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Week 2 Field Outing - Skydio

AT 309 Lab #2

Skydio Mapping

Weather:

1854 UTC (1:54 EST) 04 Thu Sep 2025 Temperature: 18.9°C (66°F) Dewpoint: 5.6°C (42°F) (RH = 42%) Pressure (altimeter): 29.83 inHg (1010.2 hPa) (sea level pressure 1010 hPa) Winds: from the W (280°) at 8 kt (4.1 m/s, 9.2 mph) gusting to 16 (8.2 m/s, 18.4 mph) Visibility: 10+ mi (16+ km) METAR for: KLAF (Lafayette/Purdue Univ Arpt, IN, US)

LAANC/Airspace: Purdue Turf Farm, Class D airspace

we reviewed the Skydio 2+ UAS platform and its imaging features.

We had already used the Skydio 2+ in previous courses and completed several short flight missions. This lab was a refresher that helped us practice basic operation, proper image capture, and simple mission planning skills that we will use in later labs.

Using the Skydio 2+ mobile app, we took photos at different altitudes while keeping the camera pointed straight down at a 90-degree angle to the ground. These are called nadir images. Nadir images are important for mapping and photogrammetry, and we will use them a lot throughout the rest of the course.

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At 25 feet AGL, the drone captures a small area, but the images show a lot of detail because the drone is flying low.

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Raising the altitude to 100 feet lets the drone capture a much larger area, but the images start to lose some small details.

We kept taking nadir images at higher and higher altitudes until we reached the highest altitude allowed by our LAANC approval at the Purdue University Turf Farm.

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At higher altitudes, each image covers a much larger area, which shows the tradeoff between covering more ground and seeing fine detail.

Overall, this lab showed that flight altitude directly affects image scale, coverage, and detail. Understanding this is important for planning effective UAS mapping missions in future labs.

1. Introduction

The purpose of this project was to utilize the Skydio S2 platform to capture aerial images at various altitudes and demonstrate the platform’s autonomous flight and data collection capabilities. Particularly, the emphasis was on showing how the drone’s vision based autonomous flight system and stable straight down imaging could be used to observe differences in data quality across altitudes and apply these results for subsequent mapping and analysis tasks.

2. Study Area

The exercise was conducted at a turf farm site. This location provided flat terrain and minimal surrounding obstacles, making it an optimal environment for drone flight and data collection. Weather conditions were clear with light winds, ensuring stable flight. Multiple teams were working simultaneously on site, with visible parking areas and research equipment in use.

Table 1

Table 1

Location

Turf Farm

Terrain

Flat grassland

Weather Conditions

Clear skies, light winds

Potential Hazards

Human activity, vehicles, small equipment

There are no rows in this table

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3. Methods

Data collection was conducted using the Skydio S2 and its dedicated controller. Key parameters included:

- Flight Altitudes: 25 ft to 200 ft in 25 ft increments - Gimbal Setting: -90° - Flight Mode: Manual altitude control with auto stabilization - Geofence: Not used. open area, FAA altitude restrictions observed - Overlap & GSD: Altitude based capture used to analyze relative resolution differences

4. Data Collection Outcomes

Table 2

Table 2

Travel & Setup Time

30 minutes

Total Flight Time

20 minutes

Number of Images

8 (altitude increments from 25–200 ft)

Video Captured

Waypoint flight video (~40 seconds)

Average Battery Consumption

20%

Dataset Size

1500 MB (RAW photos + video)

There are no rows in this table

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There were no significant issues during the data collection process. The drone maintained stable hover and nadir imaging at each altitude. Some minor shaking was noted due to wind during altitude transitions, but this did not affect the final data quality.

5. Data Deliverables

illustrate differences in field of view and resolution quality:

200 ft altitude – Wide field of view, lower resolution 100 ft altitude – Narrower field of view, clearer subject identification 25 ft altitude – High resolution, clear identification of equipment and personnel

Pixel resolution observations: - Lower altitudes yield smaller GSD values, resulting in higher detail. - This demonstrates how altitude selection directly impacts data quality for mapping and inspection tasks.

6. Conclusion

This exercise confirmed that the Skydio S2 platform is capable of reliable, vision-based autonomous flight and data collection. The drone’s ability to maintain stable nadir imaging at various altitudes ensured that data could be collected consistently and effectively. Results highlight the S2’s potential for use in 2D mapping, 3D modeling, and site inspections where data precision and consistency are critical. Overall, this report serves as evidence of the Skydio S2’s reliability and utility in professional data collection tasks.

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