Frequency rate of selected housing-relevant offences, 3-year average from the Berlin crime atlas (Kriminalitätsatlas Berlin, Polizei Berlin, dl-de-by-2.0). Granularity Bezirksregion, mirrored onto planning areas. A structural aggregate, NOT part of the overall score. Relates cases only to registered residents, not to tourists/commuters.
Higher = more recorded cases per resident, not a measure of personal risk and not a judgement of a “good” or “bad” Kiez.
Calculation
Recorded crime per Bezirksregion: frequency rate (cases per 100,000 residents) of selected housing-relevant offences, equally weighted (0.20 each): neighbourhood offences (Kieztaten), residential burglary, vandalism, street robbery/bag snatching, bicycle theft. For each offence the 3-year average (2023–2025), from which the weighted index is derived, normalised to 0–100 (300 → 0, from 1,750 → 100). The upper limit caps city-centre outliers (government quarter, Alexanderplatz) whose frequency rate is overstated by tourists and commuters. The values are only available per Bezirksregion and are mirrored onto the planning areas it contains (constant within the Bezirksregion). A separate dimension, NOT part of the overall score, structural context like the social situation. Higher means more recorded cases, not a safety ranking.
Aggregation
LOR Bezirksregion
Maintenance
navigator.berlin (own calculation from the Berlin crime atlas (Kriminalitätsatlas Berlin), Berlin Police)
Update frequency
annually (Kriminalitätsatlas, reference date 31 Dec)
Coverage gaps
Granularity Bezirksregion (143), coarser than the five dimensions native to planning areas.
The frequency rate relates cases only to registered residents, not to tourists, commuters or customers: inner-city hotspots appear overstated.
Unreported crime: only reported cases, and reporting behaviour varies by location.
What we don't show
Crime scene principle: only cases with an exact crime scene, pickpocketing excluded.
No statement on personal risk and no rating as a “safer” or “more dangerous” Kiez.
Night-time noise disturbs the sleep phases in which the cardiovascular system and nerves recover. The World Health Organization recommends a guideline value of 40 dB for night-time noise (LNIGHT). The Berlin noise mapping therefore reports LDEN and LNIGHT separately.
LDEN stands for “Level Day-Evening-Night” and is a noise average weighted over 24 hours. Evening and night levels count with penalties of 5 and 10 dB, because noise is more disturbing then. The value serves as a uniform comparison standard across the EU.
The strategic noise mapping shows road, rail, aircraft and industrial noise separately. The map shows total traffic noise from road, rail and air traffic (LDEN), combined per planning area.
The Senate Department for Urban Mobility, Transport, Climate Action and the Environment takes suggestions on strategic noise reduction into the action plan. Complaints about specific sources (construction sites, businesses) go to the responsible Bezirk office (Bezirksamt) or public order office (Ordnungsamt). On the methodology page we link to the official points of contact.
The open Berlin data provides one noise class per planning area (for example “medium” or “high”), not point values. We reproduce the value exactly as published, so as not to suggest a precision that the dataset does not contain.
For each planning area, the Senate Department calculates how many square metres of green space near homes are available per resident within the catchment area. The benchmark is 6 square metres per person. Whether a planning area reaches or misses this value determines the category “high”, “moderate” or “low”.
Trees and larger green spaces lower the air temperature through shading and evaporation. Urban climate analyses show that densely built neighbourhoods with little vegetation stay measurably warmer on summer days than areas with comparable buildings and more greenery. The climate category on this map reflects that.
Stop density is a first, rough indicator of connectivity. It says nothing about frequency, routes or accessibility. In Berlin, a high density often correlates with inner-city locations and interchange hubs, a low density with outer-city areas.
Not at present. The value counts stops within the area boundaries and divides them by the area. We are gradually extending the indicator with walking distances and station categories. The methodology page documents every extension.
We count U-Bahn, S-Bahn, tram and bus stops of the BVG and S-Bahn Berlin GmbH together. Regional rail stations are reported additionally, because they are relevant for commuting.
Live data requires server caching and licence costs, and is often available only for a short time. We deliberately rely on static aggregates from open datasets that we can check and version.
Rents depend on year of construction, fittings, location and reference dates. The Berlin Mietspiegel provides ranges per residential area and age-of-building class, not point values per address. On the methodology page we link to the official Mietspiegel calculator.
The standard land value (Bodenrichtwert) describes an average land price per square metre, verified by the Berlin Committee of Valuation Experts (Gutachterausschuss). The Mietspiegel describes the local comparative rents for housing. Both values apply to areas, not to individual addresses.
PET is a bioclimatic indicator. It states which air temperature in an enclosed room would correspond to the perceived temperature outdoors. Wind, humidity and radiation feed into it. The value is suited to comparing heat stress across urban areas.
The German Weather Service (Deutscher Wetterdienst) counts a day with a maximum temperature of 30 degrees Celsius or more as a hot day. The number of hot days per year in Berlin has risen markedly since the 1990s, as documented in the 1991-2020 climate normal period.
A climate normal period is a 30-year reference period that the World Meteorological Organization uses to make weather averages comparable. For Berlin, we use the current period 1991-2020 as the basis for comparison.
Asphalt and stone store heat and release it again at night. Heavily sealed neighbourhoods cool down less well than neighbourhoods with vegetation or open water. The urban climate analysis treats sealing as one factor among several.