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Remote Sensing as Information Technology

Why so long? “Remote sensing data is like raw wheat,” said Dunn C. Wallet, President and Chief Executive Officer of Terra Nova International in Los Altos, California. In his view, both commodities must undergo extensive processing to be useful, whether as imagery or bread. Yet in the remote sensing world, “we expect the customer to pull up his or her truck to the farmer’s gain elevator, haul away the raw product to ‘mill’ and subsequently process the raw material into some form suitable for consumption.”

To sustain the metaphor, wheat must not only be harvested, but also be winnowed, ground, and baked. Most earth resources satellites return digital data from passive sensors. Passive sensors exploit the fact that every object on earth reflects solar electromagnetic radiation or else emits its own radiation. (ERS-1 returns digital data from active radar sensors that detect microwave radiation beamed to earth from the satellite itself. As for the short lived Russian remote sensing satellites, they return photographic film, not digital data, to earth).

Some satellites have scanning mirror instruments, and others (such as SPOT and IRS) have push broom sensors. As the satellite travels north and south in its near polar orbit, the scanning mirrors swing east and west to define a scan line, building up the basics of a two dimensional image. The push-broom instruments, in contrast, image a complete line at a time.

Remote sensing satellites in low earth orbit circle the planet about every 100 minutes, so the rotation of the earth below presents new terrain with each orbit. After 14 to 44 days (depending on the satellite), the starting point returns and the cycle is repeated.

Thus, in each cycle, the satellite traces out several hundred paths running from pole to pole is divided into several hundred rows. In remote sensing parlance, a scene is one row combination an image is one scene made on a particular date.

The cross track dimension is determined by the scan rate in scanners and by the detector’s size in push broom sensors. The pixel’s angular size and the satellite’s altitude together define the sensor’s spatial resolution on the earth.

Each sensor on a remote sensing satellite assigns several digital values to each pixel, corresponding to the measured radiation levels in its various bonds. The pixel values are transmitted to earth for achieving on high density computer tapes. A third calls on computer power stems from atmospheric effects unwanted energy or ‘noise’ scattered into the sensors field of view. The atmosphere transmits and absorbs electromagnetic energy, in the process altering it spectrally.

 

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