ES 771 Lecture
James S. Aber


Advanced Very High Resolution Radiometer

The Advanced Very High Resolution Radiometer or AVHRR is carried on a series of polar-orbiting satellites that are designed primarily for meteorological observations of clouds, sea-surface temperature, and snow/ice cover. AVHRR is a whiskbroom scanner that combines a wide ground swath with low spatial resolution. AVHRR detects energy in four (or five) bands of visible, short-, mid-, and thermal-IR wavelengths. AVHRR has also proven quite useful for land resources applications over broad regions. AVHRR has become particularly valuable for global monitoring and analysis of land vegetation. Impressive regional and global mosaics have been produced from AVHRR imagery.

AVHRR instrument.

Vegetation Index

The state of the world's vegetation has become a major subject of research during the past two decades. Vegetation is a key indicator for overall environmental conditions, and changes in vegetation are a useful means for recognizing changes in other environmental factors. Regional and global analysis of both terrestrial and marine vegetation is now possible based on satellite remote sensing. The status of vegetation and vegetation changes over multiyear periods can be documented.

Active, green vegetation absorbs red light (0.6-0.7 Ám) strongly; whereas, near-infrared radiation (0.7-1.0 Ám) is strongly reflected. No other common materials at the Earth's surface have this kind of spectral pattern. On this basis several vegetation indices have been developed for mapping and analyzing terrestrial vegetation biomass. These indices all involve combinations of red and near-infrared bands; the most widely used is called the normalized difference vegetation index (NDVI).

NDVI = (short IR - red) ÷ (short IR + red).

NDVI values extend from -1.0 to +1.0. Typical NDVI values for active terrestrial vegetation range from 0.1 to 0.6. Materials that reflect red more strongly than near-infrared (clouds, snow, water) result in negative values. Bare rocks and soils reflect red and near-infrared about equally, so their NDVIs are around zero. Several other simple vegetation indices have been devised using red and near-infrared bands (Tucker 1979).

Other vegetation indices
near-infrared ÷ red (near-infrared ÷ red)½
(near-infrared + red) ÷
(near-infrared - red)
near-infrared - red
near-infrared + red (inverse NDVI + 0.5)½


Many, more-complicated vegetation indices have also been proposed; however, most of them are functionally equivalent to simple ratios or the NDVI (Perry and Lautenschlager 1984). In any case, creating these vegetation indices involves one or more raster overlay operations (+, -, *, ÷), which result in output of fractional real numbers. Real-number data storage is a significant limitation when analyzing very large data sets. To overcome this problem, the real-number output may be converted into byte-binary scale (0-255).

AVHRR is the most important satellite system for regional or global mapping of terrestrial vegetation. Bands 1 (red) and 2 (near-infrared) are used to construct NDVI or vegetation indices. AVHRR data come in two resolutions: (1) 4 km Global Area Coverage (GAC) and (2) 1 km Local Area Coverage (LAC). GAC is used for continent-wide coverage; LAC is best for regional coverage.

EROS Data Center AVHRR

The EROS Data Center can receive directly 1 km AVHRR data covering most of North America, and EDC also accesses LAC data on tape relayed from other ground stations. Various kinds of data products are provided by EDC. Daily data sets are used to produce weekly and biweekly composite LAC data sets for the United States. In this procedure, the data corresponding to the highest NDVI value (or greenest) per pixel are selected for the periodic composite data set (Loveland and Ohlen 1993). In this way, the effects of clouds, dust and haze are largely (but not completely) eliminated. The resulting data set represents the highest NDVI values over the region during the period represented by the temporal composite.

Beginning in 1989, the EROS Data Center has developed a continuous time series of vegetation information based on AVHRR data for the United States (Eldenshink 2006). The time series consists of weekly and biweekly composites of maximum NDVI values showing vegetation conditions. The data are radiometrically and spatially corrected for consistent, multiyear results.

AVHRR greenness data.

AVHRR data sets are further used in combination with other kinds of data to create a land-cover characteristics database for the conterminous U.S. Multisource, multitemporal classification results in seasonally distinct land-cover regions. This kind of information forms the basis for environmental monitoring and modeling applications.


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