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Sliver polygon

Sliver polygon is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Sliver polygon rather than just read about it. In short: A sliver polygon, in the context of Geographic Information Systems (GIS), is a small polygon found in vector data that is an artifact of error rather than representing a real-world feature. They have been a recognized source of error since overlay was first invented in the 1970s.

Sliver polygon — main illustration
Sliver polygon — illustration

Key takeaways

  • Sliver polygon belongs to science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Sliver polygon to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Sliver polygon from memory before moving on to harder problems.

Reference excerpt

A sliver polygon, in the context of Geographic Information Systems (GIS), is a small polygon found in vector data that is an artifact of error rather than representing a real-world feature. They have been a recognized source of error since overlay was first invented in the 1970s.

History These meaningless polygons were recognized early in the development of GIS. In fact, in 1978 Michael Goodchild found that they constituted the majority of all polygons in some operational GIS. Early programs for performing vector overlay, such as WHIRLPOOL, developed mechanisms for preventing sliver polygons, such as the "epsilon filter" (fuzzy tolerance) In recent decades, most of the focus of software vendors and practitioners has been on improving the quality of GIS data to prevent them.

Cause, Prevention, Repair Sliver polygons are typically created when polygons are automatically generated from lines that should be coincident (e.g., an international boundary following a river de jure, or two adjacent counties) but are not, due to the natural discrepancies that arise from manual or automated digitization. This can occur when a single layer is digitized and adjacent polygons are traced separately, or during vector overlay when separate polygon layers are merged. They can be prevented during the digitization process by ensuring that lines that are supposed to be coincident actually are coincident. The editing systems in most GIS software provides for snapping, in which a point placed near an existing point "snaps" to the exact same coordinate. The user can usually control the process, such as setting a snap tolerance (the maximum distance to consider "close enough"), and which layers and which parts of those layers to snap to. In addition, many systems have tracing tools, so that newly digitized lines can exactly follow existing lines. During the overlay process, the preferred mode of sliver polygon prevention is the use of a fuzzy tolerance, which is sometimes called a "xy tolerance" (ArcGIS) or "snapping threshold" (GRASS), and was originally called an "epsilon filter." The user provides a tolerance distance, and as the lines of the input layers are being combined topologically, any lines that are roughly parallel, consistently closer together than the fuzzy tolerance, are combined into a single line. The choice of a proper fuzzy tolerance depends on the situation, especially the scale of the data, and can be a challenge. If it is set too large, narrow but meaningful polygons (e.g., islands in a river) can be collapsed. If sliver polygons still exist in a data set, they may be removed manually or automatically. Some GIS systems provide a tool for topological verification, which searches for topological errors in a data set (sliver polygons being one among many potential types of error), flagging them for correction. One option is to attempt to remove them automatically; many GIS systems provide a tool (usually called Eliminate) that finds very small polygons and merges them into one of the adjacent polygons. There is usually a parameter to pre-select, in situations where there is more than one adjacent polygon, either the largest adjacent polygon or the one with the longest common boundary.

References

External links The Polygon Overlay Operation, E.2.

Illustrations

Sliver polygon: Examples of sliver polygons
Examples of sliver polygons

Worked examples

Example 1 — a first encounter with Sliver polygon

Start with the simplest possible case. Write down what Sliver polygon claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Sliver polygon before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Sliver polygon ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Sliver polygon

In research
Sliver polygon appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Sliver polygon in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Sliver polygon is common in secondary-school and first-year university syllabi. It links to neighbouring topics Geographic information systems, Geometric intersection, Polygons, so understanding it makes those chapters shorter.
In everyday life
Look for Sliver polygon outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Sliver polygon in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Sliver polygon means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Sliver polygon out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Sliver polygon in simple terms?

A sliver polygon, in the context of Geographic Information Systems (GIS), is a small polygon found in vector data that is an artifact of error rather than representing a real-world feature. They have been a recognized source of error since overlay was first invented in the 1970s.

Why does Sliver polygon matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Sliver polygon?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Sliver polygon.

Tags

  • Geographic information systems
  • Geometric intersection
  • Polygons

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