Course manual 2024/2025

Course content

Geographical Information Systems (GIS) and Remote Sensing (RS) include a powerful set of computational techniques, models, and tools for storing, retrieving, and analyzing spatial and temporal distributed geographical data. In this course, you will become acquainted with a wide array of remote sensing resources, which will be used to answer environmental questions at the interface of earth science and ecology. The variety of course assignments, or modules, cover topics for students who are new and who are experienced users of GIS and RS. This course is organized in small modular sections and has a flexible structure that allows you to work at your own pace within the temporal boundaries of 8 weeks. We encourage regular study progress; therefore, we added acceptable deadlines for the mandatory quizzes, which are posted on Canvas.

From the available assignments, you are able to make selections; in particular, you may focus on certain GIS or RS techniques and/or topics that are closely aligned to your personal study plans in your master track. The software used is mainly ArcGIS Pro, but some modules also use eCognition software or the Google Earth Engine-based cloud infrastructure for analysis.
Our assignments are self-tuition assignments (modular tutorials and accompanying quizzes) that cover a wide spectrum of topics, such as visualization tools, weighting and ranking methods, suitability analyses, raster-based analysis, least-cost pathways, Web services, model building, hydrological tools, Python scripting, and path-distance analysis. The remote sensing tools and techniques comprise supervised classification, change analyses, object-based image segmentation and classification, band-ratio analyses, image pre-processing, computing vegetation indices, and more. Images and datasets used are highly diverse and range from Digital Elevation Models (DEMs), LiDAR data, Landsat imagery, SPOT imagery, Sentinel imagery, radar bands, orthophotos, soil, geomorphological, land use, land cover, and other data in multiple data formats. The techniques and skills are applied to a wide variety of landscapes and environmental situations, such as flooding in Bangladesh, desertification in the Sahel zone, predictions of hummingbirds in the Andes, land use and land cover change in China, India, and the Netherlands, urban areas, food production in the Mekong delta, and more. After finishing a mandatory selection of assignments, there is space for an individual topic for all students. For those new to GIS and RS, run a project on land use and land cover classification in an area of their choice. Students with experience in GIS and RS write a one-page A4-sized research outline, which has to be agreed upon by both the student and the staff. The research project is documented in a technical GIS report with accompanying digital products (preferably a map package). Students are encouraged to use their own (master) research data, although there are pre-fabricated topics available as well.

Study materials

Practical training material

  • Modules, tutorials and quizzes - published on Canvas

Software

  • ArcGISPro, eCognition, Google Earth Engine

Other

  • Other relevant information will be published on Canvas.

Objectives

  • To acquire theoretical knowledge of geospatial analysis and classification techniques and Remote Sensing technology
  • To master practical skills with ArcGIS Pro, Google Earth Engine and eCognition software
  • To apply GIS and RS tools and techniques for spatial and temporal analysis of patterns in geo-ecosystems
  • The student can design and carry out a practical GIS / RS case study
  • The student can write a technical GIS/RS report / present a story line map
  • The student can manage and store digital data according to FAIR principles

Teaching methods

  • Self-study
  • Lecture
  • Computer lab session/practical training
  • Working independently on e.g. a project or thesis

Lectures:

In the first lecture, the structure of the course will be introduced, and a general overview of assignments, deadlines, and deliverables will be outlined. In addition, a short introduction or refresher of some RS principles. During this lecture, attention is paid to your personal GIS or RS background, because that will determine your assignment selection.

We have a second lecture by Dr. Yifang Shi, who will provide an overview of applications with techniques at the forefront of technological developments, February 10. It is highly recommended that you attend this lecture!

Assignments/Modules:

Students without previous GIS/RS experience finalize 16 self-tuition modules (in total, 6 EC). The modules should be finished at the end of the course. The content of the modules is briefly described elsewhere in this document and in detail on Canvas. Students without previous experience in GIS or RS who are interested in a small project should finish 12 modules and then complete a short project.

Students with previous experience finalize eight self-tuition modules (a total of ~3EC) before the project. The content of the modules and the project (~3EC) are described elsewhere in this document. Projects should be discussed with the coordinator in advance, somewhere halfway te course.

Self-study:

Scheduled study time according to the official course schedule is indicated on the DataNose; however, students are free to work during other days at home or other locations within the projected period (February–March). The GIS studio (Room C4.203) at Science Park Amsterdam is open Monday–Friday from 9.00–17.00 and mostly a bit earlier and later. In this room, there are sufficient computers available; outside scheduled periods, you may reserve a computer via the manager of the GIS-Studio, Thijs De Boer. One module requires the use of the eCognition software; that software is only available in the GIS-Studio.

Project:

Students with previous GIS/RS experience decide on a two-week project (~3EC), depending on their interest and in agreement with the coordinator. After confirmation on the topic, the student prepares a short project plan (maximum of 1 page) in which the project is described, the data is described (availability, metadata and format have been checked) and a work plan is presented in which the proposed techniques and processing steps are indicated and the foreseen deliverables are
outlined.

For students with limited GIS/RS skills, a short project can be done, details on the project are available on Canvas, and selection of the project should be in communication with the course coordinator.

Learning activities

Activity

Number of hours

 remark

Lectures

4

presence recommended

Module assignments

83 (students with previous experience) or 124/164 students without previous experience.

self-tuition 

Project

81 (students with previous experience) or 40
(students without previous experience)

self-study

Total

168

 

Attendance

Requirements of the programme concerning attendance (OER-B):

  1. Attendance during practical components exercises is mandatory.

Additional requirements for this course:

The first lecture is at the Science Park; see the DataNose for the current schedule. Students can work individually in the GIS-Studio at Science Park during the scheduled periods, which secures regular working hours. However, given the larger numbers of participants and to introduce flexibility, students are free to adapt a personal schedule, which allows them to plan work alternatively within the allocated time for this course. Windows-based computers are available in the GIS Studio and run the latest ArcGIS Pro installed by the ICT department of the UvA. Other operating systems are, in our experience, difficult or even impossible to use properly with ArcGIS Pro. Thijs de Boer, the manager of the GIS studio, will inform you before the start of the course how to install the software and provide you with an ArcGIS Pro licence, in case you don't already have one. Within the 8-week period, you need to finish the course, perhaps even earlier than the deadline. The course is now almost fully self-taught, which means minimum contact with the coordinator or teachers because the modules are (mostly) self-explanatory. If you need to use the eCognition software (only available in GIS Studio), then an on-campus computer is necessary.

Assessment

Item and weight Details

Final grade

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

5%

Quiz Module 6

Must be ≥ 5

5%

Quiz Module 7

Must be ≥ 5

5%

Quiz Module 8

Must be ≥ 5

7.5%

Quiz Module 9

Must be ≥ 5

7.5%

Quiz Module 10

Must be ≥ 5

7.5%

Module 11

Must be ≥ 5

7.5%

Module 12

Must be ≥ 5

7.5%

Quiz Module 13

Must be ≥ 5

7.5%

Module 14

Must be ≥ 5

7.5%

Module 15

Must be ≥ 5

7.5%

Module 16

Must be ≥ 5

7.5%

Module 17

Must be ≥ 5

7.5%

Module 18

Must be ≥ 5

7.5%

Module 19

Must be ≥ 5

7.5%

Module 20

Must be ≥ 5

40%

Project+Report with pre-knowledge

Must be ≥ 6

15%

Technical Report -> No pre-knowledge

Must be ≥ 6

15%

Project package -> No pre-knowledge

Must be ≥ 6

Students without pre-knowledge of GIS or RS start with mandatory modules 1–10. Grade division: quizzes 1–8 count for 5%; quizzes 9 and 10 for 7.5%. This is a total of 55%. The remaining 45% can be chosen as follows: a) Six quizzes can be selected from modules 11–20 and count for 7.5% each (note: module 15 is mandatory for all students), or b) Students can opt for an additional 2 modules (15%) and a small project (30% of the final grade: division: 15% datasets and 15% technical report). Detailed instructions and examples of project data will be available on Canvas.
Students with pre-knowledge: Modules 10-12 and 14-15 are mandatory, then select 3 additional modules (from 16-20, module 13 is only selectable if you are not familiar with the hydrology tools) for a total of 8 quizzes (60%) and the project for 40% of the final grade (division: 20% datasets and 20% technical report).

All quizzes have one attempt and must be graded with a 5.0 or higher. After the deadlines for the individual quizzes, the maximum score for that quiz is maximized to 7.0. The project must be graded 6.0 or higher. The final grade of the course must be 5.5 or higher to pass. If students do not finalize the course within the allocated time, there is a resit possibility (June–July). Maximum scores for missing quizzes are then maximized to 6.0. All individual scores remain valid for a period of one year.

Inspection of assessed work

The manner of inspection will be communicated via the digitial learning environment.

The course is self-taught; students are encouraged to work on their own. For help and feedback, we this year organized contact moments as follows:

Short 1-hour visits to the GIS studio by Harry or Thijs during regular schedule hours; see DataNose for regular hours.

Discussion board: on Canvas per assignment, we will regularly answer issues raised by students. We encourage you to use this platform to exchange solutions to software, hardware, and other issues raised by you. Of course, no answers should be posted; this will be seen as plagiarism. We trust you as responsible master students willing to learn a new skill.

For help with Google Engine modules, you may contact Dr. Yifang Shi.

From experience, we know that consulting the HELP from the help functions in ArcGIS Pro or just 'google' about any problem you are confronted with will enormously help you find your way through the software and seek solutions. You are not the only student having issues with bugs (we do as well), so there is a large quantity of useful posts on YouTube and other resources that may help you overcome challenges you are confronted with. It is allowed to use AI support to find Help for the software, but not for writing tasks. We ask for a statement in the report how AI has been used in this course.

Assignments

1 - An introduction to Remote Sensing and GIS

  • Graded individual quiz

2 - Earthquake analysis in the U.S. and the Netherlands

  • Graded individual quiz

3 - Location of an ecoduct in a cultural landscape

  • Graded individual quiz

4 - Finding coffee bean locations using the suitability modeler

  • Graded individual quiz

5 - Working with the living atlas - online data

  • Graded individual quiz

6 - Flood Hazard analysis in Bangladesh

  • Graded individual quiz

7 - Using indices in earth observation

  • Graded individual quiz

8 - Quantifying geodiversity ofHawaii

  • Graded individual quiz

9 - LULC classification in China using Landsat

  • Graded individual quiz

10 - Interpolating geophysical data on sand thickness

  • Graded individual quiz

11 - Normalized differential Vegetation Index

  • Graded individual quiz

12 - Land use and land cover classification India

  • Graded individual quiz

13 - ArcHydro Tools - hydrological analysis in Spain

  • Graded individual quiz

14 - Working with LiDAR data - Flevopark Amsterdam

  • Graded individual quiz

15 - Predicting hummingbirds

  • Graded individual quiz

16 - Python - critical habitat mapping

  • Graded individual quiz

17 - Radar remote sensing

  • Graded individual quiz

18 - Image segmentation and classification

  • Graded individual quiz

19 - Intro Google earth Engine

  • Graded individual quiz

20 - Google Earth Engine Advanced

  • Graded individual quiz

Project

  • Full descriptions and explanations are elsewhere in this course manual and/or will be published on Canvas

Selection of assignments

Development of assignments is currently in progress; names may slightly differ, content-wise the assignments are still up-to-date. Due to the transition to new quiz design on Canvas, we have traditional quizzes (1-10), who have not been upgraded to the new quiz format. The difference is that the traditional quizzes come with a .pdf document of instructions and questions, the new format only has quizzes with built-in instructions. We appreciate it if students let us know how we can improve these new formats, since there is no previous experience in this course with the updated teaching design.

The modules have been designed by IBED staff members and (former) master students. The assignments should be finished, preferably in the order listed on Canvas; each assignment will take you about a full day to finish, with some a bit longer or shorter. Within this course, the student will be able to proceed and finish along three possible routes:
1. Assignments for students with no or limited GIS/RS knowledge. Finish assignments 1–10 (including 10), then take 6 additional graded assignments from 11 to 20 (assignment 15 is mandatory), for a total of 16 modules. Another option is to run an individual project after 12 modules (modules 1–10, 15, and one of your choice).
2. Assignments for students with pre-knowledge of GIS and RS. Start with assignments 10–12 (including 12) and 14–15 (including 15) first, then select 3 other assignments from modules 16–20 (13 only if unfamiliar with hydro tools), for a total of 8 modules. After finishing, continue with a project and contact the coordinator for that.
3. Assignments for students who are unsure (with some pre-knowledge but no or limited ArcGIS Pro experience): contact the coordinator within the first week of the course to discuss which modules can be included from the first route.

Note: Start and finish the modules in the proposed sequence!

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

Students Activity Start End Hand in
Without pre-knowledge 16 modules

February 3

March 28 Quizzes in Canvas: see deadlines
Without pre-knowledge 10 modules +
project

February 3

March 13,
modules
March 28
project
Quizzes in Canvas
Technical report
and datasets for
project
With pre-knowledge 8 modules

February 3

March 5 Quizzes in Canvas: see deadlines

With pre-knowledge

Project

March 5 March 28

Assignment in Canvas:

- datasets 

technical report 

 

Resit

June/July End of June, first week July; to be announced

- modules/project

Honours information

Not applicable

Additional information

Getting started  and working in the GIS-studio of IBED

GIS accounts

To use the computers, you need an account and a password. Staff, postgraduates, and PhD students of IBED can use their own (UvA-) student or staff account (UvANetID). Students enrolled in a course can use their student login name or number.

If you do not have a login name or number, please send an e-mail to w.m.deboer@uva.nl ,you will then receive a guest account from the manager of the GIS studio, Thijs de Boer.

Network drives

After you have logged in and have opened My Computer on your desktop, you might see:

  • Hard Disk Drives segment with System (C:\) do not use drive C for storage of data; it is meant for programs!
  • and one other hard drive, named the (D:\) drive.
  • Devices with Removable Storage segment with your USB-ports, etc.
  • Network Drives segment normally with two network drives

Local drives (C:\) and (D:\) are not backed up. Always store your data and files (after work is done) in a cloud environment!

On Canvas, you can find the exercises, examples, tutorials, and manuals that you will need. Of course, you have read/write access to a personal folder (with your name) on the D-drive. You must first copy the module files (and sometimes unzip them) from Canvas that you need to a self-named folder (usually with your name in it) on the D drive.

A normal working scheme is as follows:

Locate the files you need from Canvas and copy them to a new self-named folder (usually with your name in it) on the local D-drive (NOT on the C-drive !).

  1. While working always open and save your files from/to this local folder.
  2. Before you log off copy your files to your personal cloud in order to be sure that a back-up is made. Any data left on the D:\drive can be deleted at any time!

Contact information

Coordinator

  • dr. A.C. Seijmonsbergen

Staff