Though we often take the plants and trees around us for granted,
every aspect of our lives is dependent on them. They feed
us, cloth us, absorb carbon dioxide, provide us with oxygen,
and give us building materials and medications. When drastic
changes occur to the vegetation around us, our health, economy
and environment can all be affected. Twenty-five years ago,
for instance, thousands of people starved when the vegetation
in the Sahel region of Africa dried up during an extended
drought. Over the past five decades deforestation in South
America has left thousands of acres fallow and has possibly
destroyed many valuable medications.
As part of an effort to record major fluctuations in vegetation
and understand how they affect the environment, Alfredo Huete
at the University of Arizona and Christopher Justice at the
University of Virginia plan to measure and map the density
of vegetation over the Earth. They will use the MODIS instrument
aboard the Terra satellite to gather images of the planet's
surface in the form of data. The team will then use an algorithm
called a vegetation index to classify and quantify the various
concentrations of vegetation around the globe. Every 16 days
and every 30 days the scientists plan to combine the daily
indices to create detailed maps of the Earth's vegetation
To determine the density of plants on a patch of land, researchers
must observe the distinct colors (wavelengths) of sunlight
reflected off the Earth. As can be seen through a prism, many
different wavelengths make up the spectrum of sunlight. When
sunlight strikes objects, certain parts of this spectrum are
absorbed and other parts are reflected or emitted. In plant
leaves, chlorophyll absorbs red light and other visible wavelengths
from the sun, for use in photosynthesis. The cell structure
of the leaves on the other hand reflects near infrared light.
The more foliage a plant has, the more these types of light
Remote sensing instruments such as MODIS have a number of
light detectors on board that measure specific wavelengths
of light coming off the Earth. With these detectors researchers
can take a satellite image of the infrared and red light emanating
from a plot of land. They can then compare the intensity of
these two types of light at each point (pixel) on the image
to arrive at the vegetation density. In general, if the difference
is at its highest value, then the vegetation at that pixel
is likely to be dense and may contain some type of forest.
If it is at its lowest value, then the vegetation is probably
sparse and may consist of tundra or desert. Values between
these two extremes indicate vegetation such as grassland and
Nearly all satellite vegetation indices employ this difference
formula to quantify the density of plant growth on the Earth.
The Arizona team plans to use two such indices in their surveys.
The first is known as the normalized difference vegetation
index (NDVI), and it has been around for more than twenty
years. In this formula the difference in intensity of red
and infrared light reflecting from an area of land is divided
by the sum of the two intensities. The result is an index
of vegetation that runs from zero to one. A zero means almost
no vegetation and a one indicates the highest amount of vegetation.
The second index, the enhanced vegetation index (EVI), takes
advantage of MODIS's state-of-the-art capabilities. While
the EVI returns values ranging from zero to one, it corrects
for some distortions in the reflected light caused by the
particles in the air and the ground cover below the vegetation.
The data product also does not become saturated as easily
as the NDVI when viewing rainforests and other areas of the
Earth with large amounts of chlorophyll.
However, the improved index does not eliminate all obstacles.
Clouds and aerosols can often block the satellite's view entirely,
glare from the sun can saturate certain pixels, and temporary
malfunctions in the satellite instrument itself can distort
an image. Consequently, many of the pixels in a day's worth
of images are undecipherable, and a map made from the daily
vegetation index would be patchy at best.
With the imaging data the MODIS instrument provides, Huete
and his team should be able to use these indices to get daily
measurements of vegetation density over most of the Earth's
surface. The maps will be helpful in monitoring and understanding
environmental and climate changes such as deforestation and
desertification. The maps will also play a major role in other
satellite measurements. They are crucial in classifying different
types of vegetation in the land cover change data products
(MOD 12), and they provide surface estimations for the leaf
area index (MOD 15). Additional data products will use the
indices to mask vegetation. The MODIS snow cover data product
(MOD 10, MOD 33), for instance, will incorporate the NDVI
in heavily forested areas to separate tree canopies from the
snow that lies beneath them.