Earth-orbiting satellites – particularly of the Landsat series, developed and launched by the U.S. Geological Survey and the National Aeronautics and Space Administration (NASA) – provide a wealth of worldwide images for remote detection and study of earth surface phenomena. The Advanced Very High Resolution Radiometers (AVHRR) present on these satellites provide ecological researchers with the tools for remotely sensing the health of ground vegetation. This data is being used for monitoring desertification; identifying areas suitable for forest development, animal grazing, or grain agriculture; and detecting whether ground vegetation is suffering from heat or water stress. Real-time satellite pictures are also widely used for identifying and following the progress of forest fires in remote regions.
Although satellite sensors provide impressive amounts of high-resolution data, sophisticated approaches are required to retrieve useful information from these measurements. Moreover, recent readings along with many years of stored historic data are often required to elucidate conditions on the ground, as present vegetation health levels can only be understood against the background of past performance.
Plant health is characterized or governed by four major determinants:
Density of vegetation (or biomass) – which indicates the total biological productivity of the area under consideration;
Biological vigor (or photosynthetic activity) – which enables highlighting energy transformingelements of biomass as distinguished from their structural and circulatory elements;
Soil water – a decrease in which helps determine whether plants are likely to suffer from water stress; and
Temperature – an increase in which exposes dryland plants to heat stress.
By assessing these four factors, scientists can compare the relative health of vegetation growing over wide areas, as well as changes determined by changing weather conditions or human activities. They are also able to make educated predictions of what the future may hold for a region under investigation.
Sophisticated satellite radiometers that measure particular light-frequency bandsreflected off the earth’s surface transmit the data for determining these factors. In addition, researchers have designed various formulas that extract ecological details from these measurements.
For many years, the so-called Normalized Difference Vegetation Index (NDVI) has been used to measure and monitor plant growth (vigor), vegetation cover, and biomass production. Here two AVHRR frequency bands are accessed, the channel measuring red light (channel 1, 0.58-0.68 micron) and that recording in the near infrared (channel 2, 0.725-1.10 micron). Since leaf chlorophyll absorbs red light energy, which is converted in the plant to chemical energy, the lower the amount of reflected, or nonutilized, red light picked up by the satellite, the greater the amount of chlorophyll in the vegetation. (Because leaves reflect little red or blue light, the overwhelming quantities of reflected green give living vegetation its characteristic color.)
The AVHRR near-infrared channel picks up that portion of the reflected light spectrum created by the plant’s mesophyll leaf tissue. Such infrared signals are similar to those used in security thermal imagers to identify intruders. Therefore, vigorously growing healthy vegetation has low red-light reflectance (due to its chlorophyll) and high near-infrared reflectance (due to its total biomass).
Researchers have formulated a simple algorithm that combines these two readings into a single vegetation health measure, the Normalized Difference Vegetation Index (NDVI),
NDVI = (NIR – RED)/(NIR + RED).
Here NIR stands for the near infrared reflectance radiometer reading and RED, the reading in the red band. Thus as NIR goes up and RED goes down, NDVI will approach a value of 1. Usually, values between -1 and 1 reflect healthy vegetation. Because normal NDVI readings will depend on the type of vegetation, meteorological conditions, time of the year, and on the long-term climatic situation, researchers have developed more sophisticated formulas based on maximum and minimum NDVI values available from many years of stored satellite data. One of these is the vegetation condition index (VCI), which is built upon a 0 to 1 scale. Low values represent stressed vegetation conditions; middle values, fair conditions; and high values, optimal or above-normal conditions.
Temperature is another factor central to vegetation health. Low temperatures can freeze and seriously damage plants, but high temperatures are no less problematic. Excess air temperatures speed up plant biochemistry, causing rapid, inefficient growth, and reduced length of reproductive period even when water supplies are adequate. High temperatures can also damage cell membranes and the particularly heat-sensitive reproductive organs. This can lead to a substantial reduction in wilderness vegetation biomass and agricultural yields.
Land surface temperature is measured through a factor known as the brightness temperature (BT), which is calculated via the thermal infrared satellite band of 10.5-11.3 micron. In order to evaluate relative temperature stress of a region over study, researchers use a temperature condition index (TCI). Here low TCI values (close to 0) indicate harsh weather conditions (due to high temperatures) relative to the composite period, middle values reflect fair conditions, and high values (close to 1) reflect the most favorable conditions. It is important to note that VCI and TCI were constructed to present low values as representing harsh conditions and high values as signifying excellent conditions.
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