A Grower's Guide to Remote Sensing
What you need, what's available, what's ahead
By R.D. Curley, CPAg, CCA, and Stephen Paley, Ph.D.

First, let's all get started on the same foot. What is remote sensing? It's simply viewing crops from above, recording what is viewed, and displaying the image to provide a "map" of crop health and/or soil conditions.
        These "maps" permit field scouts to pinpoint the location of crop stresses and soil conditions much earlier and infinitely more effectively than their current method of randomly walking fields to find problems. But identifying the cause of crop stresses requires field observation, and diagnosis by trained personnel. We are still many years away from reliably identifying the causes of crop stresses in imagery without scouting.
        Reliable and consistent imagery can vastly increase scouting efficiency by three to five fold. In addition, field scouts never again have to wonder whether they've missed a serious "yield-robbing" problem. ThereÍs no more guessing or gambling with your crop.
        This is what regular, timely, season-long remote sensing which provides consistent reliable imagery is capable of doing—giving your crop the chance of yielding up to its full potential, within limitations of weather and uncontrollable soil conditions.

This circular field in San Luis Valley, Colorado, is about one-half mile in diameter. The image is the first in a series of photos that show the progression of a potato disease called blackleg.

Limitations of Current Systems
Agricultural remote sensing, by analogy, is where radar was a few years before World War II. At that time, radar suffered from two deficiencies which greatly reduced its usefulness for detecting enemy aircraft: it didnÍt detect enemy aircraft all of the time ("masking"); and it sometimes displayed aircraft that weren't there ("false positives"). As a consequence, radar could not be used as the sole tool for detecting enemy ships and aircraft, and a system of human aerial spotters was used in addition in the early years of World War II.
        Likewise, remote sensing is also subject to "masking," field problems which fail to show up in its imagery, and to "false positives," nonagricultural features which mimic agricultural stress that do show up.
        Masking and false positives are caused by several effects of the atmosphere collectively known as clutter. Because of clutter, current remote sensing systems and their imagery detect and display field problems on a "hit-or-miss" basis. This means that you can't rely on them as primary crop production management tools. If a grower depended on one, and it missed an important problem, yield loss could be disastrous, resulting in a significant reduction in his profits.
        False positives lead scouts on wild goose chases in fields, causing them to look for crop problems that aren't there. They are thus big time-wasters for scouts, as well as major sources of uncertainty.
        Most imagery also displays too many features which need to be characterized by the scout, which can keep him busy in a field for a week, trying to sort out the important features. Imagery not only needs to display all problems and conditions in the field, but also to accurately distinguish between features and areas of the field which are normal„and donÍt require scouting„from areas which are stressed.
        Accurately distinguishing between stressed and unstressed areas is achieved simply by removing the effects of clutter.

One week later, a photo of the same potato field indicates the severity of its disease. This field is irrigated by a center pivot system.

Production Management Capabilities of a Remote Sensing System Without Clutter
Agricultural Management Systems (AMS), Inc., has developed a system without clutter. Doing so required new science and technology. Refining existing technology was not effective.
        The AMS system combines "clutter compensation" with sensitivity that's about 6xs that of most systems operating today in agriculture. Increased sensitivity allows detection of agricultural problems and conditions earlier, when they are at lower stress levels. But unless the affects of clutter are also removed, increased sensitivity alone will simply increase a system's ability to image false positives.
        AMS imagery displays stress levels accurately, and in a way that lets the scout distinguish stress-areas across the field with just a glance at the imagery. To that end, stress levels are assigned different colors and arranged in a particular order.
        These stress-colors change as stress levels change across the field. The changes progress from normal to poor plant health in the following order of color-change in the imagery: from dark blue to light blue, light green to medium green to dark green, to yellow, brown, light red, dark red, magenta, and finally to violet. Areas that are dark green or below are considered normal. Colors which are yellow and above are considered abnormally stressed and require scouting for identification of the cause.
        There are a number of significant advantages that such imagery can bring to crop production management systems:
1) Scouting accuracy and peak acreage increases significantly. Scouts are sure that every field problem and condition is found and that none are missed. Equally important, scouts are able to scout fields in 1/3 to 1/5 the time required by normal pattern scouting. The increased efficiency allows for them to spend more time consulting with clients rather than "just walking fields."
2) Knowing early, where and what problems exist in fields permits more timely application of treatments—often site-specific application—before problems get out of hand.
3) Many crop diseases can be detected up to three weeks before showing any visible signs of disease. Today, there are biotech tests which can identify crop diseases overnight in plant samples which do not yet exhibit signs of the disease. The PCR, for example, being developed by a number of agricultural universities.
4) Irrigation farmers can detect water deficits in their crops much earlier and more accurately. More effective irrigation scheduling and distribution can be accomplished without waste of water and the fuel used to pump it.

How does the AMS system detect stress?
By simply detecting plant characteristics that change as plants are subjected to stress—temperature, water content and/or chlorophyll content—the AMS system can detect stress. For the sake of increased sensitivity, our system uses detectors cooled to the temperature of liquid nitrogen—around 350 degrees F below zero-and far infrared radiation to produce its imagery.
        Far infrared is felt on human skin as heat. It should not be confused with near infrared, which is light slightly longer than red light. Both visible and near infrared light are used by most current systems today to produce agricultural imagery.
        Far infrared is almost completely absorbed by water, so rain or clouds below our aircraft prevent us from producing imagery. AMS can't fly in the rain. We get around the cloud problem, however, by flying at night when clouds are almost always above 3,000', our normal altitude for flying imagery.
        Another advantage to night-time flying is that imagery is transmitted electronically to customers' personal computers the same night it is flown. The imagery is therefore available for scouting within several hours, no later than 6 AM.

A Few Rules-of-thumb for Judging Remote Sensing Systems and Their Imagery
Satellite imagery contains more clutter than imagery flown at the same time and location from a low flying aircraft. This happens because satellite sensors have to look through the entire atmosphere, rather than the few thousand feet of atmosphere for a sensor aboard a low-flying aircraft.
        A system with a cooled detector will be significantly more sensitive than one which is not cooled. Cooling reduces electronic sensor "noise" which increases system sensitivity.
        Satellite sensors for agriculture cannot be cooled (or re-calibrated as they continue to change after being launched in space).
        For a given pixel size, the same system flown from a flying aircraft has greater sensitivity than if it were flown from a satellite, because the satellite sensor is further away from the field.
        Reliable production management capability described above can't be achieved from satellites because of fundamental limitations imposed by the physics of sensors and of the atmosphere.

Requirements for a Remote Sensing System to Perform Crop Production Management
The remote sensing system must remove the effects of clutter and must also have sufficient sensitivity to detect all field problems and conditions each time it flies over the field. It must also eliminate false positives from the imagery, distinguish between stressed areas which require scouting and unstressed areas which don't, and provide the above imagery at frequent, uninterrupted intervals—about weekly in our experience—so that all field problems and conditions are detected early or pre-visibly.

A Look Ahead
Remote sensing has reached the performance level that will make it one of the two major tools driving agriculture for the next few decades. The other tool is biotechnology. Clutterless imagery is a powerful production management tool right now. But developments that are shaping up in the near term will make it even more powerful. Even with modern farming techniques, up to 1/2 of yields are lost to stress. If field problems and conditions are detected early enough, many of them can be corrected before they reduce yields. Pre-visible detection of field problems with reliable imagery, followed by identification and correction of the problem, may prevent yield-losses and reduce the cost-of-inputs through site specific treatments.
        All of the pieces of the puzzle to further enhance the power of production management imagery are rapidly coming together: 1) GPS and GIS to put scouts at the location of detected stresses, visible or pre-visible; 2) instrumentation and tests developed to diagnose the cause of pre-visible stress like the PCR (light, rugged instruments for in-field diagnosis) and ; 3) mechanized equipment suitable for site-specific application.
        Another trend that may affect much of US agriculture is the major synergism between consistent, reliable imagery and precision agriculture. They both enable site-specific agriculture. There is some overlap in capability but most of it is complementary.
        Joining capital-intensive precision agriculture with frequent, low cost, reliable imagery will result in a system of crop production management that is more powerful„and much more cost-effective. For instance, the ability to detect and eliminate many crop diseases before they get a foothold will permit crops to produce more nearly up to their genetic potential. Agriculture will become more efficient, therefore more profitable at the same time.

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