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MODIS Data Product Non-Technical Description - MOD 13

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 density.

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 are affected.

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 farmland.

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.


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