Geometry
Confirm field, coordinate reference, boundary, exclusion areas, grid or zone alignment, and intended coverage.
GEOREFERENCED FIELD INSTRUCTIONS
Prescription
Maps
A prescription map assigns a target rate, product, population, depth, or other controllable value to locations or management zones within a field.
4CHAPTERS4VISUAL BLOCKS12GRAPH LINKS2SOURCES
DECIDE / SELECTED CONCEPTPrescription MapsStart with the role, then move through the editorial sequence.
HOW TO READ THIS PAGE
Visual explanationA diagram or operating scene makes the relationship visible.
Structured modelA flow, comparison, capability set, or boundary map organizes the idea.
Guided explanationOriginal prose connects the concept to its operating context.
01 / Overview
A map can carry
a field decision.
A prescription is the decision layer between observed variability and machine control. It combines field geometry with target values chosen through agronomic analysis, rules, models, experiments, or service recommendations.
The file does not discover the correct rate on its own. It records a decision that must remain interpretable after export, transfer, display, and machine execution.
02 / Workflow
Evidence becomes zones,
zones become targets.
01
OBSERVEBuild the evidence layerField identity, boundaries, sampling, yield, imagery, terrain, crop, season, methods, uncertainty, and source lineage
02
DECIDEVersion management intentQualified objective, zones or grid, target values, products and units, assumptions, authority, review, effective state, and exclusions
03
HAND OFFTransfer to the machine chainFormat, coordinate context, field and task identity, terminal preview, supported function, configuration, default behavior, and operator acceptance
04
RECONCILECompare intent with evidenceAs-applied report, interruptions, coverage, product and rate context, physical checks, corrections, outcomes, uncertainty, and next evidence need
CONTROLLED MEANINGThe decision must survive every handoff.
Identity, geometry, units, provenance, versions, authority, machine limits, exceptions, and review remain visible around the loop.
01EVIDENCE / 01Spatial layersSoil, yield, imagery, elevation, crop, or scouting data
02MODEL / 02Management logicZones, constraints, response assumptions, and economics
03PRESCRIBE / 03Target mapProduct and rate attached to field geometry↗04VERIFY / 04As-applied resultMachine record compared with intended work
03 / Integrity checks
Before the field,
validate the instruction.
Units and products
Verify rate units, product identity, density or concentration assumptions, and machine conversions.
Machine limits
Check minimum, maximum, increments, section width, response time, and default behavior outside mapped areas.
Transfer preview
Inspect the prescription on the receiving terminal before application and retain the original version.
04 / Boundaries
Spatial detail can exceed
decision quality.
More zones are not automatically better.Resolution should reflect evidence quality, management scale, machine response, and economically meaningful variation.
Interpolation creates estimates.Values between samples depend on assumptions and should not be presented as directly observed measurements.
Transfer can change meaning.Units, products, geometry, attribute names, unsupported values, or coordinate handling can shift during conversion.
As-applied is the execution record.The prescription shows intent; machine documentation is needed to evaluate what the system reports it actually applied.
05 / Connections
See the system around this concept.
Follow incoming and outgoing relationship records to understand what supplies, informs, enables, coordinates with, or extends this technology in the published knowledge graph.
Relationship radar / published edges12 records / 12 neighboring systems
Incoming07records point toward this concept
decide rolePrescription MapsSelected technology
Outgoing05records point from this concept
12connections visible
observe / Field sensingYield Monitoring and Mapping ↗can inform
Cleaned, interpreted yield maps can contribute historical field evidence when agronomic teams prepare later management decisions.
decide / Farm softwareFMIS ↗organizes and exchanges
Farm management software can organize the field context and task information around prescription-map workflows.
act / Field applicationVariable Rate Technology ↗provides spatial intent to
A prescription map can express where a variable-rate operation should change its target across a field.
observe / Earth observationAgricultural Remote Sensing ↗can contribute evaluated spatial evidence to
Validated remote-sensing patterns can contribute one evidence layer when agronomic teams define management zones or spatial instructions.
observe / Soil intelligenceDigital Soil Mapping ↗can contribute qualified soil evidence to
A validated soil class or property map can contribute one spatial evidence layer to an agronomically reviewed prescription workflow.
act / Precision plantingVariable-Rate Seeding ↗can provide reviewed spatial seeding intent to
A versioned prescription can associate bounded field zones with reviewed seeding targets, crop and seed context, units, checks and fallback behavior for a variable-rate planting operation.
observe / Aerial platformsAgricultural Unmanned Aircraft Systems ↗can provide reviewed spatial application intent to
A supported prescription can associate bounded field zones with reviewed targets for an agricultural UAS application, while exact format, units, transfer, route, rate control, fallback, local permission, and as-applied verification remain separate checks.
act / Planting systemsElectric Planter Row Drive ↗can provide reviewed spatial intent to
A supported prescription can provide bounded population targets to an electric row-drive workflow while agronomic evidence, units, coordinate reference, version, transfer, position quality, transitions, controller limits, fallback, physical output and later response remain explicit.
position / Geospatial field modelingAgricultural Field Boundary Mapping ↗can provide reviewed spatial context to
An accepted operational field extent and exclusions can provide spatial context for a prescription workflow, but do not supply agronomic evidence, treatment authority, zone logic, units, product identity, rate limits, accessibility, machine compatibility, or approval.
act / Irrigation controlVariable Rate Irrigation ↗can provide reviewed spatial intent to
A supported prescription can provide bounded spatial water targets to VRI while evidence, field identity, units, version, transfer, machine interpretation, position, hydraulics, transitions, fallback and physical delivery require acceptance.
observe / Nutrient managementManure Nutrient Characterization ↗can contribute bounded material evidence to
A qualified manure analysis can contribute one material-specific input to reviewed spatial intent while field evidence, crop needs, nutrient credits, legal authority, units, equipment, approval, and fallback remain separate.
decide / Production intelligenceAgronomic Model Decision Support ↗can contribute reviewed evidence to
A bounded agronomic model may contribute one evidence layer to a spatial plan when inputs, assumptions, version, uncertainty, human review, and field identity remain explicit.
8CONNECTED ROUTES2–6STEP POSITIONS66ROUTE SOURCE LINKS
Technology system
From field evidence to application
Follow a complete decision loop from measured field variation through management software and spatial intent to machine-side application control.
- 01 / OBSERVEMeasure with yield mappingTechnology→
- 02 / ORGANIZEPut the record in an FMISTechnology→
- 03 / DECIDEBuild prescription intentTechnology→
- 04 / VARYExecute variable rateTechnology→
- 05 / COVERCoordinate section controlTechnology→
- 06 / MODULATEControl flow at the nozzleTechnology→
- 07 / CANOPYCoordinate liquid, airflow, and chargeTechnology
CURRENT POSITION03
03 / DECIDE
Open the complete route ↗Build prescription intent
Learn how a prescription map expresses a spatial agronomic decision without acting as the machine controller itself.
06 / Evidence
Primary sources.
This briefing uses USDA ERS for the map-to-variable-rate information flow and ISO 11783-10 for task-controller and farm-management data interchange. Prescription quality and execution must be validated for the crop, field, software, terminal, and implement.
01
Precision Agriculture in the Digital Era: Recent Adoption on U.S. FarmsUSDA Economic Research Service · Accessed 2026-07-11
02
ISO 11783-10:2015 — Task controller and management information system data interchangeInternational Organization for Standardization · Accessed 2026-07-11