Sampling in Alpha Units

Alpha units, stretching across the enterprise environment.

As Our Wealth of Data and its Wasted Potential so eloquently put it, big data companies and research programs in our modern age have more data than they have the funds or time to analyze. For a price, all of this data could be available to Rural System, feeding directly into the prescriptive software of VNodal.

This data only goes so far, however, because Rural System calls for land management that responds to the unique characteristics of the land at a very high spatial resolution: 10m x 10m. This calls for correspondingly high resolution of data, which is lacking in most databases covering an area as expansive as the state of Virginia.

As an example, take a look at the soil survey database available through the USDA. You can download information about soil types for any area of the U.S. for free. Unfortunately the information is not specific enough for Rural System management. Knowing that an area of land is a sandy loam does not tell us anything about the actual nutrient content of the soil and very little about the specifics of its composition.

The Rural System logo, an ear of corn, contains a notable 4×4 grid of alpha units.

In order to supply the missing data, Dr. Giles has proposed breaking the enterprise environments in Rural System into what he calls alpha units. Alpha units are essentially 10m x 10m sampling plots covering every meter of the managed property. Much like snowflakes or people (unless you support Tyler Durden), every alpha unit is unique. Rural System is thus listening quite closely to the enterprise environment, much as a doctor listens to your heart beat.

Nothing on the land is static either, so the management actions performed would likely change dynamically. Sampling and monitoring would have to be done on all alpha units frequently, if not daily on smaller properties.

Monitoring would have to extend to include a 100m buffer around the property, so that incoming pollution or threats from invasive species can be detected before they affect the enterprise environment.

Naturally, the information entered into the corresponding GIS map would also be organized in a grid of alpha units. Each of these alpha units could then have a designation, or pre-determined purpose.  This would only be done in the case of clear limitations on land use in that alpha unit (for example, we’ve already seen how alpha units can be designated as reserve areas).

Here you can see the corner of one or more hypothetical alpha units that have been put to use as vineyards.

Those alpha units that do not have a designation will be evaluated for one or many uses by VNodal. Characteristics such as slope, aspect, soil type, soil nutrient content, presence or absence of water, species present, and etc. will all be taken into account by VNodal in the determination of this(these) use(s).

With constant sampling on alpha units, Rural System would thus be employing a continuous feedback loop as changes are made on the land.  Managers can use this feedback to evaluate the efficiency with which management objectives are achieved.  This data, highly specific to individual enterprise environments, thus supplements existing databases nicely to produce the most precise management possible.

So now that you know how Rural System obtains and uses data to manage its enterprise environments, what do you think? Do we go far enough to provide precise management?