> For the complete documentation index, see [llms.txt](https://docs.live-eo.com/surfacescout/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.live-eo.com/surfacescout/configuration/defining-the-risk-model-around-your-pipeline.md). # Defining the risk model around your pipeline **Handling terabits of satellite data every single week is complex, but we've made it easy for you to generate key insights about your assets! The question "How do we assign a criticality level to those Insights?"**

You have probably noticed that we assign a criticality level to the Insight that SurfaceScout generates, right?

We do that automatically, let's dive into it! ### Distance-based risk model This is our most straightforward risk model. We measure the distance from the edge of the insight to the pipeline centerline and set the risk level according to defined distance ranges. For example: * **High**: from 0 to 5m * **Medium**: from 5 to 10m * **Low**: from 10 to 15m

### Change type risk model In this case, we scan a specified corridor—typically ±30 meters from the pipeline centerline—and assign a criticality level to each insight based on the type of change detected. For example, excavation work may represent a higher risk than plowing activity. Here’s how the classification might look: * **High**: Construction activity * **Medium**: Logging activity, waterbody changes * **Low**: Agricultural changes

### Combination of distance and change type risks model The rationale is that construction activity farther from the pipeline centerline may pose less risk than plowing activity occurring closer to it.

Change Type / Distance	0 to 5m	5 to 10m	10 to 15m
Plowing activity	Low	Low	Low
Construction	High	High	Medium
Logging activity	Medium	Low	Low

### Reference layer intersection risk model Pipeline operators may want to assign different levels of criticality to insights based on whether they intersect with an initial reference layer of existing human encroachments. The rationale is that an insight associated with pre-existing permanent infrastructure poses less risk to the pipeline than a new, unconnected observation. **For instance:** * Intersection > 30% of the Insight area with an existing human encroachment : Low * Intersection < 30% of the insight area with an existing human encroachment : High

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