Application

To review, spectral resolution refers to the width or range of each spectral band being recorded. As an

example, panchromatic imagery (sensing a broad range of all visible wavelengths) will not be as sensitive

to vegetation stress as a narrow band in the red wavelengths, where chlorophyll strongly absorbs

electromagnetic energy.

Spatial resolution refers to the discernible detail in the image. Detailed mapping of wetlands requires far

finer spatial resolution than does the regional mapping of physiographic areas.

Temporal resolution refers to the time interval between images. There are applications requiring data

repeatedly and often, such as oil spill, forest fire, and sea ice motion monitoring. Some applications only

require seasonal imaging (crop identification, forest insect infestation, and wetland monitoring), and some

need imaging only once (geology structural mapping). Obviously, the most time-critical applications also

demand fast turnaround for image processing and delivery - getting useful imagery quickly into the user's

hands.

In a case where repeated imaging is required, the revisit frequency of a sensor is important (how long

before it can image the same spot on the Earth again) and the reliability of successful data acquisition.

Optical sensors have limitations in cloudy environments, where the targets may be obscured from view.

In some areas of the world, particularly the tropics, this is virtually a permanent condition. Polar areas

also suffer from inadequate solar illumination, for months at a time. Radar provides reliable data, because

the sensor provides its own illumination, and has long wavelengths to penetrate cloud, smoke, and fog,

ensuring that the target won't be obscured by weather conditions, or poorly illuminated.

Often it takes more than a single sensor to adequately address all of the requirements for a given

application. The combined use of multiple sources of information is called integration. Additional data

that can aid in the analysis or interpretation of the data is termed "ancillary" data.

The applications of remote sensing described in this chapter are representative, but not exhaustive. We do

not touch, for instance, on the wide area of research and practical application in weather and climate

analysis, but focus on applications tied to the surface of the Earth. The reader should also note that there

are a number of other applications that are practiced but are very specialized in nature, and not covered

here (e.g. terrain traffic ability analysis, archeological investigations, route and utility corridor planning.