3 EC
Semester 1, period 2
5132RESE3Y
Remote Sensing - sensing the 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 software environment of ArcGIS Pro.
In the self-tuition assignments we offer GIS-based tools and techniques, amongst others preprocessing techniques, suitability analyses, raster-based analysis, model building, and path-distance analysis. The remote sensing tools and techniques include, for example supervised classification, change analysis, band-ratio analysis, image enhancement and computing of vegetation and other indices which can be used in food production, 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 environmental and to diverse situations and/or topics such as flooding in Bangladesh, desertification in the Sahel zone, Land Use and Land Cover change in China, urban areas, and more.
After finishing 10 mandatory assignments, you will continue with a project. This research project is documented in a technical remote sensing report with accompanying digital products.
Various scientific papers which will be available via links on Canvas
https://www.nrcan.gc.ca/sites/www.nrcan.gc.ca/files/earthsciences/pdf/resource/tutor/fundam/pdf/fundamentals_e.pdf
10 Quizzes, available on Canvas, datasets, tutorials
ArcGIS Pro - to be installed on own laptops before the course starts
2 Lectures - presentations remote sensing and intro to 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 |
remark |
|
Lectures |
4 |
The first lecture is necessary to understand the course structure, expectations, course requirements and remote sensing background; the second part will Introduce you to the Project |
|
Online Laptop Practical |
52 |
Mandatory: individual quizzes will guide you through the first 10 modules. Additionally, 4 sessions spread over 2.5 weeks are projected for a Project (two students) on remote sensing satellite classification |
|
Self-study |
30 |
Time to read, prepare, write and consume information during online laptop practical and the project period |
|
Total |
84 |
Note: the remote sensing course is in parallel with the World Food and ecosystem course: carefully plan your time! |
Programme's requirements concerning attendance (OER-B):
Additional requirements for this course:
The course is on campus, the presence and absence rules are as follows:
| Item and weight | Details |
|
Final grade | |
|
5% ESRI certificate | Must be ≥ 5 |
|
5% Quiz Module 1 | Must be ≥ 5 |
|
5% Quiz Module 2 | Must be ≥ 5 |
|
5% Quiz Module 3 | Must be ≥ 5 |
|
5% Quiz Module 4 | Must be ≥ 5 |
|
5% Quiz Module 5 | Must be ≥ 5 |
|
7.5% Quiz Module 6 | Must be ≥ 5 |
|
7.5% Quiz Module 7 | Must be ≥ 5 |
|
7.5% Quiz Module 8 | Must be ≥ 5 |
|
7.5% Quiz Project Module 9 | Must be ≥ 5 |
|
25% Upload your Map package | Must be ≥ 5.5 |
|
15% Upload your Technical Report | Must be ≥ 5.5 |
For each quiz there is a deadline, which is the day before the next practical session at 17.00, or the Friday after a practical session at 17.00. After the deadline, submission will be closed. There is a resit possibility for 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 2023. 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 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 2023. Re-submission will be possible starting two weeks before the resit date. Maximum grades for the short technical report and the digital map package will be 7.0.
| Leerdoel: | Toetsonderdeel 1: |
|---|---|
| #1. The student can explain the basic concepts of remote sensing: wavelengths, spatial/temporal/spectral resolution, absorption & reflection, band ratios, NDVI, supervised classification | Quiz 0,1,6,7,9 |
| #2. The student can select, download and pre-process satellite images for use in spatial models | Quiz 1,2,5 |
| #3. The student can apply various remote sensing tools and techniques and spatial analysis techniques using the GIS software ArcGIS Pro for the identification, mapping and quantification of Land Use and Land Cover, especially in relation to agricultural areas | Quiz 1,3,4,7 |
| #4. The student can quantify geodiversity by computing an index based on metrics from digital elevation models and thematic datasets (geology, soils) | Quiz 8 |
| #5. The student can evaluate Land use and land cover variation, based on satellite processing in important food production areas | Quiz 9 |
| #6. The student can write a technical remote sensing report and manage digital remote sensing data | Quiz 0-9, 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 0-9 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: 10 quizzes (numbered Module 0- 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 map 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 |
Requirements | Weight |
| 44 |
Lecture November 3: course structure and introduction to Remote Sensing 0 - Laptop: Introduction to ArcGIS Pro |
November 4, 17.00 |
Must be ≥ 5.0, retake allowed in week 50 of the course | 5% |
| 45 |
1 - Laptop: Getting started to Remote Sensing & GIS |
November 9, 17.00 | Must be ≥ 5.0, retake allowed | 5% |
| 45 | 2 - Laptop: Earthquake analysis | November 11, 17.00 | Must be ≥ 5.0, retake allowed | 5% |
| 46 | 3 - Laptop: Ecoduct location in a cultural landscape | November 16, 17.00 | Must be ≥ 5.0, retake allowed | 5% |
| 46 | 4 - Laptop: Locating coffee been using the suitability modeler | November 18, 17.00 | Must be ≥ 5.0, retake allowed | 5% |
| 47 |
5 - Laptop: Living atlas and web services data in earth observation |
November 23, 17.00 | Must be ≥ 5.0, retake allowed | 7.5% |
| 47 |
Lecture November 25: Introduction to Project 6 - Laptop: Flooding in agricultural systems: Bangladesh |
November 25, 17.00 | Must be ≥ 5.0, retake allowed | 7.5% |
| 48 | 7 - Laptop: Using indices in earth observation | November 30, 17.00 | Must be ≥ 5.0, retake allowed | 7.5% |
| 48 | 8 - Laptop: Quantification of geodiversity of Hawaii | December 2, 23.59 | Must be ≥ 5.0, retake allowed | 7.5% |
| 49 | 9 - Laptop: Project Land Use and Land Cover Classification China | December 7, 17.00 | Must be ≥ 5.0, retake allowed | 10% |
| 49 and 50 - Laptop: Project |
Project on land use and land cover classification Week 50: resit of modules |
December 16, 17.00 | Project must be ≥ 5.5, retake allowed, see resit date |
Report: 20% datasets: 15% |
The schedule for this course is published on DataNose.
Not applicable
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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.
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; therefore, it is needed to install the software before the practical's start. We will also open the discussion board on Canvas this year to address general software and tool-related issues per module.