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Lessons on Earth observation applications
Contributing new lessons or case studies

Hands-on lessons in the use of EO data

LearnEO! has developed ten lessons for the UNESCO Bilko software, which show how data from ESA satellites (EnviSat, SMOS, CryoSat, GOCE) can be used to monitor our environment. Also available are the three winning lessons from the LearnEO! lessons writing competition in 2013/14, and ten lessons developed by the Global Lakes Sentinel Services (GLASS), developed for the BEAM/SNAP software.

Follow the links in the box on the right for overviews of the lessons.

We encourage other Earth observation scientists to develop additional lessons or shorter case studies suitable for different audiences from high school to university level. For more information on how to contribute, see our information for LearnEO! authors.

Ten lessons from LearnEO!

LearnEO! has developed ten peer-reviewed lessons on the use of satellite data to monitor our environment. The lessons are intended primarily for use in university courses or professional self-study by users who are not primarily remote sensing experts.
Beginner lessons may also be suitable for high school students.
Intermediate lessons assume some general background knowledge about ocean or land remote sensing.
Advanced lessons require more detailed background knowledge in a the application area.
 

Lesson 1 screenshot
Lesson 1: The Amazon river plume

Measurement of sea surface salinity (SSS) from space began with the launch of the ESA Soil Moisture and Ocean Salinity (SMOS) satellite in November 2009. One of the most obvious features when looking at SMOS data is the input of freshwater from the Amazon River. The Amazon also delivers a vast quantity of nutrients into the Atlantic, which encourages the growth of phytoplankton. This lesson uses these two features of the impact of the Amazon to compare the spatial scales over which changes in salinity and ocean colour can be viewed using EO data.

Level: Intermediate. Suitable for students with some background in oceanography.
Lesson 2 screenshot
Lesson 2: Monitoring oil pollution at sea

SAR (synthetic aperture radar) is a well established tool for detecting oil on the sea surface. More recently optical sensors such as MERIS and MODIS are also used, particularly in the subtropics, where cloud is less of a problem than at higher latitudes or along the equator. This lesson uses ASAR and full resolution MERIS data to show how SAR and optical data may be used to to monitor illegal discharge of oil at sea, or to provide information for oil spill clean-up and environmental assessments after accidents.

Level: Intermediate. Requires some knowledge of ocean remote sensing.
Lesson 3 screenshot
Lesson 3: El Niño and the Southern Oscillation (ENSO)

El Niño is one of the most famous phenomena in the ocean-atmosphere system. In the ocean it affects sea surface height and ocean temperature. In the atmosphere it affects the winds and transport of moisture. It therefore influences seasonal weather patterns in many regions of the world, and understanding how it develops can help us estimate the likelihood of floods or droughts in these areas. This lessons looks at the progression of El Niño across the Pacific Ocean and its turn back to La Niña, using the power of the global view made possible by satellite observations.

Level: Beginner
Lesson 4 screenshot
Lesson 4. Monitoring Atlantic storms

Significant wave height is a by-product of measuring sea surface height from satellites. Even if the orbit repeat times of altimetry satellites means we cannot measure wave heights for all storms, many impressive examples are available. These show that storms in the Atlantic can create waves comparable with those whipped up by hurricanes. Using historical examples from the altimetry record, supported by meteorological observations and wave height data from other sources, this lessons explains how wave height is read from the altimetry wave form and teaches the interpretation of along-track (non-imagery) satellite data and its use in oceanography.

Level: Intermediate. Suitable for students with some background in oceanography.
Lesson 5 screenshot
Lesson 5. Observing Earth gravity: the geoid and its use to compute ocean dynamic topography

Gravimetric satellites, including GOCE, have improved our knowledge of the geoid. As a result we are now able to calculate the mean ocean currents from altimetric measurements of sea surface height - something that was not possible before the advent of gravimetric satellites. This lesson introduces the geoid as computed from GOCE measurements. It highlights some of the geoid features that match either deep inhomogeneities, or reliefs in the Earth's crust, and explains how these influence sea surface height.

Level: Advanced
Lesson 6 screenshot
Lesson 6. Monitoring Arctic sea ice

The Arctic is one of the areas where the impacts of global climate change are strongest. It is also an area which is quite difficult to measure in situ and thus one where satellite observations show their full strength. Several different sensors are used to monitor sea ice in the Arctic. Some allow us to see the global picture; others give a closer, more detailed view. This lesson introduces examples of both types. Monthly radiometer data is supplemented with a zoom in on one area with SAR data. The lesson also mentions freeboard measurements from CryoSat altimetry, which will become available as an ESA product towards the end of 2013.

Level: Intermediate
Lesson 7 screenshot
Lesson 7. Forest monitoring

Optical satellite data have been used successfully to map fire scars and post-fire recovery, but are limited by cloud cover. C-band space-borne radar can 'see' through cloud, and has the potential for assessing the extent and severity of wild fire impacts, provided the effects of soil moisture and low vegetation is taken into account. This lesson shows how a time series of SAR images can be used to monitor both deforestation and vegetation recovery after forest fires. The synergy with optical data is demonstrated through the use of Landsat imagery. The importance of satellites for global fire monitoring is also shown, using example data from A/ATSR.

Level: Intermediate. Requires some understanding of SAR remote sensing theory.
Lesson 8 screenshot
Lesson 8. Monitoring urban growth

Satellite observations are a valuable tool for updating urban maps and analysing settlement dynamics - both important for planning sustainable development. The ERS-Envisat SAR archive provides a unique source of data that can be used to track and understanding the dramatic changes in land cover around many large cities over the past 15 years. Using the city of Rome as an example, this lesson demonstrates the use of SAR data to monitor short term and long-term changes. It also explains how interferometric coherence can add valuable information, and shows how optical data may be used to validate results.

Lesson 9 screenshot
Lesson 9. Land cover mapping

Land cover data is required for conservation, land resource planning, and studies of biodiversity and environmental change. The only feasible way of obtaining such information for large areas over several years is with satellites. However, obtaining data of sufficient accuracy is not always straightforward. Results may vary depending on sensor characteristics and classification methods. This lesson shows how to obtain land cover information form multi and hyperspectral data at different spatial resolution, and teaches the basics of land-cover data validation. It also looks at the possibility of obtaining extra information by using sensors that look at a location from several viewing angles.

Lesson 10 screenshot
Lesson 10. Monitoring soil moisture

Soil moisture is a key variable for understanding global water and energy budgets. It controls the redistribution of rainfall into infiltration, surface runoff and evaporation at the earth surface, and also has a strong effect on surface energy exchange. Information on soil moisture is also important for flood and drought monitoring, weather forecasting, water management and agricultural planning. The SMOS mission was designed to provide such information. However, measuring soil moisture from satellites is not trivial because of the effects that surface roughness and vegetation cover have on the signal recorded by the satellite. This lesson explains the physical principles of soil moisture retrieval from SMOS, and demonstrates some of the processing steps necessary to produce soil moisture maps from SMOS measurements.

 
 

Comments and suggestions

We welcome feedback on the lessons. If you have used one or more of the lessons in your studies or as part of a course you deliver to your students, we would like to hear from you. What aspects of a lesson worked well? Were there problems? If so, what can we do to improve a particular lesson?

Please e-mail your comments and suggestions to lesson@learn-eo.org.
 

Winning lessons from the LearnEO! lesson writing competition

1st Prize. Monitoring phytoplankton seasonality: phenology indices and their importance for coral reef biology

Authors: Marie-Fanny Racault and Dionysios E. Raitsos
Being the base of the marine food-web, phytoplankton provides a source of food for the larvae of many coral reef species, including fish, crustaceans and mollusks. The bloom timing (phenology) and intensity is determinant for the larvae survival. The lesson introduces phenology metrics to monitor the seasonality of phytoplankton using remote sensing ocean colour data from the European Space Agency (ESA) Climate Change Initiative project (OC-CCI). It investigates the phytoplankton dynamics in major coral reefs of the Red Sea, which is one of the most saline and warm seas in the world.
The jury said: ".. a very well prepared lesson with excellent background information .. both informative and interesting. .. the two authors are clearly experts in the field and their enthusiasm for the subject comes over. .. A very nice lesson!"

Suitable for university students or continued professional development training (intermediate level).
screenshot
2nd Prize. Detection of harmful algal blooms in coastal waters: examples from the Benguela upwelling system.

Authors: Hayley Evers-King and Marie Smith
Phytoplankton blooms fuel vast coastal fishery and aquaculture resources. However these blooms can often be harmful, as a result of anoxia or presence of toxins. Thanks to its high temporal and spatial resolution, ocean colour data allows scientists and managers to understand this phenomena and manage risks to resources. This lesson covers how we can use both in situ and satellite derived ocean colour data to detect high biomass blooms and how we can address the challenges of using this data in the dynamic coastal environment.
The jury said: "This is a great lesson with some nice imagery and quite ambitious exercises. Probably more advanced than others in scope. As a result the lesson takes a fair amount of time, but the results are well worth the effort."

Suitable for university students or continued professional development training (intermediate to advanced level).
3rd Prize. Observing the Eyjafjallajökull volcanic plume

Author: Mirko Lamantea
Phytoplankton blooms fuel vast coastal fishery and aquaculture resources. However these blooms can often be harmful, as a result of anoxia or presence of toxins. Thanks to its high temporal and spatial resolution, ocean colour data allows scientists and managers to understand this phenomena and manage risks to resources. This lesson covers how we can use both in situ and satellite derived ocean colour data to detect high biomass blooms and how we can address the challenges of using this data in the dynamic coastal environment.
The jury said: "This lesson deals with an inherently interesting topic ..using both colour composite images and volcanic ash detection algorithms. The results are clear .. highly suitable for the target audience. The background information is very thorough and provides a good theoretical grounding for the lesson.""

Suitable for university students or continued professional development training (intermediate level).
NOC Bilko UNESCO