Introduction:

Our recent project at the Purdue Wildlife Area involved comprehensive data collection, processing, and analysis. This report summarizes our endeavors, detailing the location, metadata, flight operations, processing challenges, deliverables, and data analysis.

Location:

The project took place at Purdue Wildlife Area, specifically within Area 2, a rural setting characterized by diverse land cover including bare land, grasslands, tree cover, and water bodies. Flight operations were conducted within Class G airspace, allowing flights up to 400 ft AGL without LAANC authorization.

Metadata:

Flight details, including vehicle, sensor, pilot, and weather information, are summarized in Figure 2. The flight was executed smoothly under favorable weather conditions, facilitating optimal data collection.

Flight Operations:

Two flights were conducted, with Ronald Greene piloting the second flight. Greene's flight lasted nine minutes, capturing 511 high-detail photos without incident. Post-flight checks ensured data integrity before departure.

Processing:

Challenges arose during orthomosaic and DSM processing due to the dataset's size and detail. After splitting and merging the data, processing was completed in approximately six hours, yielding quality orthomosaic and DSM outputs (Figure 3).

Deliverables:

A range of cartographically correct maps was generated, including orthomosaic, DSM, land cover classification, and tree height analysis. Each map served specific analytical purposes, facilitating a comprehensive understanding of the mission area.

Data Analysis:

Orthomosaic, DSM, and their comparison provided detailed representations of surface and elevation features (Figures 4-6). Digitized orthomosaic and reclassed DSM maps highlighted key land features and objects taller than 6m and 10m, respectively (Figures 7-10). However, challenges were encountered in creating the classified map due to software limitations, leading to processing delays and eventual data loss (Figure 11-12).

**Conclusion:**

This project served as a culmination of knowledge acquired throughout Purdue's UAS courses. It underscored the importance of GIS software in processing and analyzing UAS-derived data. Challenges encountered during the project provided valuable learning experiences, enhancing proficiency in data collection, processing, and map creation. Overall, this project exemplified the practical application of UAS technology and GIS in environmental analysis and management.