Measuring Vegetation
by John Weier and David Herring
August 30, 2000

Though we often take the plants and trees around us for granted, almost every aspect of our lives depends upon them. They feed us, clothe 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 are all 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 destroyed many species including possible valuable medications.

Global Normalized Difference Vegetation Index
Satellite maps of vegetation show the density of plant growth over the entire globe. The most common measurement is called the Normalized Difference Vegetation Index (NDVI). Very low values of NDVI (0.1 and below) correspond to barren areas of rock, sand, or snow. Moderate values represent shrub and grassland (0.2 to 0.3), while high values indicate temperate and tropical rainforests (0.6 to 0.8).

In an effort to monitor major fluctuations in vegetation and understand how they affect the environment, 20 years ago Earth scientists began using satellite remote sensors to measure and map the density of green vegetation over the Earth. Using NOAA’s Advanced Very High Resolution Radiometer (AVHRR), scientists have been collecting images of our planet’s surface. By carefully measuring the wavelengths and intensity of visible and near-infrared light reflected by the land surface back up into space, scientists use an algorithm called a "Vegetation Index" to quantify the concentrations of green leaf vegetation around the globe. Then by combining the daily Vegetation Indices into 8-, 16-, or 30-day composites, scientists create detailed maps of the Earth’s green vegetation density that identify where plants are thriving and where they are under stress (i.e., due to lack of water).

next: Normalized Difference Vegetation Index (NDVI)

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Measuring Vegetation (NDVI & EVI)
Introduction
Normalized Difference Vegetation Index (NDVI)
NDVI as an Indicator of Drought
Enhanced Vegetation Index (EVI)

 Measuring Vegetation

Normalized Difference Vegetation Index (NDVI)

To determine the density of green on a patch of land, researchers must observe the distinct colors (wavelengths) of visible and near-infrared sunlight reflected by the plants. As can be seen through a prism, many different wavelengths make up the spectrum of sunlight. When sunlight strikes objects, certain wavelengths of this spectrum are absorbed and other wavelengths are reflected. The pigment in plant leaves, chlorophyll, strongly absorbs visible light (from 0.4 to 0.7 µm) for use in photosynthesis. The cell structure of the leaves, on the other hand, strongly reflects near-infrared light (from 0.7 to 1.1 µm). The more leaves a plant has, the more these wavelengths of light are affected, respectively.

Visible and Near-Infrared
Vegetation appears very different at visible and near-infrared wavelengths. In visible light (top), vegetated areas are very dark, almost black, while desert regions (like the Sahara) are light. At near-infrared wavelengths, the vegetation is brighter and deserts are about the same. By comparing visible and infrared light, scientists measure the relative amount of vegetation. (The variation in shade is more apparent in the detail of the U.S. West Coast).

The NOAA AHVRR instrument has five detectors, two of which are sensitive to the wavelengths of light ranging from 0.55–0.70 and 0.73–1.0 micrometers. With AHVRR’s detectors, researchers can measure the intensity of light coming off the Earth in visible and near-infrared wavelengths and quantify the photosynthetic capacity of the vegetation in a given pixel (an AVHRR pixel is 1 square km) of land surface. In general, if there is much more reflected radiation in near-infrared wavelengths than in visible wavelengths, then the vegetation in that pixel is likely to be dense and may contain some type of forest. If there is very little difference in the intensity of visible and near-infrared wavelengths reflected, then the vegetation is probably sparse and may consist of grassland, tundra, or desert.

NDVI example

NDVI is calculated from the visible and near-infrared light reflected by vegetation. Healthy vegetation (left) absorbs most of the visible light that hits it, and reflects a large portion of the near-infrared light. Unhealthy or sparse vegetation (right) reflects more visible light and less near-infrared light. The numbers on the figure above are representative of actual values, but real vegetation is much more varied. (Illustration by Robert Simmon).

Nearly all satellite Vegetation Indices employ this difference formula to quantify the density of plant growth on the Earth — near-infrared radiation minus visible radiation divided by near-infrared radiation plus visible radiation. The result of this formula is called the Normalized Difference Vegetation Index (NDVI). Written mathematically, the formula is:

NDVI = (NIR — VIS)/(NIR + VIS)

Calculations of NDVI for a given pixel always result in a number that ranges from minus one (-1) to plus one (+1); however, no green leaves gives a value close to zero. A zero means no vegetation and close to +1 (0.8 - 0.9) indicates the highest possible density of green leaves.

next: NDVI as an Indicator of Drought
back: Introduction

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Measuring Vegetation (NDVI & EVI)
Introduction
Normalized Difference Vegetation Index (NDVI)
NDVI as an Indicator of Drought
Enhanced Vegetation Index (EVI)

Related Links:
Drought: the Creeping Disaster

 Measuring Vegetation
Visible and Near-infrared, U.S. West Coast

back: Normalized Difference Vegetation Index (NDVI)

  Vegetation appears very different at visible and near-infrared wavelengths. In visible light (top), vegetated areas (like the Pacific Northwest) are very dark, almost black, while desert regions are light (the Great Salt Lake desert). At near-infrared wavelengths the vegetation is brighter, and deserts are about the same. By comparing visible and infrared light, scientists measure the relative amount of vegetation.

 Measuring Vegetation

NDVI as an Indicator of Drought

Satellite remote sensors can quantify what fraction of the photosynthetically active radiation is absorbed by vegetation. In the late 1970s, scientists found that net photosynthesis is directly related to the amount of photosynthetically active radiation that plants absorb. In short, the more a plant is absorbing visible sunlight (during the growing season), the more it is photosynthesizing and the more it is being productive. Conversely, the less sunlight the plant absorbs, the less it is photosynthesizing, and the less it is being productive. Either scenario results in an NDVI value that, over time, can be averaged to establish the "normal" growing conditions for the vegetation in a given region for a given time of the year. In short, a region’s absorption and reflection of photosynthetically active radiation over a given period of time can be used to characterize the health of the vegetation there, relative to the norm.

NDVI Anomaly

The difference between the average NDVI for a particular month of a given year (such as August 1993, above) and the average NDVI for the same month over the last 20 years is called NDVI anomaly. (Compare the August 1993 NDVI anomaly to August 1993 NDVI and Average August NDVI in North America.) In most climates, vegetation growth is limited by water so the relative density of vegetation is a good indicator of agricultural drought.

The above image shows the NDVI anomaly in the U.S. for August 1993. In that year, heavy rain in the Northern Great Plains (North and South Dakota, Alberta, and Saskatchewan) led to flooding in the Missouri River. The resulting exceptionally lush vegetation appears as a positive anomaly (green). Concurrently, in the Eastern U.S., rainfall was very low, and the region exhibited a strong negative anomaly (dark red).

Today, researchers at NASA and NOAA have two decades of NDVI data over the entire globe. Comparing this month’s or this year’s NDVI data with the 20-year average reveals whether the productivity in a given region is typical, or whether the plant growth is significantly more or less productive. So for the purposes of this Web site, a given region in which there is a period of reduced plant growth (due to a lack of precipitation) is labeled as "in drought." Other possible causes for lower than normal NDVI are exceptionally cold temperatures (which can delay or cut short the growing season) and clouds.

next: Enhanced Vegetation Index (EVI)
back: Normalized Difference Vegetation Index (NDVI)

  pullquote

Measuring Vegetation (NDVI & EVI)
Introduction
Normalized Difference Vegetation Index (NDVI)
NDVI as an Indicator of Drought
Enhanced Vegetation Index (EVI)

 Measuring Vegetation

Enhanced Vegetation Index (EVI)

In December 1999, NASA launched the Terra spacecraft, the flagship in the agency’s Earth Observing System (EOS) program. Aboard Terra flies a sensor called the Moderate-resolution Imaging Spectroradiometer, or MODIS, that greatly improves scientists’ ability to measure plant growth on a global scale. Briefly, MODIS provides much higher spatial resolution (up to 250-meter resolution), while also matching AVHRR’s almost-daily global cover and exceeding its spectral resolution. In other words, MODIS will provide images over a given pixel of land just as often as AVHRR, but in much finer detail and with measurements in a greater number of wavelengths using detectors that were specifically designed for measurements of land surface dynamics.

Consequently, the MODIS Science Team is preparing a new data product–called the Enhanced Vegetation Index (EVI)–that will improve upon the quality of the NDVI product. The EVI will take full advantage of MODIS’ new, state-of-the-art measurement capabilities. While the EVI is calculated similarly to NDVI, it corrects for some distortions in the reflected light caused by the particles in the air as well as the ground cover below the vegetation. The EVI 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.

Frequency of Coverage
Neither the NDVI nor the EVI product will eliminate all obstacles. Clouds and aerosols can often block the satellites’ view of the surface entirely, glare from the sun can saturate certain pixels, and temporary malfunctions in the satellite instruments themselves can distort an image. Consequently, many of the pixels in a day’s worth of images are indecipherable, and maps made from the daily Vegetation Indices are patchy at best.

Borneo 10 day vs. 30 day

Longer term averages of vegetation data help remove errors caused by clouds, but removes detail, especially at high spatial resolutions. The above pair of images shows the island of Borneo during September 1999. On the left is a 10-day average from September 21–30. Heavy cloud cover caused some areas to appear as if they had little or no vegetation (light brown). The 30-day average for the whole month of September, however, shows that the entire island is heavily forested.

With the imaging data the MODIS and AVHRR instruments provide, scientists should be able to use these indices to get daily measurements of vegetation density over most of the Earth’s surface. The maps are helpful in monitoring and understanding environmental and climate changes such as deforestation and desertification as well as drought. The maps also play a major role in other types of satellite measurements. For example, they are crucial in helping scientists classify different types of vegetation over the world’s landscapes as well as detecting changes in land surface cover over time.

back: NDVI as an Indicator of Drought

  pullquote

Measuring Vegetation (NDVI & EVI)
Introduction
Normalized Difference Vegetation Index (NDVI)
NDVI as an Indicator of Drought
Enhanced Vegetation Index (EVI)

Enhanced Vegetation Index
The Enhanced Vegetation Index (EVI) improves on the venerable NDVI. Derived from state-of-the-art satellite data provided by the MODIS instrument, EVI improves on NDVI's spatial resolution, is more sensitive to differences in heavily vegetated areas (as seen here in the Yucatan Peninsula), and better corrects for atmospheric haze as well as the land surface beneath the vegetation. Early data from MODIS shows the differences between EVI and NDVI.