The Advanced Very High Resolution Radiometer
A Brief Reference Guide

by David A. Hastings and William J. Emery
Section III: Applications of AVHRR Data in Meteorology, Oceanography, Terrestrial Sciences; Effects of the Satellite system on Applications

Table of Contents:


Initially, the NOAA satellites were designed to observe the Earth's weather in the form of cloud patterns. Infrared sensing extended this view from daytime-only imagery to systems that sampled both day and night. Experience with the SR and the VHRR clearly demonstrated that these scanners could be used for more than monitoring the weather. Subsequent sensors were, therefore, specifically designed to measure other phenomena such as sea surface temperature, terrestrial vegetation, etc.

NOAA designed AVHRR for the following tasks: Channels 1 and 2 were to be used to discern clouds, land-water boundaries, extend of snow and ice, and the inception of snow/ice melting, and to monitor terrestrial vegetation employing the computation of the NDVI; Channels 3, 4, and 5 were to be used to measure the temperature of clouds and the sea surface, and for nighttime cloud mapping. Applications have extended far beyond these original objectives. Discussion of current applications is too extensive to be adequately covered in this brief review. Good compendia can be found in the proceedings of regional symposia on AVHRR imagery. Such compendia include Prata (1986), Hastings et al. (1987), Thomas et al. (1989), and Gagliardini (1989). In addition, the International Journal of Remote Sensing, Remote Sensing of Environment, and professional meetings of conferences in meteorology, (especially in Europe) and oceanography are excellent sources of research papers on current applications.


Simple mapping of cloud patterns is still an important application of AVHRR data, especially at high latitudes where data from geostationary satellites are severely distorted (due to Earth curvature). Meteorologists in northern Europe, for example, use AVHRR much more extensively than do those in the southern United States. Such meteorological applications include interpreting cloud top temperatures and heights for predicting and monitoring storms (Saunders, 1988); differentiating ice, water, shadow, and other aspects of clouds (Scorer, 1989; Karlsson, 1989); deriving information about winds at high latitudes from monitoring cloud motions (Turner and Warren, 1989); boundary layer airflow patterns (Winiger et al., 1989); water vapor content of the lower atmosphere (Schluessel, 1989); and the study of tropical cyclones (Hille et al., 1986).

It should be acknowledged that the AVHRR does not fly alone on the TIROS-N satellites but rather flies jointly with the TIROS-N Operational Vertical Sounder (TOVS). The TOVS is really not a single instrument but rather a combination of the High-resolution Infrared Radiation Sounder (HIRS, now the HIRS-2), the Microwave Sounding Unit (MSU), and the Stratospheric Sounding Unit (SSU). Together, these systems provide a suite of infrared and microwave channels that can be used to profile atmospheric temperature and, to a lesser degree, atmospheric moisture. The TOVS is presently the mission-critical sensor for meteorological applications. Climatology is also studied. Typical applications include the extend of snow cover, vegetation conditions, the advance/recession of shorelines, and relations between sea surface temperature and Sahelian drought (represented by the Normalized Difference Vegetation Index). Many of these applications remain in the research domain, and have not yet matured into products that can be routinely marketed.


It was recognized early-on in the NOAA satellite program that one of the environmental variables easiest to compute from the operational infrared (IR) imagers was sea surface temperature (SST). The VHRR and its immediate successor, the AVHRR-1, used a single thermal infrared channel in the 10- micrometre window, to measure (SST). It was realized that by adding an 11-micrometre channel, the difference in the values of the two thermal IR channels would help to correct for the atmospheric attenuation of the SST signal due to the presence of water vapor in the atmosphere. This then gave rise to the Multi-Channel SST (MCSST) which is computed from channels 4 and 5 of the AVHRR.

One of the problems of computing SST from the infrared AVHRR channels is that, even though the IR channels are calibrated onboard the satellite (with both internal hot and external cold loads), the SST must be compensated for intervening atmospheric effects and the drifts of the internal calibration sources. At present, the MCSST is calibrated against SST values measured in situ by satellite tracked, drifting buoys. These buoys are constrained to measure SST at anywhere from 0.5 to 1.0 m below the surface while the IR satellite sensor receives energy emitted from the mm thin skin layer of the ocean (Schluessel et al., 1987; Emery and Schluessel, 1989; Schluessel et al., 1990). An alternative is to calibrate the AVHRR derived SST with skin SST reference measurements made by a radiometer mounted on a ship.

Infrared AVHRR imagery has also proven very useful in mapping mesoscale ocean features in terms of their SST signatures (Evans et al., 1984; Cornillon et al., 1987). Major ocean currents, such as the Gulf Stream, are readily visible by their marked SST gradients. Techniques have been developed for mapping ocean current variability from their signatures in the AVHRR SST imagery (Cornillon et al., 1987, Emery et al., 1986).

Another oceanographic application of AVHRR data is in the study of sea ice. Properly filtered for clouds over ice, AVHRR imagery can be used to compute sea ice concentration and ice edge location (Emery et al., 1991b). Also, a sequence of AVHRR images, either visible or thermal infrared for polar winters, can be used to compute ice motion (Ninnis et al., 1986; Emery et al., 1991a).


The AVHRR has evolved into an invaluable resource for studying the land surface. AVHRR's frequent day/night synoptic coverage (morning and afternoon views give it twice the chance to have cloud-free coverage), its ability to see huge areas in stereo, its IR calibration, and the ability to be rigorously reprojected, are features unavailable in any other system.

While many geologists are concentrating on very small areas, with systems carrying anywhere from 7 to 256 spectral channels, AVHRR offers almost unused stereoscopic views of entire structural provinces and their surroundings - offering the opportunity to guide previously unattainable regional geological syntheses (Hastings, 1988), e.g., Monitoring of volcanic eruptions (and their effects on climate and safety of aircraft movements) (Matson, 1984; Prata, 1989).

In the area of monitoring terrestrial vegetation, the AVHRR-derived NDVI has proven to be a very robust and useful quantity. There is considerable discussion on how to interpret the NDVI, and how to relate the satellite-derived model to climate and terrestrial phenomena (Tucker et al., 1981; Tucker and Sellers, 1986). However, there is little doubt that the NDVI provides a useful space perspective monitor of vegetation, land-cover, and climate, if used carefully. The index has been produced and utilized globally (Kidwell, 1990) and regionally (Tucker et al, 1985,86; Goward et al., 1987; 1991; Sakamoto et al., 1987).

Multi-channel imagery from the AVHRR has also proven to be useful in snow cover mapping. The frequent coverage of the AVHRR is again the prime advantage in being able to distinguish clouds from snow cover with their similar albedo signature. Methods have been developed for routinely computing snow cover from AVHRR imagery (Dozier et al., 1981; Carroll et al., 1989). Combined with topographic relief information, snow cover from AVHRR can be converted to snow-water equivalent to give an estimate of the amount of water reserve represented by the winter snowpack. Again the primary limitation is cloud cover blocking the signature of the snow cover, but the frequent coverage of the AVHRR helps to lessen the impact of cloudiness.

Another use of AVHRR data lies in monitoring forest fires in terms of their IR signature. Because forest fires are intensely hot, the thermal IR signature can be spotted in the AVHRR as soon as the fire size becomes large enough to dominate the 1-km pixel of the AVHRR. In addition, the visible and IR channels will clearly reflect the smoke plume associated with the forest fire, which assists in mapping the fire location and estimating its progress in time. NDVI is also a good estimator of the damage done to vegetation after the fire, and can be used to map the burnout made before the fire.

Finally, the AVHRR can be used to assist in mapping forest fire fuel potential. Again, a vegetative index, such as the NDVI, is the primary indicator of where dead trees are abundant. Because the NDVI only responds to healthy, growing vegetation (it really indicates the health of the growth), those areas densely populated with dead or dying trees will show a decrease in NDVI. While it may take a few in situ samples to verify the patterns suggested by the NDVI mapping, the satellite perspective provides a unique way to survey the distribution of dead trees that make up the forest fire fuel potential.


Note that the statement, "sun synchronous", used to describe the TIROS-N orbit is an approximation. In reality, the orbit precesses in an effort to maintain the same local time. Thus, over a 14-day cycle the actual local time varies slightly. Besides the variation in nominal equatorial crossing times and the annual variation in sunrise and sunset, there is a tendency for actual equatorial crossings to occur somewhat later during the lifetime of any given satellite. This change is several minutes monthly, amounting to as much as two hours over the lifetime of a satellite.

Also, is should be observed that the polar orbit of the satellite, combined with the 3000-km swath of the AVHRR, leads to considerable overlap of the satellite imagery at polar latitudes. At equatorial latitudes the orbit is designed so that only a few kms overlap on adjacent orbits, but at 80 degrees N/S the sequential AVHRR swaths overlap by about one-third. This greatly increases the coverage at polar latitudes which is important for the removal of clouds in this persistently cloudy region of the world.

Several additional "departures from perfection" of the AVHRR system are discussed in the references. One should not think, however, that the AVHRR sensor is inferior or superior to other systems currently in orbit. Scientists use AVHRR for such a wide variety of applications that one naturally expects this system to be short of perfection for any single application.
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