Embedded Files
Course Description
Introduces students to the use of unmanned aircraft systems for remote sensing and acquiring information about the Earth’s surface without coming in contact with it. Topics include but are not limited to an introduction to remote sensing, classification of unmanned aircraft systems, attitude estimation, lateral channel fractional order flight controller design, remote sensing using a single UAS, using multiple UAS’s, and diffusion control using mobile sensors and actuator networks.
Reflective Statement
Completing this course gave me a strong foundation in using unmanned aircraft systems (UAS) for remote sensing and data collection. I learned how UAS technology can gather detailed information about the Earth’s surface without direct contact, and how different UAS classifications are suited to specific applications.
One of the most valuable skills I developed was understanding and applying concepts such as attitude estimation and fractional-order flight controller design for lateral channels, which deepened my appreciation for the engineering principles underlying stable and precise flight. I also gained experience in both single- and multi-UAS operations, learning how to coordinate multiple platforms for more complex remote sensing tasks.
Working on projects involving diffusion control with mobile sensors and actuator networks taught me how UAS can be part of integrated systems that respond to changing conditions in real time. These activities not only improved my technical abilities but also strengthened my problem-solving and teamwork skills.
Overall, this class expanded my technical knowledge of UAS-based remote sensing and provided practical, hands-on experience I can apply to future work in aerial surveying, environmental monitoring, and other data-driven applications.
Project 1-Measurement
In this project, an automated mapping flight was conducted to generate a high-resolution orthomosaic for spatial analysis. The mission covered 4 acres in 7 minutes and 52 seconds, capturing 290 nadir images (-90° gimbal angle) at 150 feet AGL using 80% front overlap and 75% side overlap to ensure accurate photogrammetric processing. The flight was completed with a single battery at a mapping speed of 16 mph and a 180° flight direction.
The collected imagery was processed in DroneDeploy to produce an orthomosaic. Using DroneDeploy's measurement tools, linear distances and area calculations were extracted from the final map product to support quantitative site analysis and demonstrate applied photogrammetry workflows.
Project 2- 3D Orbit
This project, titled 3D Orbit Rutgers, is a digital mapping and aerial inspection initiative. Focused on the Rutgers Building, the project utilizes high-resolution drone imagery captured to create a detailed 3D orthomosaic map of the site and its surrounding landscape. The interface provides comprehensive analysis tools, including layers for Plant Health and Elevation, as well as an inventory of individual inspection photos that allow for a granular look at the building's exterior and rooftop infrastructure. By integrating geospatial data with visual media, the project serves as a centralized hub for site monitoring, asset management, and spatial documentation.
Project 3- Vegetation Indexing
This project focused on the application of remote sensing techniques to assess turf health on a local baseball field. By utilizing a small Unmanned Aircraft System (sUAS), a high-resolution multispectral dataset was captured to generate a Normalized Difference Vegetation Index (NDVI) map. This map allows for the identification of areas with high chlorophyll activity versus those under stress, providing actionable insights for precision turf management and irrigation optimization.
Project 4- Entire Campus
This mission focused on capturing a comprehensive, high-resolution orthomosaic map of the entire Atlantic Cape Community College Mays Landing Campus. Spanning approximately 128 acres, the project served as a large-scale exercise in mission planning, battery management, and regulatory compliance.
To ensure maximum safety and maintain strict Visual Line of Sight (VLOS) for a mission of this scale, the STEM building rooftop was utilized as the primary command center. This elevated vantage point provided an unobstructed line of sight across the entire mission radius, allowing for real-time monitoring of the aircraft's telemetry and surrounding airspace that would have been obscured at ground level.
Project 5-Inspection
This mission focuses on the high-resolution aerial inspection and 3D modeling of the school library at the Atlantic Cape Community College (Mays Landing Campus). Utilizing a DJI Mavic 3 Enterprise equipped with an RTK module, the project aims to assess the structural integrity and surface condition of the gym's vertical facade.
Key objectives include:
Precision Mapping: Capturing detailed RGB imagery to identify potential structural issues or surface degradation.
3D Reconstruction: Generating an accurate 3D model of the building for comprehensive spatial analysis and maintenance planning.
Safety & Compliance: Operating within Class C airspace with full LAANC authorization and strict adherence to pre-flight safety protocols.
Page updated
Google Sites
Report abuse