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Surface height variation is clearly visible, especially where structures and vegetation exist.Patchy areas and speckling appear in some sections, indicating less reliable elevation estimates.These inconsistencies likely result from reduced overlap and lack of cross-hatch flight paths.Overall, the DSM is usable but less refined than a full grid mission.The DSM clearly captures surface features such as buildings, tree lines, and vegetation height changes.Flight liens and image centers are consistent, showing good coverage and overlap.Higher elevation values appear along the western edge, likely caused by trees and uneven vegetation.Some noise and rough texture near the boundary edges suggest weaker overlap and edge-of-mission artifacts, which is common in boundary-only flights.The terrain surface is smoother than the DSM and highlights overall ground shape well.Elevation transitions are more uniform across the site.Some distortion near the edges suggests insufficient ground point classificationThis directly reflects the limitations of collecting only boundary data rather than the full coverage.The DTM does a good job removing most above-ground features, leaving a smoother representation of terrain.Gradual elevation change from west to east is visible, showing the natural slope of the area.Minor rough patches remain near the western boundary, likely due to dense vegetation or limited ground visibility during collection.These artifacts likely to relate to flying only a boundary instead of a full interior grid. The orthomosaic is visually clear with good color consistency and sharp detail.Structures, roads, and field patterns align well with real-world features.Minor stretching and distortion appear near the outer edges of the mosaic.These edges issues are consistent with limited overlap and boundary-only mission planning.Data Set 2 Skydio Red and Blue Boundary
AT 309 Final Data Product GIS and Mapping Introduction
AT 309 Final Data Product GIS and Mapping
Introduction
In AT 309, multiple different labs were completed with different aircraft to gain experience working with UAS data, GIS software, and 3D mapping products. Some of the aircraft used includes the DJI Mavic 2, Skydio 2+, and the DJI Matrice 300. These labs focused on collecting aerial imagery and processing it into usable outputs such as Ortho mosaics, digital surface models, digital terrain models, and 3D points clouds. We went to various locations to allow different series of data to be collected, these location included the Student Garden at Purdue University, and the Turf farm research and diagnostic field at Purdue university. The goal of these labs was to understand how raw drone data can be turned into accurate maps and spatial data for real world applications.
Throughout the semester, we worked with software like Drone2Map, ArcGISPro, ArcGIS Earth, and Pix4D. Drone2Map and ArcGISPro were used to process imagery, manage coordinate systems and projections, and apply basic cartographic standards. The labs also highlighted how flight planning, overlap, and data quality affect the final outputs. Overall this report summarizes the workflows used across all labs, the skills developed, and the results of the GIS and 3D products created during AT309.
Processing insight
Overall steps we took to process data for the three data sets. To begin processing the UAS imagery, each mapping mission was first organized into separate data folders to ensure the datasets remained clear, readable, and easy to manage throughout processing. Once organized, the imagery was uploaded into Drone2Map, where the appropriate processing workflow was selected. For these projects, the focus was on generating standard 2D mapping products, so the Ortho mosaic, DSM and DTM outputs were enabled. Before starting the processing, basic project settings were reviewed, including image alignment options and output selections. After confirming the desired products, the processing was initiated and monitored as the software completed image alignment, dense matching, and final product generation. Once processing finished, Drone2Map produced a 2D map view displaying the completed Ortho mosaic and elevation models.
After the Drone2Map processing was complete, the final outputs were transferred directly into ArcGISPro for visualization analysis, and map creation. In ArcGISPro, multiple layouts were created to examine and compare the different data products. The DSM was used to visualize the full surface of the area, including terrain, buildings, vegetation, and other objects, making it useful for applications such as urban planning, emergency response, and infrastructure analysis. The DTM was used to represent the bare-earth surface by removing above ground features, which is especially important for terrain analysis, engineering, and construction-related work. To improve interpretation of elevation changes, shaded versions of both the DSM and DTM were created using hill shading, which simulates sunlight and shadow to give the terrain a more 3D appearance. In addition, an Ortho mosaic map was created, which combines overlapping aerial images into a single, geometrically corrected image that allows for accurate measurements and visual assessment of the area.
For each project Drone2Map also generated supporting processing information such as image count, processing time, cell size, pixel depth, elevation values, and coordinate projection details. Because the same general processing steps were applied across multiple mapping missions, it was possible to compare the quality of the final products between different flight patterns and conditions. This workflow demonstrated how consistent processing settings, combined with good flight planning, result in higher-quality spatial data that can be effectively used within a GIS environment
Data set 1 DJI Mavic 2 Red boundary
For this lab, our team conducted a mapping mission using the DJI Mavic 2 Pro to collect aerial imagery over the assigned study area at the Purdue Student Garden. The mission was flown using a parallel “lawn mower” grid pattern, which allowed for consistent image overlap and efficient coverage of the site. This lab also introduced a new flight application that does not require a paid subscription, providing an opportunity to compare its usability and performance to other mapping platforms used in previous missions, such as the Skydio s2. The primary goal of this mission was to gather high quality imagery for future processing and to gain hands on experience with mission planning, execution, and metadata collection for grid based mapping. By flying a single area using the Mavic 2 Pro, this lab emphasized understanding how flight parameters, overlap settings, and environmental conditions influence data quality while ensuring safe and compliant UAS operations.
Weather
Table 17
Temperature
78
Visibility
4 miles
Precipitation Prob.
38%
Wind
7 MPH
Gusts
9
KP index
2
Sats
21
There are no rows in this table
Parameters for flight
Table 18
Altitude
80 meters (200 feet)
Overlap
80%
Camera orientation
Nadir
There are no rows in this table
DSM
Figure 1 DSM Red boundary
Table 19
Cell Size
X= 1.647cm Y= 1.647cm
Pixel Depth
32 bit
DSM Value
202.344 -246.642
Coordinate Projection System
WGS 1984 UTM Zone 16N Transverse Mercator EGM96 Height (current Z)
There are no rows in this table
Review of DSM for Red Boundary DJI Mavic mission
Shaded DSM
Figure 2 Shaded DSM Red Boundary
Table 20
Cell Size
X= 1.647cm Y= 1.647cm
Pixel Depth
32 bit
DSM Value
202.344 -246.642
Shaded DSM Value
0-255
Coordinate Projection System
WGS 1984 UTM Zone 16N Transverse Mercator EGM96 Height (current Z)
There are no rows in this table
Shaded DSM review
DTM
Figure 3 DTM Red Boundary
Table 21
Cell Size
X= 8.2337cm Y=8.2337cm
Pixel Depth
32 bit
DTM Value
202.419 – 222.546
Coordinate Projection System
WGS 1984 UTM Zone 16N Transverse Mercator EGM96 Height (current Z)
There are no rows in this table
Review for DTM
Shaded DTM
Figure 4 Shaded DTM Red boundary
Table 22
Cell Size
X= 8.2337cm Y=8.2337cm
Pixel Depth
32 bit
DTM Value
202.419 – 222.546
Shaded DTM Value
0-255
Coordinate Projection System
WGS 1984 UTM Zone 16N Transverse Mercator EGM96 Height (current Z)
There are no rows in this table
Review for shaded DTM
Ortho mosaic
Figure 5 True Ortho Red Boundary
Table 23
Cell Size
X= 1.647cm Y = 1.647cm
Pixel Depth
32 bit
Coordinate Projection System
WGS 1984 UTM Zone 16N Transverse Mercator EGM96 Height (current Z)
There are no rows in this table
Review for orthomosaic
This was my second data set that I processed through Drone2Map!
In this lab, our team completed two mapping mission using the Skydio platform at the Purdue Student Garden to practice planning, executing, and managing autonomous UAS mapping flights. We flew both a standard lawnmower grid mission and a cross-hatch mission with a perimeter scan to simulate real world mapping scenarios. The lab focused on collecting usable aerial imagery while identifying and responding to challenges such as software issues, environmental hazards, and unexpected interactions on site. Through these missions, we gained hands-on experience with Skydios autonomous mapping capabilities and reinforced the importance of preparation, adaptability, and proper communication during UAS operations.
Red Rectangle (Lawnmower Grid) Mission
Table 24
Altitude
200 feet
Overlap
80% frontal and side
Lens Angle
90° (Nadir)
Flight time
approximately 20 minutes.
There are no rows in this table
Blue Rectangle-Size Area (Cross Hatch + Perimeter)
Table 25
Altitude
60–80 feet ( for clearance of obstacles)
Overlap
80%
Lens Angle
75° bevel
There are no rows in this table
Extra Notes
Table 26
Location
Weather
Hazards
Notes
Student garden
Sunny
Trees, gardeners
One pedestrian interaction.
There are no rows in this table
DSM Red boundary
Figure 6 DSM red boundary
Table 27
Cell Size
X= 2.782cm Y= 2.782cm
Pixel Depth
32 bit
DSM Value
205.072-237.771
Coordinate Projection System
WGS 1984 UTM Zone 16N Transverse Mercator EGM96 Height (current Z)
There are no rows in this table
Review for DSM
The DSM effectively shows height differences between structures, vegetation, and open ground. Taller objects such as buildings stand out clearly against flatter terrain. Some elevated noise appears along tree lines, which is expected due to irregular vegetation and shadows impacting point matching.
Shaded DSM red boundary
Figure 7 Shaded DSM of purdue student garden
Review for shaded DSM of Red boundary
The DSM clearly captures surface features such as greenhouses, buildings, and taller vegetation. Rectangular patterns from the garden plots and structures are easy to identify, which indicates good image overlap and flight consistency. Slight noise appears near the outer edges and along taller objects, likely caused by shadows and angle changes during image capture.
Table 28
Cell Size
X= 2.782cm Y= 2.782cm
Pixel Depth
32 bit
DSM Value
205.072-237.771
Shaded DSM Value
0-255
Coordinate Projection System
WGS 1984 UTM Zone 16N Transverse Mercator EGM96 Height (current Z)
There are no rows in this table
Shaded DSM blue
Figure 8 shaded dsm blue
Table 29
Cell Size
X= 2.782cm Y= 2.782cm
Pixel Depth
32 bit
DSM Value
205.072-237.771
Shaded DSM Value
0-255
Coordinate Projection System
WGS 1984 UTM Zone 16N Transverse Mercator EGM96 Height (current Z)
There are no rows in this table
Shaded DTM blue boundary Review
This visualization helps emphasize elevation patterns while still showing underlying imagery. Flight lines and image centers appear evenly spaced, showing good mission planning. Any slight inconsistencies in height values occur mostly near the mission boundary, again pointing to reduced overlap at the edges.
DTM blue boundary
Figure 9DTM blue boundary
Table 30
Cell Size
X= 1.391cm Y=1.391cm
Pixel Depth
32 bit
DTM Value
205.134– 209.143
Coordinate Projection System
WGS 1984 UTM Zone 16N Transverse Mercator EGM96 Height (current Z)
There are no rows in this table
DTM review
This DTM looks good overall and clearly represents the underlying terrain without buildings or vegetation height. Elevation changes are smooth, especially across open grassy areas, which shows that the terrain filtering worked correctly. Some edge areas appear slightly smeared or stretched, which is likely due to less overlap near the boundary of the flight area. These minor distortions relate to the fact that data density drops off at the edges of the mission.
Shaded DTM blue boundary
Figure 10DTM Blue boundary
Table 31
Cell Size
X= 1.391cm Y=1.391cm
Pixel Depth
32 bit
DTM Value
205.134– 209.143
Shaded DTM Value
0-255
Coordinate Projection System
WGS 1984 UTM Zone 16N Transverse Mercator EGM96 Height (current Z)
There are no rows in this table
Shaded DTM blue boundary review
This DTM does a good job removing above ground features and showing elevation trends across the site. The center of the map looks very clean, while the perimeter shows small elevation inconsistencies. These issues likely come from fewer image tie points near the edges and slight elevation smoothing during processing.
Orthomosaic blue
Figure 11Orthomosaic blue boundary
Table 32
Cell Size
X= 2.782 Y = 2.782cm
Pixel Depth
32 bit
Coordinate Projection System
WGS 1984 UTM Zone 16N Transverse Mercator EGM96 Height (current Z)
There are no rows in this table
Orthomosaic Map review
This final orthomosaic clearly combines both boundary areas and shows consistent alignment between datasets. The POIs are sharp and well-defined, especially in the central overlap region. Minor distortion near the outer boundary is visible but does not significantly impact usability. These small issues align with field conditions such as changing lighting and the limits of a single-battery mission.
Ortho mosaic RED boundary
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