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Week 05 3D Grid Mapping

Lab Report — Mavic 2 Pro Mapping Mission

Team: Kenzie Florkiewicz (PIC), Ryan Pirro Date of Mission: September 22, 2025

1) Introduction

This exercise evaluated a parallel, “lawn-mower” grid mapping workflow on the DJI Mavic 2 Pro using a no-subscription flight app. The goal was to acquire nadir imagery suitable for orthomosaic generation while documenting the end-to-end process—planning, execution, and metadata capture—so we could compare the experience against prior work with the Skydio S2. The mission was planned at 60 m AGL with 80% forward and 80% lateral overlap and the camera held at a true 90° nadir, allowing us to assess coverage efficiency, image quality, and how the app integrates with Mavic 2 Pro camera and flight controls.

2) Study Area

The survey covered the larger, red-outlined block at the Purdue Student Garden—the same footprint previously flown with the Skydio S2—to maintain a consistent baseline for comparison. The site comprises mixed grass and paved surfaces with broad, open sightlines; beyond the target polygon, a tree line and several light towers define the perimeter. On arrival, ambient conditions were favorable for mapping: temperature approximately 78 °F, visibility near 4 mi, winds around 7 mph with 9 mph gusts, and a moderate UV index. GNSS availability was strong (21 satellites observed during preflight). While local hazards were limited within the polygon, we noted potential airspace sensitivities associated with the nearby stadium environment and confirmed that our selected block remained clear of event-driven TFR-like constraints at the time of flight. The operation was conducted under an approved LAANC authorization from LAF with a 200-ft AGL ceiling; this ceiling aligned with our 60 m (≈200 ft) flight plan.

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3) Methods

Mission planning focused on ensuring seamless offline capability, so we pre-downloaded the basemap tiles and cached the mission polygon on the mobile device prior to departing for the field. In the app, we defined the survey rectangle to fully encompass the assigned area and set a regular, back-and-forth flight path with 80% forward and 80% side overlap. The camera was fixed at a 90° nadir to optimize ground sampling and avoid parallax artifacts unsuitable for 2D products. Takeoff, initial climb, and transition to the first leg were performed under manual supervision before handing over to the app’s autonomous leg-to-leg navigation. The Mavic 2 Pro’s exposure remained locked once the histogram indicated mid-tones were adequately centered, minimizing brightness drift across the image set. Throughout the sortie, we monitored battery, link quality, and wind warnings; none exceeded conservative thresholds. The full mission completed on a single battery in under ten minutes, after which we landed, reviewed image thumbnails on-device, and archived the original files to our field storage.

4) Data Collection Outcomes & Metadata

The mapping run executed as planned with uniform track spacing and consistent footprint overlap. Image EXIF records preserved key metadata (timestamp, GPS coordinates, altitude, focal length, exposure), and the app’s mission report captured the programmed parameters and final coverage polygon. Immediately post-flight, we spot-checked the sequence to confirm there were no dropped captures on turns and that ground texture remained sharp across the frame.

Operational summary (fill in exact counts post-offload):

Drive & setup time was approximately ten minutes from staging to wheels-up.

Flight time was about ten minutes, completed on one battery.

Number of images captured: [insert count].

Typical image size: [insert MB per image]; total dataset size: [insert total MB/GB].

LAANC authorization ID and details were recorded with the mission log for traceability.

These data are ready for orthomosaic processing and basic GIS analysis (e.g., footprint mapping, condition notes). The consistent nadir angle and high overlap should support robust aerotriangulation with minimal need for manual tie-point intervention. Should we elect to compare to the previous Skydio S2 run, the identical footprint will allow direct evaluation of flight-time efficiency, overlap adherence, and image sharpness across platforms.

5) Notes & Observations

The free app’s workflow was straightforward: polygon definition, altitude/overlap entry, camera-nadir lock, and autonomous execution. Leg transitions were smooth with predictable turn radii, and the capture cadence matched the programmed overlap at 60 m AGL without buffering stalls. Compared to earlier Skydio S2 mapping, the Mavic 2 Pro provided slightly crisper nadir imagery in bright conditions due to its larger sensor and lens characteristics, while the app’s lack of a subscription did not impede the essentials of grid-based mapping. Battery management was trivial for this footprint, and RF link remained solid across the area. The only caution for future flights is to double-check stadium-related airspace advisories on event days; otherwise, the garden block is well-suited for training sorties.

6) Data Management & Archiving

Immediately after landing, we verified image continuity and exposure consistency, then copied the dataset to our designated field drive and mirrored it to secondary storage. The full image set, mission log, and LAANC approval screenshot were organized under a dated folder structure: /M2P_StudentGarden_2025-09-22/RAW, /LOGS, and /AUTH. Each file retains original filenames to preserve capture order, and a sidecar text file documents flight parameters (altitude, overlap, nadir, battery used) for future processing notes.

7) Conclusion

This mission achieved its objectives: collect high-overlap nadir imagery at 60 m AGL over the assigned garden block; document workflow and metadata using a no-subscription app; and establish a like-for-like comparison against a prior Skydio S2 mapping of the same area. The dataset is complete, quality-checked, and ready for ingestion into photogrammetry software to produce an orthomosaic and ancillary GIS products. Future iterations might test lower or higher altitudes to study GSD trade-offs, introduce cross-grid or diagonal passes to further densify tie points, and schedule flights under differing sun angles to evaluate shadow impacts on texture matching.

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