How Wittenberg connects
Compare routes in Wittenberg and accessible facilities. Examine how connections provide access to a place and which changes you would like to investigate.
Select a hotspot to see which destinations create the cluster and the paths connecting them. Then examine this location and housing costs in the place lab.
Integration describes how directly a street can be reached through the network. Blue marks low values; red marks high values.
More points mean higher through-movement potential. Modelled, not counted or real-time traffic.
Select a place and open the analysis.
See the recorded street course and how its sections differ in the network.
- Median
- Lowest section value
- Highest section value
Everyday access
| Facility type |
|---|
Existing → changed: the selected street section is interrupted. Both counts start at the same place entry; each time window includes all shorter paths.
Selected named facilities from OpenStreetMap, baseline 6 October 2026, cultural supplement retrieved 19 October 2026. Model: shortest network paths plus straight attachments, 4.8 km/h. Entrances, opening hours, crossings and slopes are not verified. Counts describe the mapped selection, not the completeness or quality of local provision. Inventory and supplement. Data basis.
Mapped opportunities, not measured popularity. Circles mark starting points, not catchment boundaries. Culture includes museums, libraries, theatres, cinema, cultural centres and selected heritage sites. One cluster can contain many individual sites. Gastronomy and leisure are not yet included. Hotspot data and method. © OpenStreetMap contributors, ODbL.
Mapped sites in the municipality
Data basis
Named facilities from OpenStreetMap, baseline 6 October 2026. Cultural supplement retrieved 19 October 2026 for the documented central areas. This is not a complete inventory. Luther House is temporarily closed and excluded from walking-time counts and hotspots. Distances use the street network of 6 May 2026; estimated times assume 4.8 km/h. Straight attachments connect mapped centres to paths. Entrances, crossings, accessibility, opening times and slopes are not verified. Terrain heights: official DGM1 sampled at 20 metres, DHHN2016. No slope adjustment or accessibility assessment. Inventory and supplement. Sources and calculation. © GeoBasis-DE / LVermGeo ST, DL DE BY 2.0.
Where is a closer look worthwhile?
These street sections combine high modelled accessibility with a strong role on routes through the city. They suggest questions for a site visit and an urban design study.
Compare the model with a design proposal: Forum Alte Canzley. A concept for the Schlossplatz.
A study for your city
Which facilities are accessible? Which connections hold a neighbourhood together? MGA brings maps, data and spatial analysis together around your development question. Together, we define the study area and data requirements, then develop transparent comparisons and questions for further planning.
Discuss a city study© OpenStreetMap contributors, ODbL. Street snapshot: 6 May 2026. Network measures: 6 October 2026. Facility comparison recalculated: 19 October 2026. Spatial potential, not measured footfall or navigational advice. Download the analysis network. Municipal boundary: © GeoBasis-DE / LVermGeo ST, DL DE BY 2.0.
Read the network
Space Syntax examines relationships between street segments. Our angular model connects segments only at shared mapped junctions. Integration (NAIN) measures accessibility; Choice (NACH) measures the role of a segment on routes between other segments. Connectivity counts directly adjacent segments. Mean angular depth expresses average changes of direction in the reachable network; it is not harmonic mean depth. District views retain the surrounding network and use the same colour thresholds as the whole city.
The local scales select a network catchment of 800 or 2,000 metres from each segment midpoint. Angular routes are evaluated inside that catchment and may be longer than its radius. This is a documented exploratory implementation, not an exact replication of depthmapX Tulip analysis. Road simplification, incomplete paths, barriers and the finite study boundary affect results. Land uses, opening times, slopes and observed movement are not part of this model.
A movement forecast requires observed counts, additional attraction measures and a calibrated statistical model. An animated Choice pattern alone is not such a forecast. Movement models.
Study points use the street medians of NAIN at 800 metres and NACH at 2,000 metres. Both must reach the highest fifth of municipal segment values. At least two assessed segments are required per street. Local screening covers a 600-metre circle around the mapped entry point, not an official district boundary. Up to three separated points are shown. No result means this screen found no match, not that the place has no development potential. Land use, vacancies, conservation, ownership and observed movement must be investigated separately.
NAIN = NC1.2 / TD. NACH = log(CH + 1) / log(TD + 3). Hillier, Yang & Turner (2012), depthmapX. Hillier, Leaman, Stansall & Bedford (1976), Space syntax, 3(2), 147–185. Hillier & Hanson (1984), The Social Logic of Space.
The facility comparison is a separate metric network analysis. It counts the selected mapped destinations within walking-time windows. It does not measure Integration or Choice. Reachable numbers and the variety of facilities should be read together; the interpretation depends on the place. Vale & Lopes (2023), Accessibility inequality across Europe. Space Syntax Network. Data and method record.
Explore the places in 3D