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Imagery Classification Analysis

The main focus of this lab was getting familiar with ArcGIS Pro's object classification tools, and to me it was one of the most interesting assignments because of how visually distinct the results ended up being.

Figure 3 is probably the most striking of the three — it shows crack detection on a small stretch of road, where the classification was able to pick out the fracture lines running through the pavement just by analyzing pixel color values. It's a pretty impressive result when you think about it, because those cracks are subtle, and the fact that the software can isolate them automatically speaks to how powerful these tools are for infrastructure assessment.

Figure 2 tackles permeable versus impermeable surfaces using the same general classification approach. The blue and white separation makes it immediately clear how much of the area is covered by hard surfaces versus natural ground — the kind of output that would be genuinely useful for stormwater or urban planning work.

Figure 1, the 8-class land cover map, was actually the most involved of the three. The classification itself wasn't necessarily harder, but having to also run area calculations on top of it added another layer to the workflow that required a bit more careful thinking about what the data was actually telling you.

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