are complying with the rules regarding attendance and agreeing to actively prepare for and participate in the mandatory activities.

Assessment

For each quiz there is a deadline, which is 2-3 days after the practical session at 17.00 . After the deadline, submission will be closed. There is a resit possibility for all individual quizzes during the last week of the course. Submission on Canvas will be opened for one week for those who did not meet the first deadline. The maximum grade for each newly submitted quiz is 7.0. In case this resit in week 50 is not met, there will be a resit in February 2024. Two weeks before that deadline submission will be reopened for those who did not meet the resit during the last week of the project. The maximum grade for an individual resit module in February 2024 is 6.0.

Deliverables for the project assignment are: 1. a technical report and 2. a digital map package which will both be evaluated using evaluation rubriks. Not meeting the deadline in December means a resit in February 2024. Re-submission will be possible starting two weeks before the resit date. Maximum grades for the technical report resit and the digital map package resit will be 7.0.

Assessment diagram

Students that were enrolled in the course in previous years

Students enrolled last year: your grades of partial assignments are still valid this year. Students from earlier years: need to retake all mandatory assignments

Inspection of assessed work

Up to 20 days after the announcement of the result students have the right of inspection of their individual work (all forms
of assessment) on Canvas. Feedback is given by means of Canvas (automated tests and standard grading of these tests). Feedback for each module is placed on Canvas as soon as all students of all groups have finished and saved their tests for that module. In the week after the last Module is due, feedback to all of the modules will be disclosed on Canvas, so that students can inspect their whole work. During an individual appointment you can discuss the the assessment. For this course we will NOT schedule a Collective Assessment Evaluation. Please note: you lose the right of feedback when you don’t make an appointment within 20 days after the announcement of the results without good reasons.

The quizzes numbered 1-9 are individual assignments. These will mostly be reviewed automatically, and partly by staff.

The project is an activity for two students. Details will be posted on Canvas. Inspection of the work can be requested in contact with the coordinator or the group assistant.

Assignments

Individual assignments: 9 quizzes (numbered Module 1- Module 9), see for preliminary title under Course structure. Detailed descriptions are provided on the Canvas site for each assignment. Feedback is mostly digital within the quizzes.

Team assignment: 1 technical report and a project package. Feedback during the laptop practicals.

All quizzes, the project technical report and the map package are graded.

Fraud and plagiarism

The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl

Course structure

Honours information

Not applicable

Additional information

We vinden het belangrijk dat je je op de UvA en bij Future Planet Studies veilig voelt. Krijg je onverhoopt te maken met ongewenst gedrag of voel je je onveilig, dan kun je terecht bij verschillende personen. Je melding wordt altijd vertrouwelijk behandeld. Kijk op onze website voor meer informatie over waar en bij wie je terecht kunt.

It is important that everyone feels safe at the UvA and Future Planet Studies. We are committed to provide social safety and we offer various forms of support for people experiencing inappropriate or unsafe situations. Consult the UvA website or Future Planet Studies Canvas page for more information and contact info.

Last year's student feedback

The remote sensing team is continuously updating the quality of the course content, and - in general - the evaluation is good. A returning issue is working with own laptops, and the requirements of the laptops -> we will post this in advance. A recurring issue is the waiting time -> we will stimulate using the Help function, and internet search for solving problems, and postings on the Discussion Board. We have dropped one module, to create more time for the project, as was mentioned in some comments. We updated many small bugs, due to software updates and other minor changes.

Contact information

Coordinator

• dr. A.C. Seijmonsbergen

Staff

Harry Seijmonsbergen -> a.c.seijmonsbergen@uva.nl

Thijs de Boer                    -> w.m.deboer@uva.nl

Walter van Dijk                -> w.vandijk@uva.nl

Jelle Bulens                      -> j.bulens@uva.nl

and assistents