3 EC
Semester 1, period 2
5132RESE3Y
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, and using the ArcGIS Pro software environment.
In nine self-tuition assignments, we offer GIS-based tools and techniques, such as 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 that 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, and 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 mounds in the Netherlands, and more.
After finishing 9 mandatory individual assignments, students continue with a project in teams of two. The results of the research project are documented in a technical remote sensing report with accompanying digital products.
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
9 Quizzes, available on Canvas, datasets, tutorials
ArcGIS Pro - to be installed on own laptops before the course starts
2 Lectures—remote sensing introduction, and information on the project
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.
|
Activity |
Hours |
Remarks |
|
Lectures |
2 |
The first lecture is necessary to understand the course structure, expectations, course requirements and some necessary basic remote sensing background; the second part will Introduce you to the Project |
|
Laptop Practical |
52 |
Mandatory: individual quizzes will guide you through the first 9 modules. Additionally, laptop sessions are spread during the last weeks of the course for a Project (two students) on remote sensing satellite classification |
|
Self-study |
32 |
Time to plan your own time to read, prepare, finish modules, write, and consume information outside laptop meetings during the course |
|
Total |
84 |
Note: the remote sensing course runs in parallel with other courses; carefully plan your time! |
Additional requirements for this course:
The course is on campus, the presence and absence rules are as follows:
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.
For this course, an attendance requirement applies to the laptop practicals as officially scheduled. During the laptop practicals, the following learning objectives are addressed in the Assessment Diagram; see elsewhere in this course manual. The guidance and exercises during laptop practicals ensure that the learning objectives can be achieved. These are tested in the project phase, during which a technical report and a digital workpackage are created.
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.
| Item and weight | Details |
|
Final grade | |
|
0.5 (5%) Quiz Module 1 | |
|
0.5 (5%) Quiz Module 2 | Must be ≥ 5 |
|
0.75 (8%) Quiz Module 3 | Must be ≥ 5 |
|
0.75 (8%) Quiz Module 4 | Must be ≥ 5 |
|
0.75 (8%) Quiz Module 5 | Must be ≥ 5 |
|
0.75 (8%) Quiz Module 7 | Must be ≥ 5 |
|
0.75 (8%) Quiz Module 6 | Must be ≥ 5 |
|
0.75 (8%) Quiz Module 8 | Must be ≥ 5 |
|
1 (10%) Quiz Project Module 9 | Must be ≥ 5 |
|
2 (20%) Upload your Project package | Must be ≥ 5.5 |
|
1.5 (15%) Upload your Technical Report | Must be ≥ 5.5 |
For individual quizzes a minimum score of 5.0 has been set. For the project deliverables, a minimum score of 5.5 has been set. The weighted final score, however, should be 5.5 or higher.
For each quiz there is a deadline, which is 2-3 days after the practical session (see individual modules). After the deadline, submissions will be closed. There is a resit planned for all individual quizzes during the last week of the course. Submissions 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. If this resit in week 50 is not met, there will be a resit in February 2025. Two weeks before the resit 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 2025 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 rubrics. Not meeting the deadline in December means a resit in February 2025. 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.
| Leerdoel: | Toetsonderdelen: |
|---|---|
| #1. The student can explain the basic concepts of remote sensing, such as: wavelengths, spatial/temporal/spectral resolution, absorption & reflection, band ratios, NDVI, and supervised classification. | Quiz 1,2,6,7,9 |
| #2. The student can select, download and pre-process satellite images for use in spatial analyses. | Quiz 1,2,5 |
| #3. The student can apply remote sensing tools and techniques using ArcGIS Pro software for the identification, mapping and quantification of information from satellite images. | Quiz 3,4,7,9 |
| #4. The student can analyze geodiversity by computing an index based on derivatives from digital elevation models and thematic datasets such as geology and soils. | Quiz 8 |
| #5. The student can design and execute a remote sensing project to analyze and interpret Land Use and Land Cover change. | Quiz 9 |
| #6. The student can write a technical remote sensing report and manage digital remote sensing (meta) data. | Quiz 1-9, Project |
Students enrolled last year: your grades of partial assignments are still valid this year. Students from earlier years: need to retake all mandatory assignments
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.
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.
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
| Week |
Activity |
Deadline |
| 44 |
Lecture October 28: Course structure and introduction to Remote Sensing Module 1 October 31 - Laptop: Getting started to Remote Sensing & GIS |
lecture 11.00-13.00 November 2, 23.59 |
| 45 | Module 2 November 3 - Laptop: Earthquake analysis |
A: November 4, 23.59 B: November 5, 23.59 |
| 45 | Module 3 - November 5/6: Laptop: Ecoduct location in a cultural landscape |
A/B: November 9, 23.59 |
| 46 | Module 4 - November 10 - Laptop: Coffee been suitability mapping Hawaii |
A: November 11, 23.59 B: November 12, 23.59 |
| 46 | Module 5 - November 12/13 - Laptop: Living atlas and digital data in Earth Observation |
A/B: November 16, 23.59 |
| 47 | Module 6 - November 17 - Laptop: Flooding in agricultural systems: Bangladesh |
A: November 18, 23.59 B: November 19, 23.59 |
| 47 |
Module 7 - November 19/20 - Laptop: Using indices in earth observation |
A/B: November 23, 23.59 |
| 48 | Module 8 - November 24 - Laptop: Quantification of geodiversity of Hawaii |
A: November 25, 23.59 B: November 26, 23.59 |
| 48 | Module 9 - November 26/27 - Laptop: Land Use and Land Cover Classification China |
A/B: December 5, 17.00 |
| 49 / 50 |
Project—December 1-12—Land Use and Land Cover classification Week 50 -> Resit of modules |
December 15, 09.00 |
Not applicable
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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 our 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 the new potential with UvA AI Chat and internet searches for solving potential problems and delays and will post solutions on the Discussion Board. We have dropped one module to create more time for the project, as was mentioned in some comments. This year we updated many small bugs due to software updates and other minor changes.
Harry Seijmonsbergen -> a.c.seijmonsbergen@uva.nl
Daniel Kooij -> d.e.kooij@uva.nl
Rosa Rougoor -> r.rougoor@uva.nl
Thijs de Boer -> w.m.deboer@uva.nl