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Week 5 3D Grid Mapping

1. Introduction

This lab focused on planning and executing a parallel ‘lawn mower’ grid-based mapping mission using a DJI Mavic 2 Pro and the Flight App. The mission was conducted over the same general assigned area as the prior Skydio S2 mapping exercise, with this flight concentrating on the larger designated polygon within the Purdue Turf Farm. The primary objectives were to discover, identify, and implement methods for parallel grid mapping missions and strengthen understanding of metadata by completing a metadata form for the mission.

Planned parameters targeted a 60 m AGL flight altitude, 80% frontal and 80% lateral image overlap, and a 90° nadir camera orientation. This report summarizes mission planning, airspace and weather due diligence, field data collection practices, dataset management, and observed strengths and shortcomings of the Drone Deploy app workflow.

2. Study Area

The study area for this mission was the Purdue Turf Farm. The site consists primarily of managed turf and open green space with adjacent paved access routes, parking areas, and nearby buildings. The relatively uniform surface of the turf provides a clean test environment for evaluating grid coverage and overlap, while the presence of boundary features such as trees, light poles, and facility structures adds useful reference points for photogrammetric alignment.

Site access was straightforward with ample space to establish a safe takeoff/landing zone. Pedestrian traffic was minimal during the mission window, though occasional service vehicles and turf maintenance activity were possible. The terrain was largely flat and unobstructed within the core mapping polygon, supporting stable low-risk flight operations for a nadir mapping mission.

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Figure 1. DroneDeploy mission planning view showing the mapping polygon and parallel grid layout over Purdue Turf Farm.

3. Mission Planning

3.1 FAA Compliance and LAANC Pre-Check

Because the Purdue Turf Farm lies within controlled airspace in the Lafayette region, a LAANC pre-check was performed prior to field operations. The pre-check indicated that the location was eligible for auto-approval under the authorizing airport LAF in Class D airspace. The authorization request window shown in the app was Sep 23, 2025 from 12:50 PM to 2:50 PM EDT (2 hours). This step ensured that the planned operation remained compliant with applicable FAA rules for UAS operations in controlled airspace.

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Figure 2. LAANC Authorization Request pre-check showing auto-approval eligibility under LAF in Class D airspace.

3.2 Pre-Flight Weather Review

A pre-flight weather review was conducted using an aviation weather summary tool for the KLAF area. Conditions were reported as VFR with no warnings. Visibility was 10 miles with few clouds, and surface winds were light at approximately 4 knots from roughly 160°. The temperature was approximately 22.2°C. These conditions were considered favorable for mapping due to reduced turbulence and a lower risk of motion blur, supporting consistent image capture for high-overlap photogrammetry.

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Figure 3. Pre-flight weather summary for the KLAF area indicating VFR conditions and light winds.

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Figure 4. Detailed weather breakdown including winds, clouds, and temperature parameters used to support go/no-go decisions.

3.3 Mission Design in Drone Deploy

The mapping mission was created in the Drone Deploy Flight App using a parallel grid pattern. The polygon was drawn to cover only the required larger area within the assigned site. Key settings were reviewed to align with lab objectives: 60 m AGL altitude, 90° nadir camera orientation, and 80% frontal and lateral overlap.

During setup, the app’s Automatic Settings displayed 80% front overlap and 75% side overlap. This introduced a potential mismatch with the lab requirement of 80% lateral overlap. To address this, lateral overlap was confirmed and treated as a deliberate parameter requiring manual verification.

Obstacle Avoidance was enabled to provide an additional safety margin near trees and structures at the site boundaries. The mission area was also reviewed for offline availability on the mobile device per lab guidance.

4. Field Data Collection

In the field, the flight crew conducted a brief operational review, confirmed roles (Pilot in Command and Visual Observer), and verified that the mission parameters matched the lab’s required profile. The team established a clear takeoff and landing area with good visual access to the full polygon. Throughout the mission, the Visual Observer monitored for any changes in site activity, approaching vehicles, or pedestrians that could affect safety.

4.1 Potential Hazards and Mitigation

Potential hazards at the Purdue Turf Farm included: (1) intermittent ground vehicle or turf maintenance equipment movement along access roads, (2) trees, light poles, and facility structures near the perimeter of the mapping polygon, (3) possible wildlife or unexpected pedestrian entry into the operating area, (4) temporary GPS or connectivity variability, and (5) sun angle/glare changes that could affect image consistency.

Mitigation strategies employed were: establishing a clearly defined safety buffer around the takeoff/landing zone; maintaining continuous Pilot–Observer communication; pausing or aborting the mission if ground traffic entered the immediate area; keeping obstacle avoidance enabled; and conducting a deliberate parameter check of altitude and overlap settings prior to launch. These steps helped ensure safe operations while preserving the integrity of the mapping dataset.

5. Data Review and Storage

After mission completion, the collected images were reviewed for adequate coverage, sharpness, and exposure. No major gaps were observed in the grid pattern based on the in-app mission summary and preliminary image review. The dataset was then saved to a dedicated storage location and shared with the flight crew member to support future lab requirements.

Table 1 summarizes the required mission and dataset metrics recorded for this flight.

Table 5

Table 5

Metric

Recorded Value

Time to drive to the field and set up

30 minutes

Time to fly the mission

30 minutes

Number of images captured

105 images

Average size of each image

≈ 10.5 MB per image

Total dataset size

0.98 GB

There are no rows in this table

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The relationship between image count and average image size is consistent with the recorded total dataset size within expected rounding and file system reporting variation.

6. Data Collection Outcomes / Expected Deliverables

This mission produced a image dataset intended for photogrammetric processing to generate a 2D orthomosaic and related mapping products. The dataset will be used to evaluate grid coverage and the practical impact of overlap settings, and to compare workflow considerations with the earlier Skydio S2 assignment over the same broader area.

7. Drone Deploy App Process Documentation & Shortcomings

7.1 Process Summary

The Drone Deploy workflow for this lab followed a structured sequence: selecting the mission type, drawing the polygon over the required area, configuring altitude and overlap targets, verifying the camera orientation, enabling obstacle avoidance, checking offline map availability, connecting the Mavic 2 Pro, and executing the mission after final airspace and weather confirmation.

7.2 Observed Shortcomings

The most notable shortcoming encountered was the potential for mismatch between the lab’s overlap targets and the app’s default Automatic Settings. The displayed 75% side overlap could lead to non-compliance with the specified 80% lateral overlap requirement if not actively verified. Additionally, the offline map toggle may be overlooked in a fast-paced field setup, reinforcing the importance of a pre-departure checklist and a two-person cross-check of critical parameters.

8. Metadata Summary (for submission with this lab)

Platform/UAS: DJI Mavic 2 Pro Flight App: Drone Deploy Flight App Mission Type: Parallel ‘lawn mower’ grid mapping Study Area: Purdue Turf Farm (assigned area; larger required polygon) Airspace/Authorization: LAANC pre-check eligible for auto-approval; Authorizing airport: LAF; Airspace class: D Authorization Window (as shown in app): Sep 23, 2025 12:50 PM–2:50 PM EDT Planned Altitude: 60 m AGL Camera Orientation: 90° nadir Overlap Target: 80% front / 80% side App Automatic Settings Displayed: 80% front / 75% side (manual verification required) Weather: VFR; visibility 10 mi; temp ~22.2°C; wind ~4 kt from ~160°; few clouds Crew Roles: Pilot in Command / Visual Observer Images Captured: 105 Average Image Size: ~10.5 MB Total Dataset Size: 0.98 GB Drive + Setup Time: 30 minutes Mission Flight Time: 30 minutes Expected Products: Orthomosaic / 2D map outputs

9. Conclusion

This lab successfully demonstrated planning and execution of a parallel grid mapping mission using the DJI Mavic 2 Pro and the Drone Deploy Flight App over the Purdue Turf Farm. Airspace due diligence confirmed that the location was eligible for LAANC auto-approval under LAF in Class D airspace. A pre-flight weather review indicated VFR conditions with light winds, supporting safe operations and consistent image capture.

The mission collected 105 images with an overall dataset size of 0.98 GB. Travel and setup time was approximately 30 minutes, with a 30-minute mission flight duration. A key operational lesson was the need to actively verify lateral overlap when using Drone Deploy’s Automatic Settings, as the default side overlap displayed in the app may not automatically satisfy the lab’s 80% lateral overlap target. Consistent use of a pre-flight checklist, offline map preparation, and crew cross-checks can reduce configuration errors and improve mapping data reliability in future missions.

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