> For the complete documentation index, see [llms.txt](https://docs.aeroai.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.aeroai.io/siega-web-features/analysis.md).

# Analysis

Analysis is where you take data that already holds more information than it first shows and bring that detail to the&#x20;surface. A LiDAR scan, for example, often arrives as one solid wall of points, even though every point already knows&#x20;whether it is ground, vegetation, a building, or a power line. The tools in this section let you read that hidden&#x20;detail and put it to use, so the scene goes from a single mass of data to something you can actually pick apart and&#x20;understand. Each tool has its own page with the full walkthrough.

Point Cloud Classification works with point clouds that were captured with classification codes built in. It reads&#x20;those codes straight from the data, then hands you control over how each type appears. You can keep the natural color&#x20;of the cloud or switch to coloring by class, recolor any type, hide the ones you do not need, and adjust the size of&#x20;the points until the picture reads clearly. The result is the same scan, but now the ground, the trees, the buildings,&#x20;and the wires each stand on their own.

This is where your data stops being one undivided whole and starts being something you can read piece by piece.
