What is the biosphere? Can we see it from space?

2. What might we be interested in measuring in the biosphere?

(This section needs edited) Things we are interested in measuring from space include:

• The health of vegetation
• The timing of events in the life of vegetation (when does vegetation begin to get green in the Spring, when is it greenest?)
• The productivity of vegetation, which we might measure as its weight (biomass)
• The height of vegetation
• The type of vegetation

We can also sometimes measure animals from space, although for the reasons explained above this is normally very difficult! See the Oceans storymap for counting whales from space, or the Cryosphere storymap about locating penguin colonies in Antarctica.

As you've hopefully learned, simply looking at images taken by satellites can only take us so far. Sometimes it's hard to work out exactly what a satellite image is showing, especially when individual organisms are rarely visible.

We can manipulate satellite image data to make it easier to work out where organisms, especially plants and vegetation, are located.

Satellite images are made up of many tiny squares called pixels, just like your TV or computer screen. In a coloured satellite image like the ones above, the colour in each pixel is made up of red, green, and blue light. The amount of red, green, and blue light in each pixel is measured by the satellite and given a value between 0 and 255. Each value from every pixel across the image for one colour goes into a different channel: all the blue values between 0 and 255 are in the blue channel, for example. When the image is made, the three colours are mixed in the right proportions using these channel values to produce the final colour image.

Satellites also record light that we cannot see. The electromagnetic spectrum is the term used to describe the entire range of light that exists, including these invisible wavelengths. Most light that exists on Earth is emitted by the Sun. The spectrum is shown below.

3. What percentage of the electromagnetic spectrum are we able to see with our own eyes?

Some satellites like Sentinel 2A and 2B are able to detect infrared wavelengths.

Living plants absorb red light and use it for photosynthesis, but reflect green light. Plants also reflect infrared light more strongly than the bare ground. Healthier plants reflect infrared light more strongly than diseased, dead or stressed plants.

4. Based on these facts about plants and infrared light, what might infrared satellite imagery be able to tell us about plants and vegetation?

A reflectance spectrum contains information about the colour and the brightness of light in the electromagnetic spectrum reflected by an object. The reflectance spectra of vegetation and soil are shown below.

5. Optional question: How do these spectra relate to the diagram of light bands reflected by leaves above?

A false colour composite image can be used to highlight land surfaces, by making use of parts of an image (like the infrared) where a surface reflects a lot of electromagnetic radiation. In these images, the red, blue and green channels are assigned different wavelengths. When we're interested in vegetation, it's quite common for the red channel to be assigned to near-infrared, green to be red, and blue to be green. This is because of the high reflectance of near-infrared radiation by vegetation.

6. What colour would vegetation be in this false colour composite image?

Use the slider below to see how False Colour Composites can highlight vegetation. What differences do you notice between the two images? Do some things become clearer?

Click the button below to explore the worksheet 'Illuminating the biosphere'.

Follow the link to Sentinelhub Playground to create your own False Colour Composites.

While false colour composites are quick to create and allow an improved visual understanding of what we're looking at, they're not very useful for making measurements.

To get objective information from our satellite data, we can perform mathematical calculations on the reflectance values in each pixel to get a new summary number. We call this summary number a Band Index.

Band indices take advantage of the reflectance spectra of land surfaces, particularly where there are strong high and low values in the spectra. The normalised Difference Vegetation Index (or NDVI) is the band indice most commonly used for studying vegetation. It's been used in science since the 1970s!

NDVI uses infrared and red bands recorded by satellites to calculate a number between -1 and 1:

7. How do you think NDVI can be used to image the biosphere, given what we know about plants and infra-red light? Who might be interested in using NDVI images?

8. Which of the plants in the above image is healthy, which is 'stressed'? Do healthy plants have a higher or lower NDVI value?

9. Use the image above to sketch a graph that relates plant health on the x-axis to NDVI on the y-axis.

NDVI can be used to locate and quantify the amount of green vegetation. The index can also be used to work out if vegetation is stressed or diseased. This can help farmers better look after their crops. With an NDVI image, farmers could easily see where there is some sort of crop damage perhaps caused by drought, flooding or disease. Importantly, NDVI imagery could also be used to detect, isolate, and control the spread of plant disease.

In additon to satellites which act like cameras, taking pictures using reflected solar energy, some satellites create their own energy and use this to measure the biosphere. Two methods commonly used are Synthetic Aperture Radar (SAR) and Light Detection and Ranging (LiDAR).

LiDAR systems use a laser to scan the Earth, creating 3D points mapped to the surface. We can then use these points to get information about vegetation structure, such as the canopy height of a forest and the density of vegetation.

SAR are based on the same technologies boats, planes, and bats use to detect objects. SAR satellites ping the Earth with energy and measure the energy which is reflected and returned to the satellite. We can use SAR to find out information about biomass. SAR is particularly tricky to interpret, as it doesn't look like the kind of images we are used to seeing!

Forest fires are a natural part of some ecosystems. Some species, such as the Lodgepole Pine (Pinus contorta), have even evolved to take advantage of fire!

However, large and damaging forest fires have been in the news a lot in recent years. Fires are becoming bigger and hotter than they have been historically. Climate change and anthropogenic (human) influences on the structure of forests have changed the way in which forest fires work. For a long time, we have extinguished forest fires as quickly as possible. This has prevented natural forest fires from happening and has led to the build up of large amounts of fuel on the forest floor (dead wood) which can then make fires burn larger and hotter. Climate change is also increasing the frequency of drought, extreme high temperatures and storm conditions which promote large fires.

Explore the satellite images of Evia, Greece in the below BBC article.

You can explore a live map of thermal anomalies detected from space, alongside fire warnings and confirmed fires below.

Are there any large fires you can spot? Do you think they're likely at this time of year?

We can see forest fires from space. The Sentinel-2 image below shows many fires burning around the Lena river in Russia. You can see some faint orange lines where the fires are burning and can obviously see the smoke plumes being blown away from the fires on the wind. During fires like this, we can use satellites to monitor smoke and aerosols as they travel from the fire over vast distances through our atmosphere.

10. But how would we measure the impact on vegetation? Think about NDVI and false colour composites.

The Wallabi point fires in November 2019 were part of a very large Australian fire season, which made international news. We're going to take a look at some satellite imagery over the fires.

First of all, let's look at an image we're more familiar with. This is a True Colour composite from before and after the fires. Can you see where the fire has burned vegetation?

It seems like some vegetation in the large block of forest surrounding the river burned, as it appears more brown and black in the True Colour image. Let's now use a False Colour composite to try and see more clearly where there are changes in vegetation.

That's made the effects of the fire much more obvious. Because healthy vegetation reflects more near-infrared light, the areas with healthy vegetation are bright red. You can see that a lot of these areas turn darker or lose their red colour after the fire, suggesting that the vegetation has been lost or damaged. We will now try to make the areas where vegetation has been lost or damaged clearer by calculating the NDVI.

In the map above, red is representative of very low NDVI values and dark green is representative of high NDVI. You can clearly see a decrease in the NDVI over the forest area, although some areas within the forest appear to have survived the fire and remain dark green. We can make the change in NDVI easier to interpret by classifying the NDVI values into 4 categories: Dark green for high values, light green for medium values, yellow for low values, and red for extremely low values.

When we classify the NDVI values like this, we can work out the change in the area of each classification. In case, the area covered by each NDVI class before and after the fire is:

--- Table of values to be inserted here.

So, we could estimate that within the area covered by the image there has been loss of _____ area of vegetation with high NDVI values.

We can use Earth Observation of fires to:

• Detect fires as they begin using thermal anomalies
• Monitor the size and intensity of fires
• Monitor the movement of smoke and atmospheric pollutants away from the fire
• Measure the impact of fire on vegetation, including the area which has burned and how it recovers.

This is important for our understanding of how fires are changing (for the science) and for planning responses and recovery plans after a fire has happened.

• The Biosphere contains all life on Earth and can be broken down into a number of smaller systems.
• We can see the biosphere from space! This is easiest when large numbers of individuals create a change in the land surface and when our data is at a high spatial resolution.
• We may be interested in measuring the type of vegetation present, the amount of vegetation, characteristics like its health, height, leaf area...
• To help us measure vegetation, we can use the spectra of leaves to create False Colour Composites and Band Indices like the NDVI.
• We can do this over Forest Fires to better understand how they are changing in the 21st century and to plan responses to them.

For more information on the biosphere:

For more information on Earth Observation of the biosphere:

For more information on forest fires:

Interested in other SatSchool modules? You should check out:

•  SENSE CDT 
•  Space Hub Yorkshire 
• *links to other modules*

The number of organisms grouped together, the size of individuals, and the colour of organisms compared to their environment all affect how visible organisms and biological systems are from space.

1. 3 x 3 photo grid left to right, top to bottom: 1. Forests in the transition from mountains to lower elevations in Alaska, community; 2. Coral in the Great Barrier Reef, ecosystem; 3. Phytoplankton bloom off Shetland Isles, community; 4. Vegetation growing on the volcanic landscape of the Galapagos islands, community; 5. The Amazon Rainforest, ecosystem; 6.Coral reefs and the atolls of the Maldives, ecosystem; 7. Vegetation cover following the boundary of Egmont National Park, NZ, community; 8. Vegetation on land and bright green algae blooming in Lake George, Uganda, ecosystem; 9. Vegetation on the Yukon River delta, Alaska, community.

2. In the biosphere, we might be interested in measuring plant health in crops, plant diversity, species diversity, biomass, biodiversity, whether species are endangered or extinct, animal health in stressed environments, crop yield, spread or retreat of species overtime.

3. Humans can see around 0.0035% of the entire electromagnetic spectrum!

4. Infrared light measured by satellites can be used to tell us where the ground is bare i.e. there are no or few living plants. Infrared light may also be able to inform us about plant health: whether plants are diseased, dead or stressed.

5. Optional question: Healthy plants have higher reflectance values at longer wavelengths (reflect more light with longer wavelengths) as they reflect near infrared wavelengths (which are long) more strongly than other wavelengths. As plants become more stressed, they reflect near infrared wavelengths less strongly, so unhealthy vegetation reflectance spectra have lower reflectance values at near infrared wavelengths. Check your understanding of this with the interactive electromagnetic spectrum chart.

6. Vegetation would be red.

7. Higher NDVI values in an image might indicate vegetation is healthier. This is because healthy plants strongly reflect near infrared light compared to red light, so the top of the NDVI calculation will be a large value, making the NDVI value also high.

8. The green plant is healthy, the brown plant is stressed. The healthier the plant the higher the NDVI value as the difference between the amount of near infrared and red reflected light is greatest.

9. Your sketch of NDVI against plant health should look something like this:

10. NDVI could be used to map where vegetation is on a map. An NDVI map could be made of an area before a fire and another could be made for after the fire. Comparing the NDVI values in the same place for the two times will show you how fires have affected the area. False colour composite maps can be used in the same way. See the finals section for examples!