Drone Analytics & NDVI Reporting

Client Objective

Farmers and agronomists needed a way to turn raw drone imagery into consistent, calibrated crop health maps. The goal was to transform UAV datasets into actionable insights — from NDVI calculations to variable-rate prescriptions — without the manual processing bottlenecks that delayed decision-making.

Challenges

• → Calibration issues: Raw sensor data required manual correction and standardization
• → Overwhelming scale: Processing large geospatial datasets was time-consuming
• → Terrain complexity: Varied field conditions needed adaptive algorithms
• → Compatibility: Outputs needed to work with existing farm management systems

DAAF's Approach

We built an end-to-end pipeline that automates the entire workflow — from raw imagery upload to prescription generation. Our solution includes:

• → Index engine for reflectance correction and calibration
• → Smart clustering to identify zones based on vegetation health
• → Prescription builder that generates variable-rate recommendations

Solution Snapshot

Key functionalities of the developed module:

• → Upload raw imagery (multiple formats supported)
• → Compute vegetation indices (NDVI, NDRE, and custom indices)
• → Classify zones automatically using machine learning
• → Export prescriptions (ISO-XML, Shapefile, PDF formats)
• → Deliver interactive web maps for field scouting

Outcomes

Measurable benefits achieved:

• → Accelerated scouting: Maps ready in hours instead of days
• → Improved operational efficiency: Reduced manual processing by 80%
• → Reduced costs: Faster decision-making led to optimized input usage
• → Increased consistency: Standardized outputs across all fields

DAAF's module helped us go from drone flights to actionable maps in hours, not days. — One agronomist

User Experience (Flexible Section)

Key interaction features:

• → Dashboard: Overview of all processed fields and their status
• → Interactive viewer: Pan, zoom, and explore NDVI maps in real-time
• → Zone/prescription panel: Adjust thresholds and regenerate prescriptions
• → PDF reports: Downloadable summaries for field records

Security & Reliability (Flexible Section)

Safeguards implemented:

• → Data isolation: Each organization's data is completely segregated
• → Traceability: Full audit logs for all processing steps
• → Queue-based processing: Handles large uploads without timeouts
• → Parallel tiling/caching: Optimized for performance at scale

Delivery Timeline (Flexible Section)

Six-week project timeline:

• → Weeks 1-2: Sensor models, calibration pipeline, and index computation engine
• → Weeks 3-4: Zone classification, prescription builder, and export modules
• → Week 5: Interactive viewer, dashboard, and UI polish
• → Week 6: UAT, performance optimization, and documentation