---
title: "Methodology · Gatuligan"
canonical: https://bilfrittstockholm.org/en/streets/methodology/
lang: en
---

# Methodology

How we rank Stockholm's streets

## Overview

Gatuligan ranks **859 inner-city streets** in Stockholm (inside the old toll boundary) based on five factors. Each factor is normalized to a 0–100 score with percentile ranking, weighted, and summed into a total score.

The higher the score, the better the street is to spend time on as a person, cleaner air, more greenery, more street life and less car traffic.

## The five factors

20% 

### Air quality

**Source:** SLB-analys Kartläggning ABC 2025 (Stockholm Environment Administration)

**Data:** Modeled annual mean values for NO2 and PM10 in µg/m³, published as class intervals.

**Method:** The midpoints of the intervals are sampled every 10 meters along each street segment. Length-weighted average per street.

**Limitation:** The values are class intervals (e.g. "6–8 µg/m³"), not exact measurements. Streets within the same interval get an identical score.

20% 

### Traffic volume

**Source:** The Traffic Office's traffic-flow map (OpenStreetGS WFS)

**Data:** Annual average daily traffic (AADT), number of vehicles per weekday.

**Method:** Each street segment is matched to the nearest traffic-flow segment (within 50 m). Length-weighted average per street.

**Limitation:** The data comes from the 2014–2016 base year and may be out of date. Streets without a measurement point are excluded from the traffic factor (not penalized).

20% 

### Noise

**Source:** Bullerkartan 2022 (Stockholm Environment Administration, via ArcGIS)

**Data:** Modeled equivalent noise levels (LAeq, dBA) as polygon intervals (e.g. "55–60 dBA").

**Method:** The midpoints of the intervals are sampled every 10 meters along street segments. Length-weighted average per street.

**Limitation:** Based on 2019 traffic data, model-calculated. Temporary noise sources (construction, events) are not included.

30% 

### Street life

**Source:** OpenStreetMap (Overpass API, March 2026)

**Data:** Number of shops (shop=\*) plus restaurants, cafés, bars and pubs (amenity=restaurant/cafe/bar/pub/fast\_food).

**Method:** Amenities within a 15-meter buffer around each street segment are counted. Each amenity is assigned to its nearest street (avoiding double counting). Normalized per 100 meters of street length.

**Limitation:** OpenStreetMap data is collected voluntarily. Coverage varies, some areas lack data entirely. Streets with no amenities in OSM get 0 points.

10% 

### Greenery

**Source:** SBK tree-crown footprint 2022 (City Planning Administration, LiDAR scan)

**Data:** Individual tree-crown polygons (crown area >3 m², height >2 m) from laser data with >16 points/m².

**Method:** 15-meter buffer around each street. Tree-crown coverage is calculated as the ratio of crown area / buffer area.

**Limitation:** The data is from 2022 and does not capture trees planted or felled since then.

## Scoring

Each factor is converted to a 0–100 score using **percentile ranking** among all streets:

* A street with better air than 90% of all streets gets an air score of 90.
* Factors where a high value = bad (air, traffic, noise) are inverted: score = 100 − percentile.
* Factors where a high value = good (street life, greenery) are kept: score = percentile.

The total score is a weighted average. Streets that lack measurement data for a factor (e.g. traffic) are excluded from that factor, they are not penalized, but the average is computed over fewer factors.

## Scope

The ranking covers **Stockholm's inner city** (roughly inside the old toll boundary / congestion-charge zone). The boundary is defined as a manually drawn polygon based on the toll-station locations.

The following are filtered out:

* Motorways and arterials (e.g. Klarastrandsleden, Söderleden)
* On- and off-ramps (e.g. Riddarfjärdspåfarten)
* Bridges (e.g. Centralbron, Barnhusbron)
* Interchanges and connections
* Street segments shorter than 50 meters

## Known limitations

* **Traffic data is old** (2014–2016). Traffic patterns may have changed, especially after the pandemic and new traffic regulations.
* **Air data is coarse**. Class intervals (e.g. "6–8 µg/m³") give an identical score to all streets within the same interval.
* **OSM data is uneven**. Areas with active mappers have more registered shops/restaurants, which gives an artificially higher street-life score.
* **Time mismatch**. Air data is from 2025, noise and trees from 2022, traffic from 2014–2016\. The streets are compared using data from different years.
* **No account for street type**. Alleys and boulevards are compared head-on, a narrow alley without trees is penalized as hard as a wide street without trees.

## Open data and source code

All underlying data is open and free to use.

Have feedback, found an error, or want to contribute? Get in touch on [r/BilfrittStockholm](https://reddit.com/r/BilfrittStockholm).