FAA Part 107 Cohort Training | Day 2: Autonomous Mapping & NDVI Sensors

Target Audience: Veteran Cohort (Hillside Remediation & Agricultural Missions) Total Time: 4.5 Hours (2.5 hr morning theory, 2 hr ground station / GIS flight block)

I. Core Lecture Modules

Module 1: Autonomous Flight Planning & Ground Station Software (75 Mins)

  • Mission Planning Software: Utilizing tools like QGroundControl, DroneDeploy, or UgCS to program automated grid and corridor flight lines.
  • Overlap & Sidelap Parameters: Setting optimal camera triggers (typically 75-80% frontal overlap and 70-75% side overlap) to ensure seamless orthomosaic photogrammetry stitching.
  • Terrain Following: Crucial for hillside burn scar and sloping topography missions to maintain a consistent AGL altitude above ground level rather than flying a flat plane into a rising slope.
  • Fail-safes & RTH: Pre-programming Return-to-Home (RTH) altitudes, low-battery triggers, and lost-link behaviors before initiating autonomous execution.

Module 2: Multispectral Imaging & NDVI Telemetry (75 Mins)

  • The Electromagnetic Spectrum: Understanding how healthy vegetation absorbs Red light for photosynthesis and strongly reflects Near-Infrared (NIR) light.
  • NDVI Formula Mechanics: Calculating the Normalized Difference Vegetation Index using the formula: $NDVI = (NIR - Red) / (NIR + Red)$.
  • Interpreting Index Values:

    • 0.0 to 0.1: Bare soil, rock, or severe burn scars (high erosion risk).

    • 0.2 to 0.4: Sparse brush, stressed grasses, or early regeneration.

    • 0.5 to 0.9: Dense, healthy vegetation canopy and active agricultural crops.

  • Radiometric Calibration: Utilizing downwelling light sensors (DLS) and calibration reflectance panels prior to flight to account for changing cloud cover and sunlight angles.

Module 3: Watershed Prescription Generation & Seeding Payload Prep (45 Mins)

  • Data-to-Action Pipeline: Translating raw NDVI index layers into targeted variable-rate broadcast prescription maps for cover crops and native seed blends.
  • Payload Calibration: Calculating granular spreading rates (lbs/acre) based on spreader disk RPM, flight speed, and effective swath width.

II. End-of-Day Diagnostic Pretest

Question 1: Terrain Following in Sloping Terrain

You are planning an autonomous mapping grid over a steep, post-fire hillside with a 400-foot elevation gain across the survey area. Why is enabling terrain-following radar/DEM data critical for this mission?

A) It allows the drone to exceed the 400-foot AGL altitude ceiling safely.

B) It maintains a consistent height above ground level as the terrain rises, preventing the drone from unintentionally crashing into the slope or losing spatial overlap resolution. (Correct)

C) It automatically disables Remote ID requirements during automated flights.

Question 2: NDVI Index Interpretation

After processing a multispectral flight over a targeted watershed sector, your orthomosaic returns a consistent NDVI value of 0.08 across a steep embankment. How should this site be categorized?

A) Dense riparian canopy requiring no intervention.

B) Bare soil / high erosion risk zone requiring heavy root-stabilization seed blends. (Correct)

C) Mature agricultural crop ready for harvest.

Question 3: Photogrammetry Overlap

What is the primary operational purpose of configuring 75% frontal and 70% side overlap during automated mapping flights?

A) To conserve battery life by reducing the total number of waypoint turns.

B) To provide sufficient common tie-points between images for accurate photogrammetric orthomosaic stitching and 3D point cloud generation. (Correct)

C) To satisfy FAA visual line of sight requirements through digital imagery.

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