3 EC
Semester 1, period 2
5132RESE3Y
Remote Sensing includes a powerful set of computational techniques and methods for storing, analyzing and visualization of information retrieved from satellite imagery, aerial photographs or other means of remote sensing, such as geophysical prospecting. 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, for example preprocessing techniques, suitability analyses, raster-based analysis, model building, and path-distance analysis. The remote sensing tools and techniques include, amongst others, 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, the students 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, instructive tutorials
ArcGISPro - to be installed on own laptops before the course starts
Lecture presentation, intro to the project
An introduction lecture into the course set-up and the theory of remote sensing helps the student to understand the value, relevance , but also the complexity of remote sensing tools and techniques. The lecture and online laptop practicals raises interest and awareness of fundamental theories behind necessary and the wide application field of remote sensing products.
|
Activity |
Hours |
remark |
|
Lecture |
4 |
Necessary to understand course structure, course requirements and remote sensing background; Introduction to the Project |
|
Online Laptop Practical |
52 |
Mandatory: quizzes will guide you through the first 10 modules. Additional 2,5 weeks are for a Project on remote sensing satellite classification |
|
Self study |
30 |
Time to read, prepare and consume information during online laptop practical |
|
Total |
84 |
|
Programme's requirements concerning attendance (OER-B):
Additional requirements for this course:
The course is fully online, therefore the presence and absence rules deviate from the regular situation.
| Item and weight | Details |
|
Final grade |
For each quiz there is a deadline set. After the deadline, submission will be closed. There is a resit possibility for individual quizzes in week 50. 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 1, 2021. Two weeks before that deadline submission will be reopened for those who did not meet the resit in week 50. The maximum grade for an individual module is then a 6.0.
Deliverables for the project assignment are 1. a short technical report and 2. a digital map package which will be evaluated. Not meeting the deadline of December 15 means a resit on February 1, 2021. Re-submission will be possible between January 18 and February 1. Maximum grades for the short technical report and the digital map package will be 7.0.
For deadlines, weights and requirements, see course structure, further in the course manual.
| 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 derivatives from digital elevation models and thematic datasets (geology, soils ) for the island of Hawaii | 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 short technical remote sensing report and manage digital remote sensing data | Quiz 0-9, Project |
Not applicable
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 the these tests). Feedback for each module is placed on Canvas as soon as all students of all groups have done 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 the 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 loose 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 0-9 are individual assignments. These will mostly be reviewed automatically, 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, see for 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 digital geodatabase. Feedback during the laptop practicals.
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 activity |
Requirements | Weight |
| 44 |
Lecture: course structure and introduction to Remote Sensing - Seijmonsbergen Laptop: Introduction to ArcGIS Pro |
November 1, 23.59 |
Must be ≥ 5.0, retake allowed last week of the course | 5% |
| 45 |
Laptop: Getting started to Remote Sensing & GIS |
November 6, 23.59 | Must be ≥ 5.0, retake allowed | 5% |
| 45 | Laptop: Earthquake analysis | November 8, 23.59 | Must be ≥ 5.0, retake allowed | 5% |
| 46 | Laptop: Ecoduct location in a cultural landscape | November, 13, 23.59 | Must be ≥ 5.0, retake allowed | 5% |
| 46 | Laptop: Locating coffee been using the suitability modeler | November 15, 23.59 | Must be ≥ 5.0, retake allowed | 5% |
| 47 |
Laptop: Living atlas and web services data in earth observation Lecture: Introduction to Project - Seijmonsbergen |
November 20, 23.59 | Must be ≥ 5.0, retake allowed | 10% |
| 47 | Laptop: Flooding in agricultural systems: Bangladesh | November 22, 23.59 | Must be ≥ 5.0, retake allowed | 10% |
| 48 | Laptop: Using indices in earth observation | November 27, 23.59 | Must be ≥ 5.0, retake allowed | 10% |
| 48 | Laptop: Quantification of geodiversity of Hawaii | November 29, 23.59 | Must be ≥ 5.0, retake allowed | 10% |
| 48 | Laptop: Project Land Use and Land Cover Classification China | December 4, 23.59 | 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 15, 23.59 | Project must be ≥ 5.5, retake allowed, see resit date |
Report: 15% datasets: 10% |
The schedule for this course is published on DataNose.
not applicable
Not applicable
In order to provide students some insight how we use the feedback of student evaluations to enhance the quality of education, a summary of the evaluation of last year in available on Canvas. The coordinators response of last year:
I am quite optimistic about this first evaluation. This new course required lots of logistics and content-wise decisions that mostly turned out well. However, the following issues need attention/improvement:
- using well-equipped hardware from student side: windows-based computers on which ArcGIS Pro runs smoothly; there were many issues with Apple-based computers, which is not recommended
- pre-installation of the software before the course starts (students were informed on time, but not all did)
- decrease unexpected 'crashes' / error notifications, often unknown errors appeared
- repair many small and some larger issues in the modules: we have kept a record that we will use to improve in the next course.
- I will include an extra lecture halfway to look back on the content sofar and look ahead / instruct more in-dept about the project.
- definitely the size of the project (in Mbs/GBs) should be reduced to handle files more efficient.