GeoPard Tutorials | Precision Ag Software
  • Introduction to GeoPard
    • GeoPard Platform: Frequently Asked Questions (FAQ)
  • 🖥️Product Tour - Web App
    • Getting Started
      • Create a new farm
      • Draw a new field
      • Upload a field boundary
      • Edit a boundary
      • Edit a field name
      • Add a label
    • 🛰️Satellite Monitoring
      • Order Planet Scope (3m daily) imagery
      • Indices for Crops and Soils
      • 📈Crop Development Index Graph
    • 📊Zones Maps and Analytics
      • Assign Variable Rates in the Zones (Ag inputs Rates Distribution Tool)
      • Creating Zones Map using Satellite Imagery
      • Creating Zones Map using Soil/Yield/As Applied Data
      • Creating Zones Map using Topography
      • Creating Zones Map using a Template
      • Draw Zones Manually, Clone from an existing layer
      • Usage of Data Classification
      • Edit Zones Map: Merge & Split
      • Multi-Year Zones
      • Multi-Layer Analytics
      • Compare layers
      • Heterogeneity factor
      • Relative variation factor
    • 📊Equation-based Analytics
      • Batch Equation analytics
      • Catalog of Predefined Agronomic Equations
      • Catalog of Custom Functions
    • ⛰️Topography
    • ⛰️3D Maps
    • Import
      • Field Boundary
      • Soil Data
      • Yield Data
      • As Applied/As Planted Data
      • Machinery Proprietary Formats
      • Import from MyJohnDeere
    • Export / Download
      • Field Boundary Export
      • Batch Export of Boundaries, Zones and Scouting Pins
      • Zones Map Export as shapefile
      • Satellite Imagery Export as geotiff or geojson
      • Export Scouting Notes as shapefile
      • Export VRA map In ISOXML Format
      • Export to MyJohnDeere
    • 🤖API
    • Operations Log - Track errors/Imports and Analytics
    • Organizations and Roles
    • Farms Sharing between Accounts & Organizations
    • Managing Crop Season information with tags(labels)
      • Case: Managing fields for several clients
      • Case: Season details including crop and year
      • Case: Field operation details
    • ⚙️User Settings
      • Subscriptions, Account limits & Plans
      • Restoring password
      • Order the package
      • Changing preferences
    • 🚜John Deere Operations Center Integration
      • 🚜John Deere Operations Center Integration
        • 1. Create Free Trial Account with you John Deere Account
        • 2. Connect to JohnDeere Operations Center
        • 3. Connect to John Deere Organizations
        • 4. Import into GeoPard from John Deere Operations Center
        • 5. Configure Automated Data Sync
        • 6. Export Rx Maps to John Deere Operations Center as Files
        • 7. Export Field Boundaries into John Deere Operations Center
          • 7a. Organization configuration of export boundary to John Deere Operations Center as File
        • 8. Export Rx Maps to John Deere Operations Center as Work Plans
        • 9. Export Soil, Topography, Satellite or Analytics as Map Layers
      • 🚜John Deere Operations Center Data Sharing
        • 1. "Staff Member" sharing
        • 2. Problem-solving of "Staff Member" sharing
        • 3. "Partner Organization" sharing
        • 4. Problem-solving of "Partner Organization" sharing
        • 5. Problem-solving of import from John Deere to GeoPard
        • 6. Problem-solving of Work Plan creation
        • 7. Sharing Fields/Boundaries Between Partner Organizations in John Deere Ops Center, DataSync config
  • 🚀Changelog & Product Releases
    • Release Notes
      • Release Web April 2025 (Rates Distribution, improved Legends)
      • Release Web March 2025 (Improved Zones, WorkPlans updates, Yield data enhancements)
      • Release Web January 2025 (Free Trial, Usage-based Pricing Plan, USDA Yield Cleaning protocol, Export of calibrated Yield data to John Deere Ops Center, Import of kml)
      • Release Web August 2024 (Data Layer Previews, Spatially localized Zones; Use zones and Equations in new Equations)
      • Release Web July 2024 (Equation Map creation, Spatially localized zones, Seeding and Application Work Plans)
      • Release Web May 2024 (Raw view for Satellite Images, export of Zone Maps as WorkPlan to the John Deere Operations Center, redesign of Batch Analytics)
      • Release Web April 2024 (Batch Equation Maps and enhanced layer transparency)
      • Release Web February 2024 (Per area pricing, units)
      • Release Web January 2024 (many UI improvements)
      • Release Web November 2023 (Clone Polygons, Subscription management)
      • Release Web October 2023 (Yield Calibration, Equation Maps as ISOXML, PDF Export and John Deere Integration)
      • Release Web September 2023 (Cleaning & Calibrating Yield Datasets, more languages support)
      • Release Mobile August 2023 (Mobile app impovements)
      • Release Web July 2023 (Operations Log page, Sum in datasets)
      • Release Web June 2023 (Improved Equations, Operations log v1)
      • Release Mobile May 2023 (Social Login)
      • Release Web May 2023 (John Deere integration improvements)
      • Release Web January 2023 (huge amount of small improvements)
      • Release Web October 2022 (Integration with AgGateway protocols, Isoxml support and more)
      • Release Web April 2022 (3D maps and Zoning Tools)
  • 👨‍🌾Agronomy
    • Precision Agronomy Use Cases & Best Practices Overview
    • Field Management Zones (Productivity Zones) Creation Process
    • Variable Rate Seeding (Planting) Maps
    • Yield Calibration & Cleaning
    • Synthetic Yield Map
    • Create Soil Sampling Zones, Points, Route, export as KML, and execute
    • Evaluate Accuracy of Seeding Application
    • Evaluate Accuracy of Fertilizer Application
    • Field Trial Analytics
    • Nitrogen Use Efficiency & Uptake
    • Comparing Yield Datasets
    • Compare Soil Scanner Data between Years
    • Flood Detection / Insurance report
    • Profit Maps (COMING)
    • VRA/Rx/Prescription Fertilizer Maps (COMING)
    • VRA/Rx/Prescription Nitrogen Maps (COMING)
    • VRA/Rx/Prescription Spraying Maps (COMING)
    • Multi-Layer Field Potential Maps (COMING)
    • VR Lime Application Based on Soil Scanner pH Data (COMING)
    • Merging Yield Datasets Belonging to the Same Field (COMING)
  • 📱Product Tour - Mobile App
    • Installation
    • Logging in
    • Viewing satellite images
    • Viewing zones maps
    • Viewing soil data
    • Viewing yield data
    • Viewing topography maps
    • Viewing as applied datasets
    • Working in the field/Scouting zones maps
    • Working offline
    • Filters
    • Options
    • Settings
  • 🤖API Docs
    • GeoPard API Overview
    • Getting Started
    • Authorization: ApiKey, Credentials or OAuth 2.0
    • Diagrams with Basic Flows
      • 1. Field Registration
      • 2. GraphQL Subscription
      • 3. Grep Satellite Imagery
      • 4. Upload Soil | AsApplied | Yield Datasets
      • 5. Execute Equations
      • 6. Generate ZonesMap
      • 7. Download Gridded Data
      • 8. Download Original Data
    • Data Schema
    • Requests Overview
      • 1. Subscription: Get Events
      • 2. Query: Get "Fields"
      • 3. Query: Get "SatelliteImages"
      • 4. Query: Get defined "SatelliteImage"
      • 5. Query: Get "RasterMaps"
      • 6. Query: Get "ZonesMaps"
      • 7. Mutation: Generate "ZonesMap"
      • 8. Mutation: Generate "RasterMap"
      • 9. Mutation: Generate "ZonesMap" asynchronously
      • 10. Mutation: Generate "RasterMap" asynchronously
      • 11. Mutation: Generate Yield based "ZonesMap" asynchronously
      • 12. Mutation: Generate Soil based "ZonesMap" asynchronously
      • 13. Mutation: Create "Farm"
      • 14. Mutation: Create a "Field" or edit the boundary of the existing field (with optional labels)
      • 15. Query: Get "TopographyMap"
      • 16. Query: Get "YieldDatasets"
      • 17. Query: Get "SoilDatasets"
      • 18. Mutation: Generate zip archive with "ZonesMap" and "Field"
      • 19. Mutation: Delete "Field"
      • 20. Mutation: Delete "Farm"
      • 21. Mutation: Delete "ZonesMap"
      • 22. Mutation: Delete "RasterAnalytisMap"
      • 23. Mutation: Delete "SoilDataset"
      • 24. Mutation: Delete "YieldDataset"
      • Notes (Pins)
        • 25. Mutation: Save "Note" attached to "Field"
        • 26. Mutation: Save "Note" attached to "ZonesMap"
        • 27. Mutation: Save "Note" attached to "SoilDataset"
        • 28. Mutation: Save multiple "Notes", Batch operation
        • 29. Mutation: Delete "Note"
        • 30. Mutation: Delete multiple "Notes"
        • 31. Query: Get all "Notes" related to "Field"
        • 32. Query: Get "Notes" related to "ZonesMap" and type
        • 33. Query: Get "Notes" related to "SoilDataset" and type
        • 34. Query: Get a selected "Note" with all "Comments"
        • 35. Mutation: Add "Comment" to the selected "Note"
        • 36. Mutation: Add multiple "Comments" to the selected "Notes"
      • 37. Query: Get "SatelliteImages" in the defined interval
      • 38. Query: Get "UserData"
      • 39. Mutation: Set custom color schemas to selected "GeoMaps"
      • 40. Query: Get "Labels" on the account level
      • 41. Mutation: Save "Labels" on the account level
      • 42. Mutation: Delete "Label" on the account level
      • 43. Query Get "Fields"
      • 44. Mutation: Set Field Labels
      • 45. Mutation: Save User Data
      • 46. Mutation: Generate multi-layer "ZonesMap" asynchronously
      • 47. Query: Get "ZonesMaps"
      • 48. Query: Get Gridded Data from "TopographyMap"
      • 49. Query: Get Gridded Data from "FieldSatelliteImage"
      • 50. Query: Get Gridded Data from "VectorAnalysisMap"
      • 51. Query: Get Gridded Data from "YieldDataset"
      • 52. Query: Get Gridded Data from "SoilDataset"
      • 53. Query: Get Gridded Data from "AsAppliedDataset"
      • 54. Query: Get Vector Data from "SoilDataset"
      • 55. Upload zip files (over 6 MB)
      • 56. Upload photos
      • 57. Query: Get "Photos" attached to the selected "Note"
      • 58. Query: Get "Photos" attached to "Comments"
      • 59. Query: Get "AsAppliedDatasets"
      • 60. Mutation: Generate As-Applied-based "ZonesMap" asynchronously
      • 61. Mutation: Delete "AsAppliedDataset"
      • 62. Mutation: Share Farms
      • 63. Mutation: Save Organization
      • 64. Mutation: Add Users to Organization
      • 65. Mutation: Delete Users from Organization
      • 66. Mutation: Save Field
      • 67. Mutation: Save Farm
      • 68. Mutation: Refresh "VectorAnalysisMap" Statistics
      • 69. Mutation: Delete "Photo"
      • 70. Mutation: Delete multiple "Photos"
      • 71. Mutation: Generate a zip archive with "Notes"
      • 72. Query: Get Gridded Data as GeoJSON or GeoTIFF
      • 73. Query: Get Gridded Data with the Selected Buffer
      • 74. Mutation: Verify "Equation"
      • 75. Mutation: Generate "EquationMap" asynchronously
      • 76. Query: Get "EquationMap"
      • 77. Mutation: Delete "EquationMap"
      • 78. Query: Find "Fields" by "externalKey"
      • 79. Query: Find "Farms" by "externalKey"
      • 80. Query: Get Original Data
      • 81. Query: Get GeoJSON of "EquationMap"
      • 82. Query: Restore Subscription Events
      • 83. Query: Collect Platform Context
      • 84. Mutation: Calibrate and Clean YieldDataset
      • 85. Mutation: Assign Rates to VectorAnalysisMap (ZonesMap)
      • 86. Query: Get "Farms"
      • 87. Mutation: Save Custom VectorAnalysisMap (ZonesMap)
      • 88. Mutation: Export ZonesMap as Zipped Shapefile
      • 89. Mutation: Export ZonesMap as Zipped ISOXML
    • Geo Endpoints
      • WMS - Get Raster Pictures of Spatial Data Layers
        • 1. LAI
        • 2. RGB
        • 3. Field: boundary
        • 4. Field: thumbnail
        • 5. ZonesMap
        • 6. ZonesMap: custom color schema
        • 7. ZonesMap: thumbnail
        • 8. RasterMap
        • 9. RasterMap: custom color schema
        • 10. RasterMap: thumbnail
        • 11. TopographyMap: elevation in absolute numbers
        • 12. YieldDatasetsMap
        • 13. SoilDatasetsMap
        • 14. SoilDatasetsMap: custom color schema
        • 15. AsAppliedDatasetsMap
        • 16. Satellite Image: cropped by Field boundary
        • 17. Satellite Image: cropped by Field boundary and custom color schema
        • 18. YieldDatasetsMap: custom color schema
        • 19. Satellite Image: 10 colors visualization
      • WFS - Get Spatial Data Layers in Vector format (shp, geojson)
        • 1. Get the Field Boundary as Geojson
        • 2. Get the Zones map as Geojson
        • 3. Get Zones Attributes as JSON
        • 4. Get Soil data as Geojson
        • 5. Get Yield data as Geojson
    • Uploading Files
    • API FAQ
  • 🛣️Platform Roadmap
    • Roadmap
  • GIS quick Hints
    • QGIS: Change String to Number values in the shapefile
    • QGIS: Yield Data Manipulations
    • QGIS: Split Boundaries Into Subfields
    • QGIS: Merge Vector Layers
    • QGIS: Merge Selected Features from Vector Files
    • QGIS: Calculate NDVI for the Drone Geotiff File
    • QGIS: Split Multi-field Shapefiles
    • QGIS: Convert CSV to SHP
    • QGIS: Reproject Shapefile
  • Policies
    • Your Data Stays Yours, Securely Managed By GeoPard
    • Terms & Conditions
    • Privacy Policy
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This Portal Sections

  • Introduction
  • Product Tour - Web App (incl. video)
  • Product Tour - Mobile App (incl. video)
  • Precision Agronomy Use Cases

Powered by GeoPard Agriculture - Automated precisionAg platform

On this page
  • Overview
  • VRS Map Configuration Options
  • 1. Field Potential Based on Imagery Only
  • 2. Field Potential Based on Imagery, Topography, and Soil Brightness
  • 3. Field Potential Based on Yield, Soil Sampling/Scanning, Imagery, Topography, and Soil Brightness
  • 4. Equation-Based Approach for Planting
  • Variable Rate Planting Recommendations Table
  • Post-Season Analysis
  • More PrecisionAg use-cases
  • How to Start

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  1. Agronomy

Variable Rate Seeding (Planting) Maps

GeoPard provides several options how to create VRA planting maps

PreviousField Management Zones (Productivity Zones) Creation ProcessNextYield Calibration & Cleaning

Last updated 9 months ago

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Overview

Variable Rate Seeding (VRS) or VR Planting maps are essential for optimizing seeding strategies based on field-specific conditions. Configuring VRS maps effectively can significantly enhance crop yield and resource efficiency. This guide outlines the main aspects and options for creating effective VRS maps using GeoPard's precision agriculture tools. Read more about .

VRS Map Configuration Options

The following are some recommended configurations for VRS maps

1. Field Potential Based on Imagery Only

  • Description: Use historical imagery to create Variable Rate Seeding (VRS) maps based on the . GeoPard's automated recommendation system helps identify representative years. Since predicting the next season's weather is challenging, it compensates for outlier years (e.g., balancing too dry with too wet years) to provide more accurate recommendations. .

  • Best For: Quick start scenarios, especially when crop rotation information is available. Select years with the same crop (e.g., corn years for corn planting).

2. Field Potential Based on Imagery, Topography, and Soil Brightness

  • Configuration: Assign negative weight to slope (to account for erosion risk) and to higher soil brightness (indicating less organic matter).

3. Field Potential Based on Yield, Soil Sampling/Scanning, Imagery, Topography, and Soil Brightness

  • Description: Integrate multiple data sources for a comprehensive field potential map.

  • Steps:

4. Equation-Based Approach for Planting

  • Flexibility: Allows for tailored configurations based on specific agronomic needs.

Variable Rate Planting Recommendations Table

Below is a comprehensive table of planting recommendations for various crops across multiple countries.

The population recommendations are in seeds per acre for the USA and Canada and seeds per hectare for other countries.

Crop
Country
Population (Seeds/Acre)
Population (Seeds/Hectare)

Corn

USA

28,000 - 34,000

Canada

28,000 - 34,000

Ukraine

65,000 - 75,000

Brazil

60,000 - 70,000

Australia

70,000 - 85,000

Germany

70,000 - 85,000

France

70,000 - 85,000

Wheat

USA

1,000,000 - 1,300,000

Canada

1,000,000 - 1,300,000

Ukraine

4,000,000 - 5,000,000

Brazil

3,500,000 - 4,500,000

Australia

4,000,000 - 5,000,000

Germany

4,000,000 - 5,000,000

France

4,000,000 - 5,000,000

Soybean

USA

140,000 - 180,000

Canada

140,000 - 180,000

Ukraine

350,000 - 450,000

Brazil

300,000 - 400,000

Australia

350,000 - 450,000

Germany

350,000 - 450,000

France

350,000 - 450,000

Sunflower

USA

15,000 - 22,000

Canada

15,000 - 22,000

Ukraine

55,000 - 65,000

Brazil

50,000 - 60,000

Australia

50,000 - 60,000

Germany

50,000 - 60,000

France

50,000 - 60,000

Canola (Rapeseed)

USA

500,000 - 800,000

Canada

500,000 - 800,000

Ukraine

350,000 - 450,000

Brazil

2,200,000 - 3,500,000

Australia

1,200,000 - 2,000,000

Germany

1,200,000 - 2,000,000

France

1,200,000 - 2,000,000

Sugarcane

USA

8,000 - 12,000

Canada

N/A

Ukraine

N/A

Brazil

100,000 - 140,000

Australia

100,000 - 140,000

Germany

N/A

France

N/A

Barley

USA

1,000,000 - 1,300,000

Canada

1,000,000 - 1,300,000

Ukraine

4,000,000 - 5,000,000

Brazil

3,500,000 - 4,500,000

Australia

2,500,000 - 3,200,000

Germany

4,000,000 - 5,000,000

France

4,000,000 - 5,000,000

Rice

USA

100,000 - 150,000

Canada

N/A

Ukraine

N/A

Brazil

400,000 - 600,000

Australia

250,000 - 370,000

Germany

N/A

France

N/A

Cotton

USA

45,000 - 55,000

Canada

N/A

Ukraine

N/A

Brazil

100,000 - 120,000

Australia

110,000 - 135,000

Germany

N/A

France

N/A

Sorghum

USA

40,000 - 60,000

Canada

40,000 - 60,000

Ukraine

100,000 - 150,000

Brazil

90,000 - 120,000

Australia

100,000 - 150,000

Germany

100,000 - 150,000

France

100,000 - 150,000

Sources:

Post-Season Analysis

More PrecisionAg use-cases

How to Start


By integrating these methods, GeoPard helps you achieve efficient and productive farming practices through precise seeding strategies.

Description: This incorporates imagery, topography, and .

: Ensure accuracy of past yield data.

Generate s: If yield data is missing for past seasons, use GeoPard to generate these maps. Only total or average yield is needed, with an accuracy of 90%.

Description: and any available data layers (e.g., imagery, topography, yield, soil).

Available also in

Purdue University, University of Illinois Extension, , , Department of Agriculture and Fisheries, North Dakota State University, , , , , , ,

After the season, run to calculate yield output and profit maps based on yield data. This will enable optimization of the VRS map for the next season.

Refer to the for visual examples and further insights.

Using GeoPard's advanced tools and methodologies, you can optimize your seeding strategies, improve crop yields, and ensure sustainable agricultural practices. To start, register free at

👨‍🌾
multi-layer approach
soil brightness
Clean and calibrate yield data
Synthetic Yield Map
Utilize customized formulas
Batch Analytics
FAO
Embrapa
Alberta Wheat Commission
Grains Research and Development Corporation
National Sunflower Association
Australian Oilseeds Federation
Canola Council of Canada
USDA
European Commission - Agriculture and Rural Development
statistical and trial analytics
GeoPard PrecisionAg use cases PDF
app.geopard.tech
Variable Rate Planting in the GeoPard Blog
Field Potential Maps
GeoPard's Automated Recommendation of Representative Years
GeoPard automatically selects imagery, nevertheless you can select other images on demand
Field Potential Zones utilized for VR Planting, automatically created based on multi-year imagery
An Example of VR Seeding map based on Electrical COnductivity, Topography, Yield and Satellite imagery data
An example of VR Seeding Soybean map based on Yield datasets