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Precision farming is all about managing differ-ent parts of each field differently. Instead ofmanaging each field with one practice or rate,

you divide each field into smaller sub fields, or zonesof management. You manage each zone as a separatefield. Each zone has unique characteristics assignedto it based on several factors you collect. Past yield,soil test, and drainage data are just a few of the fac-tors you may consider when making a plan for eachmanagement zone. The challenge is managing thesecollected information layers in a way that can be usedto generate application maps for the next input or man-agement practice planned.

Developing management zones is a popular

control map? How about combining the variables ofremotely sensed organic matter with a grid soilsampled pH level map and weed boundary layer whendeveloping a herbicide application map?

Creating good management zones seems to re-quire some very flexible and advanced GIS capabili-ties. First of all, you need to be able to combine allcollected layers in unique ways. Secondly, you needto be able to generate unique, identifiable, and flex-ible management zones. Third, you must be able toquickly change the formula controlling the combina-tions of the different input layers.

There is very little advice out there right now.You must be able to change the influence or weightof all of your hard won field data layers as your indi-vidual experience grows. Maybe you see a compel-

Creating GoodManagement ZonesHow to Capitalize On Flexible Data Integration

By Kevin Royal

Elevations, color IR, soil yield ratings,yield maps, and image classifications canall be used to generate productivityratings or other application type maps forvariable rate applications.

method of using historical dataof a field to project and drivethe needs of fertilizer, seedpopulations, and chemicalrates. Many farmers use theprevious year’s yield map as aguide for locating these differ-ent productivity zones within afield. Some normalize severalyears of yield information togenerate these zones. While thisis a good method of using pastproductivity to manage eachzone, it is based on only onevariable. What if you want tocombine several different vari-ables? Would you need differ-ent variables for a weed con-trol or herbicide rate map com-pared to a fertilizer applicationmap? Would remotely sensedimagery be useful for generat-ing an organic matter and weed

ling study that emphasizes pastyields over one soil factor youfelt was important. You want tobe able to change the manage-ment formula quickly to evalu-ate the zone changes geographi-cally within your fields. Finally,you will want the flexibility toexport this management layer toeither a raster or vector formatthat is able to drive the variablerate applicator of your choice.You must be able to create thesedriver maps for fertilizer, seed,herbicide, and insecticide appli-cators by combining all of yourcollected layers in unique, eas-ily modified ways.

Field studies using TNT-mips, a full-featured image pro-cessing and GIS package fromMicroImages, Inc., Lincoln,Nebraska, demonstrate the ad-



vantages of the flexibility to combine all collected lay-ers in order to generate the relative productivity po-tential for each management zone. By combiningthese collected layers of field information into vectoror raster application maps, a targeted field profile canresult that contains more complete information fordriving variable rate application equipment.

The first step is to generate all of the layers thatwill influence the management zones you build foryour fields. Many people begin this step by collect-ing yield information that has been contoured or sur-face fitted into raster form. You probably want thesurface raster raw data values to be equal to the yieldat each point so you can examine individual sub ar-eas of the field directly. Soil testing on a grid basis orother similar point data can also be contoured to gen-erate the inventory layers showing “what is whereand in what amounts” throughout the fields.

Another group of layers you will want to incor-porate are any remote sensing images you can col-lect. Using air photo or satellite images, biomass andorganic content rasters can be easily generated, as wellas weed and insect pressure raster data. These areimportant variables that can be easily incorporated intoyour management formulas.

Use the Orientation tool to orient the management zones to match your fields. Choosing a management resolution youcan economically deal with is an important consideration and is independent of the raster layer input resolution.Sample points can also be generated for guiding you back to new sample (soil test, etc.) locations within any zone.

One thing to consider when getting the inputlayers lined up is the range of raw data values that thecollected data will generate in the contour rasters. Youmay want to scale each contour raster so that the high-est value of the organic matter raster is roughly equalto the highest value of the yield raster. This will makechanging the proportion or weight of each layer inthe management formula easier.

The second step is to generate some type of man-agement zone or boundary. You can use any type ofvector polygon you like. Soil types, direct photo in-terpretation, or past yield zones can be used for theseboundaries. In this article, I will concentrate on agrid management system. Choose a boundary poly-gon that represents the border of the fields you wantto manage. Once the boundary is loaded, TNTmipslets you use an Orientation tool to set the directionand enumeration (unique identifying number) of thegrid cells. Enter the grid size you want to generate byentering the area enclosed or length of sides. This isthe “Management Resolution” or smallest area youwant to manage as a separate unit. Using a multipleof the width of your normal application equipmentseems sensible, unless you can control the rate of eachindividual nozzle or planter box. Save the vector onceyou like the preview grid on your screen.

You can also generate sample points within eachgrid while in this process. Set an allowed variation



from the center of each grid cell as a percentage ofthe overall grid area. These can become navigationpoints for you to collect additional data within eachgrid management zone.

To get the properties of the collected rasters tothe management grid vectors, load all of the rasterlayers you want to use in your formula to computethe management zones along with the grid vector thatforms the boundaries of the management zones. WithTNTmips, this is accomplished using the Raster Prop-erties process. The process will generate a separatedatabase table from each input raster layer within eachgrid that contain the Max, Min, Mean, Mode, Me-dian, Standard Deviation, Cell Count, and a Normal-ize Factor of the raster for all cells encountered withineach grid polygon or management zone.

You can also transfer any other point data youhave collected to the management grid. If you have awell, rock, or any other feature marked with a GPSlocation, that feature can be transferred to the man-agement grid using the Transfer Attributes process.

With the variables from several collected layersattached to the management zones as database records,you can load the grid into the Display program andbegin to put together formulas based on several vari-ables. You can combine the variables collected fromany input raster in any way you want. The resultingnumbers in the computed field change any time the

input raster values in the attached tables change orthe expression (formula) changes. You can enter anyformula you like, multiplying, adding, dividing, orapplying any formulas you find useful for generatinga good management zone.

Depending on the type of management zone youwant to generate, it’s possible to create several com-puted fields with different combinations of collectedlayers. This is useful when using different layers tocompute a fertilizer variable rate layer compared to aherbicide rate layer. Archive several years worth ofattached databases to compare the changes from yearto year in the management zones to see if the variablerate applications you have made are having any ef-fect on the fertility, weed pressure, or yield of themanaged zones.

With the development of accounting zones, vari-able rates of seed, fertilizer, and chemicals can be re-corded as point data, much like yield information.Using the Surface Modeling and Raster Propertiesprocesses, you can surface fit the collected point ap-plication rates and transfer the mean application ratesper management zone to the polygons that form thezones. Then use the Computed field function to ar-rive at your expected net income per zone.

Vary the expected price for high, medium, andlow market scenarios. Once quality monitors are avail-

Transferring thestatistics of themultiple layers youhave collected to themanagement zoneswill allow you tomore easily work with several layers as variables whenyou work up your management formulas. The zones canbe any shape, and may be generated from soil maps,photointerpretation, or past yield information.

able, this attribute can be surfacefitted (contoured) just like anyother database field attached tothe yield points. Use this qualitydata as a factor in the net incomecomputed field to influence thevalue of all production from eachmanagement zone. You can setvarious premiums for the meanprotein content of each zone, justas you would with the expectedprice of non-premium gradedcrops.

The Display process has several ways of ThemeMapping the computed fields. As you change theformulas or expression that governs the values in the



This article is paraphrased from the original article of the same title:Royal, Kevin (1998). Creating Good Management Zones: How to Capitalize from FlexibleData Integration. Modern Agriculture, Fall 1998, 26–28.

About the author:Kevin Royal is responsible for technical sales and product support for several deal-ers of TNT products worldwide. He is also the Technical Support Team Leader atMicroImages and farms near Palmyra, Nebraska.He may be reached at 402-477-9554 (phone) or [email protected] (email).

computed fields, the colored theme mapped manage-ment grids change. This theme is dynamically linkedto the expression, so you can get instant visual feed-back of the new management zones that result from

The values in multiple database tables attached to themanagement zones are combined by a readily editablescript to generate productivity values, which are showntheme mapped into 10 productivity levels. One of thefactors used to determine productivity is the previousyield for each zone (Yields.Mean). The effect of changingthe weighting of Yields.Mean from 3.5 (upper) to 3 isshown. The altered appearance of the theme mapdemonstrates the dynamic linking of the calculatedproductivity and the displayed management map.

your newly entered formula.Once you have adjusted the computed expres-

sion for each management database field, you can makethat field permanent to lock in the current values. Youcan export the management zones to a format under-stood by a variable rate applicator or planter control-ler. Some controller software requires CAD like for-mat files such as AutoCad Exchange (DXF) formator possibly the Digital Line Graphic (DLG) formats.The TNTmips export process can also generateMapInfo or Arc-Shape files as well as many rasterformats. These formats can be directly exported towith the computed management field as an attacheddatabase table or raster cell value. When the control-ler software senses that the applicator is within one ofthe grids, it looks at the attached database or cell valueand adjusts the application rate according to the datarecord attached there.

The ability to generate georeferenced applica-tion maps in many different formats to drive variableapplication fertilizer, herbicide, and planting equip-ment based on the results of the integrated manage-ment zone maps is important. All of the layers thatyou have collected from past yields, soil and planttissue tests, and remote imaging can be used as vari-ables in the formation of field management maps. Totake advantage of the different types of layers requiresa tight integration of raster and vector data types anda flexible formula editor to vary the weights of theinput layer variables in your application formula. Youmust be ready to let the researchers and universitiessort it out while you are ready to quickly react to find-ings that make sense for your own farm.Don’t underestimate the information managementneeds of Agriculture, modern crop production requiresadvanced spatial data analysis software.

creating good management zones - microimages, inc.as you change the formulas or expression that...

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