Some affinity with computers and interest in geography (or earth and life sciences).
Similarly tagged 100-level and 200-level courses. Students that do not meet this prerequisite should contact the instructor regarding the required competencies before course allocation.
Remote sensing offers a wealth of environmental data to study environmental change and support environmental management. We are all aware that satellite imagery is used in weather forecasts, but we also rely on these datasets to help us making many other environmental decisions. The present course fosters awareness of the possibilities and pitfalls that these remotely collected measurements present. After validation with in situ data, the information can be used in modelling studies, or they can be combined with other geo-spatial data in Geographic Information Systems (GIS).
In the course we will explore the physical principles behind remote sensing, starting with the fundamental characteristics of electromagnetic radiation and its interaction with substances in the atmosphere and water. After going through a selection of environmental problems and policy issues encountered in these media, we move on to detection of direct human influence on soil and vegetation (land use). In this phase of the course we also intensify attention on spatial analysis and the role of other geo-spatial data. In the final leg of the course, all methods will be integrated in a small project in which the students take the role of an environmental advisor.
After completion of the course students will be able to:
Select suitable remote sensing data and analysis techniques for environmental resource management
Analyse/work with remote sensing and other spatial data
Assess the quality of the datasets or the results of spatial analyses
After completion of the course students will know:
The basics of remote sensing, and spatial analysis / spatial modelling
Which remote sensing data and spatial analysis methods are available
For which problems they can be used
What the strengths and weaknesses of the methods are in practice
Mode of Instruction
During the lectures the main physical basics and mathematical principles of remote sensing, and spatial analysis techniques will be revealed. We will also visit the Space Expo of the European Space Research and Technology Centre (ESTEC) in Noordwijk to experience the technology behind remote sensing. In the plenary sessions many examples of applications in environmental studies will be provided. These will be further elaborated in self-study, as case-based study assignments (for which literature and eLearning tools are provided). Computer exercises have been developed to stimulate analytical treatment of spatial data. Part of these exercises were developed for BEAM, another part uses GIS. To foster practical understanding of spatial analysis, the study ends with an integration of methods in a small project in which the students take the role of an environmental advisor.
Assessment: In-class participation in discussions and practicals
Deadline: Ongoing Course Weeks 1 – 7
Assessment: Weekly oral presentations, individual or small groups (usually 5 PowerPoint slides, or a 1000 words essay from the excursion)
Deadline: Weeks 1 – 6 (Tuesdays at 11:05-11:40)
Assessment: Final research essay, as a simulated project report (ca. 3000 words) Based on the work presented in week 7 (2 × 3 PowerPoint slides
Deadline: Weeks 7 and 8 (Tuesday 16 Oct. at 12:50)
Deadline: Week 8 (Friday 1 Jun 9:00 – 11:00)
Aavailable through blackboard and the Internet:
Boersema, J.J., Reijnders, L. (eds.), 2009. Principles of Environmental Sciences. Section 10.5.4 and 10.5.5 GIS and Remote Sensing. Springer, Heidelberg, pp. 163-166.
De Jeu, R.A.M., 2011. Digital Spatial Data: Introduction to Remote Sensing. VU, Amsterdam.
Delaney, J., Van Niel, K., 2007. Geographical Information Systems: An Introduction (Second Edition). Chapters 1 & 2, Oxford University Press, Oxford.
Eleveld, M.A., Wagtendonk, A.J., Pasterkamp, R. & De Reus, N. (2007). WATeRS: An open Web Map Service with near-real time MODIS Level-2 standard chlorophyll products of the North Sea. International Journal of Remote Sensing, 28(16), 3693–3699. doi:10.1080/01431160701253204
Longley, P.A., Goodchild, M.F., Maguire, D.J., Rhind, D.W., 2005. Geographic Information Systems and Science. Section 2.3.5, Environment. John Wiley, New York, pp. 55-60.
SEOS: Science Education through Earth Observation for High Schools. Internet-based eLearning tutorials http://www.seos-project.eu/home.html (change language for English version of the tutorials) Last accessed 8 Aug. 2012.
Smith, R.B., 2006. Introduction to Remote Sensing of Environment (RSE). www.microimages.com documentation/Tutorials/introrse.pdf (Accessed 13/12/2011).
VU-IVM, 2007. Introduction to ArcGIS 9.2/9.3
firstname.lastname@example.org (only for questions regarding the GIS practicals)
Week 1. Introduction
Session 1. Introduction to Environmental Change and Management: GIS and Remote Sensing and Practical introduction to the SEOS modules
Session 2. The use of Poseidon’s paintbox to study global change
Week 2. Basics remote sensing
Session 1. Basics remote sensing and image processing
Session 2. Excursion to the Space Expo (ESTEC Noordwijk) Move (from Thu. 6 Sept. 17:00-18:50) to Wednesday 5 Sept
Week 3. Atmosphere, radiative transfer and the biogeochemical cycle
Session 1. Optics of the ocean and marine stewardship
Session 2. Hands on practical on Coastal eutrophication with image processing software: Conducting 5 experiments with BEAM (and exporting results)
Week 4. Basics GIS
Session 1. Practical introduction to GIS and spatial analysis 1
Session 2. Practical introduction to GIS and spatial analysis 2
Week 5. Human impact: Land cover, agriculture and spatial planning
Session 1. Detecting soil properties and vegetation phenology
Session 2. Land use from above: the use of spatial data for sustainability research
Week 6. . Hydrologic cycle: Soil moisture and the Quality of inland waters
Session 1. The global water cycle from space observations and implications
Session 2. Water quality of lakes: Indicators of change
Week 7. Project Integral Case
Session1. On design of project and its implementation in GIS
Session 2. Working on the GIS project
Week 8. Finalising report and reading on behalf of the exam
Session1. Finalising report on the Integral Case Project
Session 2. Exam