Video Tutorials
Watch these step-by-step tutorial videos to learn how to use PowerZoner. The videos are organized in the recommended viewing order, from basic setup through advanced features.
Overview
PowerZoner is the most advanced satellite-based management zone creation tool available today. It analyzes multi-year crop performance patterns using NDVI (Normalized Difference Vegetation Index) data from Copernicus Sentinel-2 satellites, with unique features including peak seasonal NDVI per pixel (capturing maximum crop vigor during the growing season) and optional topography-based zone refinement to identify moisture-limited areas.
NDVI measures plant health and vigor using satellite imagery. Healthy, dense vegetation reflects more near-infrared light and less visible red light, resulting in higher NDVI values (-1 to +1 scale, where higher values indicate healthier vegetation). By analyzing NDVI patterns across multiple years, PowerZoner identifies consistent productivity zones in your fields.
PowerZoner converts raw NDVI data (-1 to +1 scale) into CPI (Crop Productivity Index) during composite creation. Each year's NDVI is normalized around its mean and set to 100, then years are averaged together. The resulting CPI values are mean-centered around 100, where values above 100 indicate areas of consistently higher-than-average crop productivity, and values below 100 indicate lower-than-average productivity. Each management zone is defined by its CPI range, allowing you to apply variable rate inputs based on actual historical crop performance.
Typical Workflow
- Setup Tab: Define field boundary, fetch satellite NDVI data (2015-present), and preview & select years for composite
- Zone Tab: Adjust zone parameters and compute management zones (automatically creates multi-year composite and classifies into zones)
- Topo Tab (Optional): Split low-productivity zones by wetness to identify moisture-limited areas (unique feature combining satellite + topography)
- Export Tab: Download shapefiles with CPI values for variable rate applications
About & Limitations
Important Disclaimer
PowerZoner is a data visualization and zone delineation tool only. It processes satellite NDVI data and topographic information "as-is" to create management zone maps based on historical crop performance patterns. PowerZoner does not provide agronomic advice, recommendations, or guarantees about crop production outcomes.
PowerZoner is NOT a replacement for professional agronomic consultation. Zone maps should be interpreted by qualified agronomists, crop consultants, or agricultural professionals who understand local soil conditions, crop requirements, and management practices. Always consult with agronomic experts before making management decisions based on PowerZoner zones.
Data Quality & Zone Reliability
The quality of your zones depends entirely on the quality of years you select:
- Including problematic years (split crops, mechanical failures, extreme weather events) will create zones that reflect those specific conditions, not typical field performance
- Selecting too few years (1-2 years) may capture single-year anomalies rather than persistent patterns
- Using years with suspect data (cloud contamination, crop rotation, significant management changes) will produce unreliable zones
Always preview years individually and exclude any that show anomalous patterns. Zones are only as reliable as the data you provide.
Boundary Accuracy is Critical
PowerZoner analyzes all vegetation within your boundary, not just crops. Satellite imagery accurately measures vegetation health and density, but it cannot distinguish between crops and other vegetation types. Non-cultivated areas with dense vegetation will appear as "high productivity" zones even though they produce no crop yield.
Exclude These Non-Cultivated Areas from Your Boundary:
- Wetlands and Sloughs: Dense cattails, reeds, and marsh vegetation will register as very high NDVI (falsely appearing as top-performing crop areas)
- Bush and Shelterbelts: Trees and shrubs have high NDVI throughout the growing season and will distort zone boundaries
- Grassed Waterways: Permanent grass cover appears as moderate-to-high NDVI and does not represent crop performance
- Fence Rows and Field Margins: Weeds, volunteer vegetation, and perennial plants along edges will skew productivity analysis
- Abandoned or Fallow Areas: Unmanaged vegetation creates false "high productivity" signals
Best Practice: Draw your boundary to include ONLY the actively cultivated crop area. If your field has internal wetlands, sloughs, or bush patches, either exclude them when drawing the boundary or manually edit the boundary shapefile to create "donut holes" (interior exclusion zones). Remember: the satellite imagery doesn't lie—it accurately shows vegetation—but it also doesn't know what is crop and what is other vegetation.
Topographic Wetness Limitations
The Refined Zones feature uses topographic wetness analysis to identify moisture-limited areas. This analysis has inherent limitations:
- Surface topography only: Cannot detect subsurface features (tile drainage, compaction layers, hardpan, restrictive horizons)
- Static analysis: Assumes consistent topographic influence across all years and weather conditions
- Resolution limits: LiDAR resolution (~3 feet) may miss micro-topographic features or very small drainage issues
- Wetness ≠ productivity: Topographic wetness indicates where water accumulates, not necessarily where crops perform poorly (some crops tolerate wet conditions)
Licensing & Usage Terms
Copyright & Ownership
PowerZoner is a copyrighted product developed by Simon Knutson and is exclusively available via GIS4AG (gis4ag.com).
Owned and provided exclusively by:
17449275 Canada Inc.
Box 599
St. Claude, MB R0G 1Z0
Canada
License Structure & Commercial Use
Commercial use of PowerZoner is permitted and encouraged. PowerZoner is designed for professional agronomists, crop consultants, precision agriculture specialists, and farming operations. The following licensing structure ensures fair use while supporting professional consulting services.
Individual Users & Small Operations
Each user or business unit requires their own license and unique login credentials. Small operations operating from a single location may share one license among staff working as a cohesive unit.
Partnerships, Consulting Teams & Multi-User Businesses
Each agronomist, crop consultant, or professional who independently manages their own client portfolio requires their own individual license. Lead agronomists may share their license with their direct support staff (assistants, technicians, data managers), but a single license cannot be shared between multiple lead agronomists or consultants who each manage separate client relationships.
This ensures each professional has full access to PowerZoner's features for their client work, while allowing reasonable sharing with support team members who assist with data preparation and analysis.
License Compliance Examples
✓ Acceptable Use Cases:
- One agronomist shares license with their assistant who prepares zone maps
- Small 3-person consulting office operating from one location shares one license
- Lead consultant shares access with GIS technician and field data collector
- Individual farmer uses PowerZoner for their own operation and shares with farm manager
✗ Not Permitted:
- Two independent agronomists in a partnership sharing one license
- Regional consulting team with 4 lead agronomists sharing one license
- Multi-location business with separate client portfolios per location using one license
- Reselling or sublicensing PowerZoner access to other consultants or businesses
Output Sharing & Client Services
Zone maps, shapefiles, and analysis outputs created with PowerZoner may be freely shared with clients as part of professional consulting services. There are no restrictions on distributing PowerZoner-generated zone maps to your clients for use in their precision agriculture operations.
Prohibited Activities
Unauthorized reproduction, redistribution, or sublicensing of PowerZoner software is strictly prohibited.
- Sharing login credentials with individuals who should have their own license
- Reverse engineering, decompiling, or modifying the PowerZoner software
- Circumventing authentication, usage tracking, or licensing controls
- Creating derivative works based on PowerZoner's proprietary algorithms or code
Volume Licensing & Inquiries
For larger organizations, multi-user teams, or volume licensing inquiries, contact GIS4AG for customized pricing and license packages. Volume discounts are available for organizations with multiple agronomists or consulting teams.
Contact for Licensing:
gis4ag.com
Email: simon@gis4ag.com
Setup Tab: Boundary, Data Fetch & Year Selection
Step 1: Define Field Boundary
Three methods to define your field boundary:
Import Shapefile
Click , select your boundary file, and it will be loaded automatically.
Draw Boundary
Click , click points around your field perimeter, and double-click to finish.
Use Saved Project
If you have a saved PowerZoner project, boundaries are included in the project file.
Maximum boundary size is 1500 acres. Boundaries larger than this will be rejected to protect API usage limits. If you need to analyze a larger area, please divide it into multiple fields of 1500 acres or less.
Step 2: Fetch NDVI Data
Once your boundary is loaded, click to retrieve Sentinel-2 satellite imagery for your field.
• Source: Copernicus Sentinel-2 satellites (10m resolution)
• Period: Peak growing season (June-August) for each year
• Years Available: 2015-present
• Metric: Maximum NDVI value during the season (captures peak crop vigor)
• Processing: Cloud-masked, quality-filtered data
Step 3: Preview & Select Years
After data fetch completes, you can preview and select which years to include in your multi-year composite. Click the eye icon next to any year to preview it on the map. Use the checkboxes to select which years to include in the composite.
✓ Good Years to Include:
• Consistent NDVI patterns across the field (smooth green-to-orange gradients)
• Similar spatial patterns between years
• Representative of typical crop performance
✗ Problematic Years to Exclude:
• Split Crops: Two distinct shades of green indicating different crops/varieties planted in the same field
• Mechanical Issues: Straight-line features of red, dark green, or light green (planter/sprayer skips, compaction tracks, tile blowouts)
• Extreme Weather: Significantly different NDVI patterns from other years due to severe drought or excessive wetness
• Crop Rotation: Lower overall NDVI if a different crop type was grown (e.g., soybeans vs. corn)
• Crop Failure: Large areas of red or very low NDVI due to disease, pest damage, or germination failure
Selecting Years for Composite
Use the checkboxes next to each year to select which years to include in the multi-year composite. The composite combines NDVI data from your selected years to identify persistent productivity patterns, removing single-year variability caused by weather, pests, or management differences.
Rainfall Indicator
Each year displays a rainfall indicator icon showing May-July growing season precipitation relative to the 20-year average for that location. This helps you understand whether year-to-year NDVI differences are due to inherent soil/productivity patterns (persistent across years) or weather-driven variability (specific to wet/dry years).
• Dry: Below average precipitation (bottom 33% of 20-year distribution)
• Normal: Near-average precipitation (middle 33%)
• Wet: Above average precipitation (top 33%)
Data Source: NOAA Climate Data (GHCN-Daily network)
Period: May-July growing season total precipitation
Baseline: 20-year rolling average centered on the year being classified
How to Use Rainfall Indicators
If a year shows significantly different NDVI patterns from other years, check its rainfall indicator:
- Dry year + low overall NDVI: Drought stress - NDVI reflects water availability, not inherent soil quality
- Wet year + low overall NDVI: Waterlogging/disease - excessive moisture reduced crop performance
- Normal year: NDVI more accurately reflects inherent soil/drainage differences
Recommended: Include 3-5 years with a mix of Normal and slightly Dry/Wet years to capture field variability under different moisture conditions.
Consider Excluding:
- Extreme Dry Years: If NDVI patterns look dramatically different from other years (uniform low NDVI = drought stress masking soil differences)
- Extreme Wet Years: If field shows widespread ponding or disease patterns not representative of typical years
- Single Outlier Years: If one year stands out visually as inconsistent with the majority pattern (check rainfall indicator for confirmation)
Composite Method
Maximum Composite (automatic): PowerZoner uses maximum composite by default, which takes the highest NDVI value at each location across all selected years. This represents the field's maximum productivity potential and is least affected by temporary issues.
Maximum NDVI shows where the field CAN perform well under good conditions. Areas that consistently show high NDVI have better soil, drainage, or topography. Areas that never achieve high NDVI may have fundamental limitations requiring different management.
Next Step: After selecting your years, proceed to the Zone Tab to create management zones from the composite data.
Zone Tab: Classification & Management
Convert the composite NDVI into discrete management zones with adjustable boundaries and statistics.
Zone Parameters
Choose how many management zones to create. Start with 3-5 zones for most fields. More zones = finer management but more complexity.
• Jenks Natural Breaks (recommended): Maximizes differences between zones - finds natural clustering in data
• Equal Count (Quantiles): Equal acreage per zone - ensures balanced zone sizes
• Equal Interval: Equal CPI range per zone - good for evenly distributed NDVI
• Standard Deviation: Highlights statistical outliers - identifies extreme high/low areas
Controls the minimum size of each zone part (a "blob"). Individual zone blobs smaller than this threshold will be merged into surrounding zones. Helps eliminate small scattered patches and creates cleaner, more contiguous management zones.
Smoothing reduces smaller zone inclusions and blends subtle variability. Higher values create simpler, more uniform zones but may lose important field detail. Low values (0-2) are recommended to preserve productivity variation patterns in 10m satellite data.
Compute Management Zones
After selecting your years in the Setup Tab and adjusting zone parameters, click . This automatically creates the multi-year composite from your selected years and classifies it into management zones. Zones appear on the map with traffic-light colors (red = low CPI, yellow = medium, green = high).
Zone Statistics
After zones are created, statistics show for each zone:
- Zone Name: Zone 1, Zone 2, etc.
- CPI Range: Minimum and maximum Crop Productivity Index values
- Acres: Zone area calculated from boundary geometry
- Color Swatch: Visual indicator matching map colors
Manual Break Adjustment
After creating zones, each zone row displays an interactive slider below the statistics that allows you to fine-tune the CPI boundary between that zone and the next higher zone. This powerful feature lets you override the automatic classification to match your field knowledge and management goals.
• Each slider controls the upper boundary (maximum CPI value) for that zone
• Drag the slider left to expand the zone (include more lower-CPI pixels)
• Drag the slider right to contract the zone (exclude lower-CPI pixels)
• The zone automatically reclassifies after 1 second (debounced live update)
• The slider's colored fill shows the current boundary position
• Constraints: You cannot move a slider below the previous zone's max or above the next zone's min
Zone Merging (Advanced)
Simplify your management by combining similar zones. Click to enter merge mode.
Enter Merge Mode
Checkboxes appear next to each zone. Select 2 or more zones to merge.
Confirm Merge
Click "Merge Selected Zones". A dialog shows which zones will be merged and asks for confirmation.
Merged Result
Selected zones are combined into the lowest-numbered zone. All pixels are reassigned. Zone colors and statistics recalculate automatically.
Undo (10 seconds)
A success banner appears at the top with an Undo button. You have 10 seconds to undo the merge if you made a mistake.
Rename Zones
Customize zone IDs and add descriptive labels for shapefile export by clicking .
Zone Description (optional): Add a text label up to 50 characters (e.g., "High Productivity Area", "Wet Depression - Needs Drainage"). This description appears in the shapefile's ZONE_LABEL attribute.
Click Save Changes to apply custom IDs/labels. Custom values will be used when exporting shapefiles. Click Reset to Default to restore original zone numbering.
Topo Tab: Wetness Analysis & Zone Refinement
The Topo Tab enhances your management zones by incorporating topographic wetness data to identify moisture-related limiting factors within low-productivity areas. This advanced analysis helps differentiate between areas limited by excess moisture (drainage issues) versus areas limited by insufficient moisture (dry hilltops, erosion), enabling more targeted management strategies.
Topography Data Fetching
Before performing wetness analysis, PowerZoner needs elevation data for your field. You can use one of two methods:
Method 1: Automatic LiDAR Fetch (Recommended)
- Select Region: Choose either US (3DEP data source) or Canada (HRDEM data source)
CRITICAL: Select the correct region for your field location. Choosing the wrong data source will result in failed LiDAR fetch or invalid elevation data, preventing topographic wetness analysis. Always select the region that matches your field's geographic location.
- Fetch & Process LiDAR: Click to automatically:
- Fetch high-resolution elevation data from public LiDAR sources
- Upload elevation data to TauDEM server for terrain analysis
- Calculate Topographic Wetness Index (TWI) using D∞ flow analysis
- Download and display wetness layer on map
Method 2: Upload Elevation Point Shapefile
If you already have elevation data from field surveys or other sources, you can upload it directly:
- Prepare Your Shapefile:
- Must be a point shapefile (not polygons or lines)
- Must have an elevation column (field name must be
elevation,z,elev, orheight- case-insensitive) - Points should be distributed throughout your field for best accuracy
- Recommended: Points collected at a minimum of 60ft swaths for reliable TWI calculation
- Package as a ZIP file containing .shp, .shx, .dbf, and .prj files
- Upload: Click and select your ZIP file
- Processing: PowerZoner will:
- Validate the shapefile format and elevation field
- Interpolate your point data to create a continuous elevation surface
- Upload to TauDEM server for terrain analysis
- Calculate Topographic Wetness Index (TWI) using D∞ flow analysis
- Download and display wetness layer on map
• Must be point geometry (not polygons/lines)
• Must have elevation column (field name:
elevation, z, elev, or height)• Elevation values must be numeric (no text or null values)
• Points should cover the entire field area
• All files must be included: .shp, .shx, .dbf, .prj (zipped together)
Wetness-Productivity Correlation Analysis
After fetching topography data, use the button to understand the relationship between topographic wetness and crop productivity in your field. This analysis reveals whether moisture patterns explain productivity differences, and recommends whether to use Standard or Refined zones.
Understanding the Scatter Plot
The correlation analysis displays an interactive scatter plot showing the relationship between wetness (X-axis) and crop productivity (Y-axis):
• Green dots: Individual pixels from your field (each dot = 1 pixel location)
• Red line: Best-fit trendline (linear or cubic model)
• X-axis (Wetness Index): Topographic wetness values (0-99 scale, higher = wetter)
• Y-axis (CPI): Crop Productivity Index (mean-centered around 100)
• R² value: Goodness of fit (0.0 = no relationship, 1.0 = perfect relationship)
How It Works
PowerZoner compares each pixel's wetness index value (from topography) with its NDVI composite value (from satellite data), then fits two mathematical models:
- Linear Model: Simple straight-line relationship (y = mx + b) - captures simple positive or negative trends
- Cubic Model: Complex curved relationship (y = ax³ + bx² + cx + d) - captures S-curves, inverted-U patterns, and asymmetric peaks
The model with the highest R² is selected as the best fit and displayed as the red trendline.
Linear vs Cubic Models: What's the Difference?
Linear Model Selected:
• Scatter plot shows a clear diagonal trend (upward or downward slope)
• Productivity increases OR decreases steadily as wetness increases
• Red trendline appears as a straight diagonal line
• Example: Wetter areas consistently have higher (or lower) productivity across entire wetness range
Cubic Model Selected:
• Scatter plot shows curved patterns (U-shapes, inverted-U, S-curves)
• Productivity relationship changes across wetness range (e.g., beneficial at low wetness, harmful at high wetness)
• Red trendline appears as a smooth curve with peaks or valleys
• Example: Moderate wetness = high CPI, but BOTH very dry AND very wet = low CPI
Common Correlation Patterns
1. Inverted-U Pattern (Most Common)
• Scatter plot forms an upside-down U shape
• Low wetness (dry areas): Low CPI
• Moderate wetness: High CPI (peak of curve)
• High wetness (wet areas): Low CPI drops again
• Cubic model selected with R² typically 0.10-0.30
What It Means:
BOTH dry AND wet areas have low productivity, but for opposite reasons:
- Dry areas (low wetness): Water-limited productivity (hilltops, ridges, erosion)
- Wet areas (high wetness): Drainage-limited productivity (depressions, poor drainage, compaction)
- Moderate areas: Optimal moisture = highest productivity
2. Wet-Only Impact Pattern
• Scatter plot shows flat line at high CPI for low-to-moderate wetness
• Sharp CPI drop only at high wetness values (right side of plot)
• Cubic model selected with relatively low R² (0.10-0.25)
What It Means:
Only wet areas have productivity issues - dry areas perform just as well as moderate areas:
- Low-to-moderate wetness: Consistent high productivity (no water limitation)
- High wetness only: Strong CPI drop (drainage is the sole limiting factor)
3. No Meaningful Pattern
• Scatter plot looks like a random cloud of points
• No clear trend or curve visible
• Linear R² < 0.2 and cubic R² not much better
• Red trendline appears nearly flat
What It Means:
Topographic wetness does NOT explain productivity patterns in your field. Limiting factors are likely:
- Soil texture or fertility differences (clay pockets, sandy areas)
- Historical management patterns (manure application, past tillage)
- Soil chemistry issues (pH, salinity, sodicity)
- Subsurface features not visible in topography (compaction layers, hardpan)
Automated Recommendation System
After analysis, PowerZoner provides a detailed automated recommendation with specific rationale based on your field's scatter plot pattern:
1. Read the scatter plot description - Understand which wetness-productivity pattern was detected
2. Review the rationale box - See why Standard or Refined zones are recommended
3. Visually confirm the pattern - Look at the scatter plot yourself to verify the automated detection
4. Follow the recommended workflow - Proceed with Standard or Refined zones as suggested
Note: The recommendation is based on statistical analysis and common patterns, but you can always override it. If you see clear wet/dry clusters in the scatter plot even with low R², Refined zones may still be valuable for your specific management goals.
Creating Refined Zones
If the correlation analysis recommends Refined Zones (or if you want to explore wet/dry patterns), click . This process:
- Identifies all pixels in the lowest productivity zone (Zone 1)
- Splits Zone 1 into three categories based on wetness percentiles:
- Dry (Low-Dry): Wetness < 40th percentile
- Other (Low-Other): Wetness between 40th and 60th percentile
- Wet (Low-Wet): Wetness > 60th percentile
- Applies blob-based majority classification (50% threshold) to maintain spatial coherence
- Applies spatial smoothing and minimum zone size filtering
- Renumbers zones: Zone 11 (Other), Zone 12 (Dry), Zone 13 (Wet), Zone 2+ (original high-productivity zones)
Wetness Classification Thresholds
Fine-tune how low-productivity areas are classified into Dry, Wet, and Other zones by adjusting two percentile threshold sliders:
Pixels with wetness values below this percentile are classified as Zone 12 (Low-Dry) - shown in brown. These are typically hilltops, ridges, or eroded areas with poor water retention.
Pixels with wetness values above this percentile are classified as Zone 13 (Low-Wet) - shown in blue. These are typically depressions, poorly drained areas, or zones with ponding issues.
Pixels with moderate wetness (between Dry and Wet thresholds) are classified as Zone 11 (Low-Other) - shown in red. These areas have low productivity for reasons OTHER than moisture (e.g., fertility, salinity, pH, compaction).
Spatial Smoothing & Filtering
Refined zones can be spatially smoothed and filtered to remove noise and create cleaner management zones:
- Spatial Smoothing (0-5 passes): Each pass applies a majority filter to remove isolated pixels and create cleaner zone boundaries. Default is 3 passes (standard). Higher values create simpler zones but may over-generalize. Use Light (1 pass) for high-detail zones or Strong (4-5 passes) for very simplified zones.
- Minimum Zone Size (0-5 acres): Small isolated zones below this threshold are merged into surrounding zones. Default is 0.5 acres. Prevents tiny fragments that are impractical to manage separately.
Refined Zone Numbering
• Zone 11 (Low-Other): Red - Low productivity, moderate wetness. Limiting factor likely non-moisture (fertility, pH, salinity, compaction)
• Zone 12 (Low-Dry): Brown - Low productivity, dry areas. Limiting factor likely moisture deficiency (hilltops, erosion, poor water retention)
• Zone 13 (Low-Wet): Blue - Low productivity, wet areas. Limiting factor likely excess moisture (poor drainage, compaction, waterlogging)
• Zone 2, 3, 4, 5+: Orange → Green gradient - Standard productivity zones (Low-Medium to High)
Interpreting Refined Zones
Zone 12 (Low-Dry) - Brown
Areas with low productivity AND low wetness values. These areas typically:
- Located on hilltops, ridges, or elevated areas
- Experience faster water runoff and lower water retention
- May have shallower topsoil or erosion issues
- Often have lower organic matter content
Zone 13 (Low-Wet) - Blue
Areas with low productivity AND high wetness values. These areas typically:
- Located in depressions, low spots, or areas with flow accumulation
- Experience slower water infiltration or drainage
- May have soil compaction or poor soil structure
- Prone to ponding, waterlogging, or extended saturation
Zone 11 (Low-Other) - Red
Areas with low productivity but moderate wetness values (neither consistently dry nor consistently wet). These areas typically:
- Have limiting factors unrelated to moisture patterns
- May have soil fertility issues (N, P, K deficiencies)
- May have soil chemistry issues (pH, salinity, sodicity)
- May have physical limitations (compaction layers not reflected in surface topography)
- May have historical management differences (past tillage, manure application patterns)
Standard vs Refined Zones: Decision Guide
Use Standard Zones When:
- Wetness-productivity correlation is weak (R² < 0.2) and no strong cubic pattern
- You're focused on fertility/nutrient management
- Topography is relatively uniform across the field
- Moisture availability is not a primary limiting factor
Use Refined Zones When:
- Correlation analysis shows inverted-U or strong cubic pattern (even if R² appears low)
- Visual inspection of scatter plot reveals clear wet/dry productivity differences
- You want to identify areas needing different moisture management strategies
- Low-productivity areas show spatial clustering in topographic low/high spots
- You're planning drainage improvements or irrigation system design
Refined Zones Workflow
- Create Standard Zones in Zone Tab first
- Select Region (US or Canada) in Topo Tab
- Fetch & Process Topography (up to 1 minute)
- Analyze Wetness-Productivity Correlation to view relationship and recommendation
- Create Refined Zones if recommended or if you want to explore wet/dry patterns
- Review Zone Statistics to see acreage and NDVI for each zone type
- Export Shapefile in Export Tab (refined zones include zone type attributes)
3D Terrain Viewer (BETA)
PowerZoner includes an advanced 3D terrain visualization tool powered by Cesium.js that displays your field's topography and management zones in immersive 3D. This feature is especially valuable for understanding how zones relate to terrain features like hills, valleys, and drainage patterns.
Accessing the 3D Viewer
After fetching elevation data (via LiDAR or uploaded shapefile), a button appears in the bottom-right corner of the screen. Click this button to launch the full-screen 3D terrain viewer.
What You'll See
• Terrain Mesh: High-resolution 3D surface showing actual field topography (hills, valleys, slopes)
• Zone Overlay: Your management zones draped over the terrain as a semi-transparent color layer
• Exaggerated Relief: Elevation differences are visually enhanced (vertical exaggeration) to make subtle terrain features visible
• Interactive Navigation: Rotate, pan, and zoom to explore terrain from any angle
• Color Scheme:
- Standard Zones: Red (low productivity) → Yellow → Green (high productivity) traffic light scheme
- Refined Zones: Zone 12 (Brown/Dry), Zone 13 (Blue/Wet), Zone 11 (Red/Other), Zone 2+ (Orange→Green gradient)
Navigation Controls
• Left-click + drag: Rotate the view around the field
• Ctrl + hold left mouse: Rotate the view
• Right-click + drag (or two-finger drag): Pan the view left/right/up/down
• Scroll wheel (or pinch): Zoom in/out
• Double-click: Reset to default view
On-Screen Buttons:
• Close (X): Exit 3D viewer and return to 2D map
• Reset View: Return camera to default overhead angle
• Toggle Zones: Show/hide zone color overlay (terrain always visible)
Practical Uses
The 3D viewer helps you:
- Understand Zone Context: See how your productivity zones relate to field topography—whether low-productivity areas align with hills, valleys, or flat areas
- Identify Terrain Patterns: Visualize slopes, drainage channels, and elevation changes that may influence crop performance
- Communicate with Stakeholders: Present management zones in an intuitive, visually compelling 3D format that growers and clients can easily understand
- Plan Field Improvements: Use terrain visualization to identify areas needing drainage improvements, irrigation adjustments, or erosion control
- Validate Zone Boundaries: Verify that zone boundaries make sense given the field's actual topography and natural features
- Export Decision Support: Use 3D perspective to finalize zone adjustments before exporting to precision ag equipment
Export Tab: Shapefile & PDF
Export Shapefile
Click to download your management zones as a shapefile ZIP.
•
zone - Zone number (1, 2, 3, ...)•
zone_name - Zone name ("Zone 1", "Zone 2", ...)•
CPI_min - Minimum Crop Productivity Index•
CPI_max - Maximum Crop Productivity Index•
CPI_avg - Average CPI (midpoint)Coordinate System: WGS84 (EPSG:4326)
Compatible with: QGIS, ArcGIS, SMS, Climate FieldView, John Deere Operations Center, precision ag equipment
Export Map to PDF
Click to create a printable map showing your zones with a legend and Copernicus data attribution.
Prescription Generator: Variable Rate Applications
The Prescription Generator creates variable rate application (VRA) prescriptions from your PowerZoner management zones. Export shapefiles with product-specific rate columns that work directly with precision agriculture equipment, farm management software, and application controllers.
A variable rate application prescription is a digital map that tells your equipment how much product (seed, fertilizer, lime, etc.) to apply in each zone of your field. PowerZoner generates prescriptions as shapefiles with rate columns for 1-6 different products, allowing you to manage multiple inputs simultaneously.
Accessing the Prescription Generator
Click the purple Rx button located at the bottom center of the map (next to the User Manual and Soil Sampling buttons) to open the Prescription Generator.
Two Operating Modes
Mode A: Use Current Zones
Automatically uses the zones currently loaded in PowerZoner. Works with both standard CPI-based zones and topo-refined zones (Dry-Limited/Wet-Limited classifications). The prescription inherits all zone attributes including CPI values and custom zone names.
Best for: Creating prescriptions immediately after generating zones, or when you want prescriptions to match exactly what you see on the map.
Mode B: Import Shapefile
Import a previously exported PowerZoner zone shapefile (from Export Tab) and add prescription rate columns to it. This allows you to create prescriptions later without re-generating zones, or to share zone shapefiles with clients who can then create their own prescriptions.
Best for: Creating prescriptions from saved zone files, working offline, or when consultants provide zone shapefiles to clients.
Creating a Prescription: Step-by-Step
Open Prescription Generator
Click the Rx button at bottom center of map. The tool automatically detects if you have zones loaded (Mode A) or prompts you to import (Mode B).
Enter Field Name
Type a field name (max 20 characters). This will be used in the export filename: {FieldName}_rx.zip
Select Number of Products
Choose how many products you want to prescribe (1-6). Common examples:
- 1 product: Seed rate only
- 2 products: Seed + nitrogen
- 3 products: Seed + nitrogen + potash
- 4+ products: Complete fertilizer blend + micronutrients
Configure Product Names & Rates
For each product:
- Product Name: Enter a descriptive name (max 10 characters). Examples: "Seeds", "N_Rate", "P2O5", "Lime"
- Unit: Specify the unit (max 8 characters). Examples: "seeds/ac", "lbs/ac", "kg/ha", "gal/ac"
- Zone Rates: Enter the application rate for each zone. You'll see one input box per zone (Zone 1, Zone 2, etc.)
Export Prescription
Click Export Prescription. A shapefile ZIP will download: {FieldName}_rx.zip
Prescription Shapefile Attributes
•
zone_id - Zone number (1, 2, 3... or 11, 12, 13... for refined zones)•
zone_name - Zone name (e.g., "Zone 1" or custom name if renamed)•
zone_desc - Custom description (if you renamed zones)•
CPI_min - Minimum CPI value in zone (historical productivity)•
CPI_max - Maximum CPI value in zone•
CPI_avg - Average CPI value in zoneProduct Rate Columns:
• One column per product with sanitized name (e.g., "Seed_Rate", "N_Rate")
• Values are decimal rates rounded to 2 decimal places
• Example: If you enter "Seed Rate" as product name, column will be "Seed_Rate"
Geometry Type: MultiPolygon (dissolved by zone_id)
File Format: Shapefile (.shp, .shx, .dbf, .prj) in ZIP container
Using Prescriptions with Precision Ag Equipment
PowerZoner prescription shapefiles are compatible with most precision agriculture equipment and farm management software platforms, including:
- John Deere Operations Center
- Climate FieldView
- AgLeader SMS
- Trimble Ag Software
- Raven Slingshot
- QGIS/ArcGIS (for review, custom mapping, or format conversion)
Agronomic Consultation Required
PowerZoner provides zone delineation and prescription export tools ONLY.
PowerZoner does NOT provide rate recommendations or agronomic advice. Application rates must be determined by certified agronomists, crop consultants, or agricultural professionals based on soil tests, yield goals, crop requirements, and local conditions. Never apply rates without proper agronomic evaluation. Incorrect rates can reduce yield, waste inputs, cause environmental harm, or violate regulations.
Import Mode: Using Previous Zone Shapefiles
If you previously exported zones from PowerZoner (or received a zone shapefile from a consultant), you can create prescriptions without re-generating zones:
Open Prescription Generator
Click Rx button, then select "Import Shapefile" mode at the top of the popup.
Upload Zone Shapefile
Click the "Click to import shapefile" box or drag-and-drop your previously exported zone shapefile ZIP (e.g., Field1_zones.zip).
Verify Zone Detection
The tool automatically detects zone IDs from the shapefile (zone_id or zone field) and displays: "✓ Loaded 3 zones"
Configure & Export
Enter field name, select number of products, configure rates, and export. The prescription will include all original zone attributes plus your new rate columns.
Example: Creating a Two-Product Prescription
Technical Workflow Example
Scenario: Creating a prescription for 2 products across a 3-zone field
Step 1: Create zones in PowerZoner (Setup → Zone Tab → Compute Management Zones)
Step 2: Consult with your agronomist to determine appropriate application rates for each zone based on soil tests, yield goals, and crop requirements
Step 3: Open Prescription Generator (Rx button)
Step 4: Configure prescription:
- Field Name: "Field_5_North"
- Number of Products: 2
- Product 1: Name = "Seeds", Unit = "seeds/ac"
- Product 2: Name = "Nitrogen", Unit = "lbs/ac"
- Enter rates for each zone (Zone 1, Zone 2, Zone 3) as determined by your agronomist
Step 5: Click "Export Prescription"
Result: Field_5_North_rx.zip with columns: zone_id, zone_name, CPI_min, CPI_max, CPI_avg, Seeds, Nitrogen
Common Issues & Solutions
Solution: The Rx button requires zones to be loaded. Make sure you've created zones (Zone Tab → Compute Management Zones) or switch to Import Mode to upload a zone shapefile.
Solution: The shapefile must have a
zone_id or zone field with numeric zone numbers (1, 2, 3...). PowerZoner zone exports automatically include this field. If using a shapefile from another source, add a zone_id column in QGIS or ArcGIS before importing.
Solution: Ensure your equipment supports shapefiles and WGS84 coordinate system. Some older equipment requires specific formats - consult your equipment manual or dealer. You may need to convert the shapefile to a different format (e.g., .isoxml for ISOBUS equipment) using your farm management software.
Advanced: Multi-Product Prescriptions
PowerZoner supports up to 6 products in a single prescription, enabling complete fertilizer programs:
- Product 1: Seeds (seeds/ac)
- Product 2: Nitrogen (lbs/ac)
- Product 3: Phosphate (lbs P2O5/ac)
- Product 4: Potash (lbs K2O/ac)
- Product 5: Lime (tons/ac)
- Product 6: Zinc (lbs/ac)
The tool can handle any product type and unit. Consult with your agronomist to determine which products and rates are appropriate for your operation.
Understanding CPI Values
Crop Productivity Index (CPI) represents the NDVI-based productivity potential of each zone, normalized around a mean of 100.
PowerZoner creates a multi-year NDVI composite by normalizing each year around its mean productivity (100 = average for that year), then averaging across all selected years. This creates a relative productivity index where:
• CPI = 100: Field average productivity
• CPI > 100: Above-average productivity
• CPI < 100: Below-average productivity
• Above 100: Areas with consistently above-average crop vigor across multiple years. These zones typically have favorable soil conditions, topography, or drainage characteristics.
• Around 100: Near-average productivity areas representing the field baseline.
• Below 100: Zones with consistently below-average productivity. These areas may have limiting factors such as soil texture differences, drainage issues, topographic constraints, or nutrient deficiencies.
Tips & Best Practices
Data Selection
- Include 3-5 years of data for stable, reliable zones
- Exclude years with crop failures, different crops, or severe anomalies
- Mix wet and dry years to see consistent patterns
- Preview years before including them in the composite
Zone Creation
- Start with 3-5 zones for most fields (70-200 acres)
- Use "Quantiles" method for balanced zone sizes
- Set minimum zone size to 1-2 acres to avoid unmanageable slivers
- Apply 3-5 smoothing iterations for cleaner boundaries
- Toggle zones on/off to verify they align with NDVI patterns
Zone Refinement
- Adjust break sliders to align zones with field knowledge
- Merge zones if they have similar management needs
- Consider field access, equipment limitations, and operational efficiency
- Compare with topography, soil maps, and yield data if available
Implementation
- Export shapefiles with CPI attributes for variable rate maps
- Import zones into farm management software or precision ag platforms
- Create separate prescriptions for seeding, fertilizer, and other inputs
- Track performance by zone to refine management over time
- Re-run PowerZoner annually to update zones with new satellite data
Map Tools
Click the ruler icon in the bottom-left corner to access measurement tools:
Measure Distance: Draw a line to measure distances (switchable units: feet, meters, yards, miles, kilometers, inches)
Add Label: Click to place text annotations on the map
Clear Labels: Remove all annotations
GPS Geolocation
PowerZoner includes GPS tracking to help you navigate to specific areas of your field and verify zone boundaries on the ground. The geolocation button appears at the bottom-center of the map alongside other field tools.
Enabling GPS Tracking
Click the geolocation button to start tracking your position. Your browser will request permission to access your location.
GPS Display
Auto-Center: Map automatically centers on your location when first enabled
Active State: Button shows purple glow when tracking is active
High Accuracy: Uses high-precision GPS mode for field-level accuracy
Use Cases
- Zone Verification: Navigate to low-productivity zones to investigate causes (compaction, drainage issues, soil differences)
- Field Scouting: Track your position while walking through zones to collect observations
- Ground Truthing: Verify that zone boundaries align with visible field features (soil color changes, drainage patterns, topography)
- Mobile Navigation: Use on a tablet or smartphone while driving through the field to locate specific areas
- Sampling Coordination: Combine with soil sampling tool to navigate to sample points
Soil Sampling Tool
The soil sampling tool provides a complete workflow for generating stratified soil sample points within your management zones, exporting them for GPS navigation, and tracking sampling progress in the field.
Opening the Sampling Tool
Click the soil sampling button at the bottom-center of the map. A full-screen sampling interface opens with a control sidebar and an embedded satellite imagery map.
Step 1: Select Zones
Choose how to load zones for sampling:
Import Zone Shapefile: Upload a previously exported PowerZoner zone file
Step 2: Configure Sampling
Set the number of sample points you want in each zone:
- Use the Points per Zone slider (1-20 points, default is 3)
- Total points = (Points per zone) × (Number of zones)
- Example: 3 points per zone × 4 zones = 12 total sample points
Step 3: Generate Points
Click to create sample locations:
Minimum Spacing: 100-meter spacing between points prevents clustering
Boundary Validation: Points guaranteed to fall within field boundary
Smart Retry: If random placement fails, falls back to zone centroid
Generated points appear on the map as numbered markers color-coded by zone. The sidebar displays a complete list with Point ID, Zone ID, and coordinates.
Step 4: Edit Point Locations
Adjust point positions as needed:
- Drag Points: Click and drag any point marker to a new location on the map
- Click to Zoom: Click a point in the sidebar list to zoom the map to that location
- Delete Points: Remove individual points or clear all points to start over
Step 5: Export for Field Use
Save your sample points as KML files for GPS navigation:
Export for GPS Device: Optimized format for Garmin, Trimble, and handheld GPS units
KML files include:
- Point ID and zone assignment
- GPS coordinates (latitude/longitude)
- Visited status (unvisited or visited with timestamp)
- Color-coded markers (red = unvisited, green = visited)
Step 6: GPS Navigation in Field
Use GPS tracking to navigate to sample points:
- Import your KML file in the soil sampling tool (or use freshly generated points)
- Click
- Blue GPS marker appears showing your current location
- Sidebar displays distance to nearest unvisited point (updates in real-time)
- Navigate to point using distance indicator
- Collect soil sample at point location
- Check Visited box for that point (marker turns green, timestamp recorded)
- Repeat for all points
• Current location: Latitude, Longitude
• Nearest unvisited: "Point 5 (Zone 2) - 127m"
• Updates every 5 seconds for battery efficiency
• High accuracy mode enabled
Import Existing Sample Points
Load previously created sample points:
- Click Import Points (KML)
- Select a KML file exported from PowerZoner or another source
- Points are loaded onto the map and listed in the sidebar
- Visited status and timestamps are preserved if previously recorded
Complete Workflow Example
1. Create zones in PowerZoner (4 zones)
2. Open soil sampling tool
3. Set "Points per zone: 3"
4. Generate 12 points
5. Drag Point 7 to avoid drainage ditch
6. Export KML: soil_samples_2025.kml
Field Collection:
7. Open PowerZoner on mobile device
8. Import soil_samples_2025.kml
9. Enable GPS tracking
10. Navigate to Point 1 (distance: 45m → 12m → arrived)
11. Collect sample, mark visited
12. Repeat for Points 2-12
13. Export updated KML with timestamps
14. Submit to soil lab with zone information
Best Practices
- Stratified Sampling: PowerZoner automatically ensures points are distributed across all zones for representative sampling
- Composite Samples: Collect 3-5 sub-samples within 10 feet of each point location and combine into one bag
- Sampling Depth: Use consistent depth (typically 6-8 inches for cropland) at all points
- Zone Attribution: Label sample bags with Point ID and Zone ID for zone-specific fertility recommendations
- Weather Timing: Sample when soil moisture is consistent (avoid immediately after rain or during drought)
- Equipment: Use clean sampling tools to avoid cross-contamination between zones
- Documentation: Export final KML with visited status for record-keeping and future reference
Data Attribution
PowerZoner integrates multiple geospatial data sources to provide comprehensive crop productivity and terrain analysis capabilities.
• Resolution: 10 meter pixels
• Revisit Time: Every 5 days (two satellites)
• Bands Used: Red (665nm) and Near-Infrared (842nm) for NDVI calculation
• Processing: Cloud-masked, quality-filtered, atmospherically corrected
• License: Free and open data under Copernicus terms
• Attribution: Contains modified Copernicus Sentinel data (years displayed in footer)
• US (3DEP): USGS 3D Elevation Program - 1 meter resolution LiDAR
• Canada (HRDEM): High Resolution Digital Elevation Model - 1 meter resolution LiDAR
• Purpose: Topographic analysis for zone refinement and wetness correlation
• License: Public domain (US) / Open Government License (Canada)
• Imagery: ESRI World Imagery - High-resolution satellite imagery
• Labels: ESRI World Reference Overlay - Place names and boundaries
• Attribution: Source: Esri, Maxar, Earthstar Geographics, and the GIS User Community
• Source: Global Historical Climatology Network Daily
• Purpose: Seasonal rainfall indicators for zone interpretation
• License: Public domain