CASE STUDY
Highland Precision Ag Uses ENVI®
Crop Science to Detect Plant Stressand Target Remediation
Tight profit margins are nothing new to growers. Fertilizers
and crop protection chemicals can amount to up to half ofseasonal expenses in large-scale agribusinesses. Crop losses
due to disease and pests can take another big bite out ofyield. And, with a large portion of budgets tied up in fixed
costs, remote sensing applications in precision agriculture
are being looked to as one way to optimize those costs andimprove margins.

HIGHLIGHTS:• Monitor crop health down tothe individual plant level• Detect plant stress and target
specific field locations for
remediation• Monitor crop growth for harvest
and yield predictions

EFFECTIVELY USING REMOTE SENSING IN PRECISION AGRICULTURE
To realize the potential that remotely sensed data offers, advanced analysis tools like ENVI® can be used toextract actionable information. For example, when multispectral imagery is analyzed, patterns become visiblethat are not clearly discernable to the human eye. This offers a window into the growth cycle that enables
early stress and disease detection, and provides information so interventions can be implemented before acrop becomes permanently impaired. The good news for growers is that ENVI® Crop Science now makes theinformation from these advanced techniques available to anyone, regardless of their prior experience withremote sensing.
IN NEED OF A NEW PERSPECTIVE
When dealing with large spatial patterns, it is sometimes difficult to see the forest for the trees. HighlandPrecision Ag (HPA), a company that assists growers in using precision agriculture, found this to be especiallytrue while working with one strawberry grower in Florida. The farmer had noticed that some areas in his fields
appeared to be dying, but there was not an obvious reason as to why. He first investigated the normal culprits,
but all the plants in the field were being treated with the same amounts of crop inputs. There also did notappear to be any environmental factors at play, such as fungus, mildew, or pests.
The problem also did not appear to be related to fertigation, given that the ailing plants were in different
beds, were not connected to the same fertigation lines, and were even in the middle of some of the lines. Even
more confounding, the plants on either side of the ailing plants were fine.

HPA collected satellite imagery over the affected area to gain a different
perspective. After downloading the Airbus imagery from the Harris
Geospatial Marketplace, they began their analysis. HPA noticed that thepattern of senescence patches appeared sporadic and could barely be
distinguished (Figure 1).
ENVI CROP SCIENCE CHANGES THE EQUATIONHPA then applied the Hotspot Analysis tool in ENVI Crop Science. The
tool uses a single band of input data to look for statistically significant
regions within an image, but true-color imagery has three bands (red,green, blue). That meant the Airbus imagery had to be distilled down toa single input layer before the analysis could be run.
A Normalized Difference Vegetation Index (NDVI) is a single band andcan be used as an indicator of plant health. By creating an NDVI imagein ENVI and then using the Hotspot tool, HPA was able to resolve thissenescent pattern with much higher fidelity.

Figure 1: True-color image of strawberry field

The output of the Hotspot tool was a classification image with red,green, and yellow regions. In this case, the red regions revealed low
NDVI values (senescent plants), green regions were higher NDVI values(above average healthy plants), and the yellow regions revealed areasthat were neither exceptionally senescent nor extremely healthy (an area
without a contiguous spatial pattern). A comparison of figures 1 and 2
revealed that these senescent regions were occurring in a straight line
across this field. Knowledge of this spatial pattern was taken back to thefield and investigated on the ground.
The field scout determined that early in the season, the sprinkler
system that was being used had been miscalibrated. Figure 3 shows a
representation of the sprinkler layout. The miscalibration resulted ininadequate head-to-head coverage. The areas with single coverage did
not receive enough water after being transplanted, and consequently
these areas underperformed later in the season. On the other hand, theareas with quadruple coverage received the most water and therefore
thrived.

Figure 2: Hotspot results derived from NDVIimage

Figure 3: The sprinkler coverage map(left) and hotspot imagery (right) overlaid with sprinkler coverage patterns shows single, double, andquadruple coverage areas.

CONCLUSION
According to the HPA field scout,without ENVI Crop Science, thisanalysis and discovery would nothave been possible. The resultsfrom this analysis gave HPA theinformation and confidence toapproach the farm operators withrecommendations about the best
spacing of their sprinklers for next
season to get the highest yieldfrom their land.

FOR MORE INFORMATION:
www.harrisgeospatial.com
Email: geospatialinfo@harris.com
Phone: 303.786.9900

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