Interactive map of the Meerbusch city area with tree crowns, search areas and heat exposure by day and night. Pan and zoom with the mouse, two fingers or the zoom buttons. On the keyboard the arrow keys pan the view, plus and minus zoom. The figures for the active layers appear as text in the status box at bottom right, and in full in the section below the map. Individual trees can be selected by clicking.
The interactive map cannot be printed – outlines and points are drawn on a dark ground that does not work on paper. The “Generate image” button above produces a picture of the current view, or open this page online.
Land use types
Background
Notes on visualisations and data
The starting view shows the city centre: every mint-coloured area is a tree crown, the pale lines are the street network. Dragging pans the view, mouse wheel or two fingers zoom. Zooming in resolves the overview into individual trees, each of which can be clicked. The search-area switch shows individual street areas of 150 m² or more that today carry no crown and have no tree closer than eight metres. The bar below selects one or more land types, highlights them and shows their measured canopy cover. The buildings switch places the official footprints as context beneath. The parking switch shows the parking strips and parking areas from OpenStreetMap — not an official survey, the space count is estimated from them and is a lower bound. The two heat switches separate what otherwise falls together in this map series: Heat by day shows the heat stress at 15:00, Heat at night the modelled air temperature at 4:00. Both are area-wide and lie beneath the crowns, which is why the trees are hidden when switched on. The places switch shows concrete public places — schools, day-care centres, playgrounds, bus stops, benches — with their actually measured shade; warm-coloured rings lie under 10 percent. The aerial imagery switch places the official orthophoto beneath from district zoom level, for comparing the vector data with reality.
A search area is not automatically a safe, new tree location. Whether a tree can stand there depends on the utility lines underground, on emergency access routes, sightlines and the question whether — and how many — parking spaces may be removed. Search areas therefore show where a closer look might be worthwhile.
Parcel boundaries are administrative cuts — a gap spanning two parcels counts as two search areas. This unit is an area to be checked, not a planting site — how many trees fit into one search area is not something this map says.
Why the utility lines are missing here: They do not exist as one dataset. Every network operator keeps its own — electricity, gas, water, sewage, district heating, telecommunications —, they are not open, and as critical infrastructure they will not become open either. That is not a gap this map can close. It does not replace a utility enquiry; it says where asking is worthwhile.
The areas come from ALKIS (actual land use). Tree positions from our own derivation from the official normalised surface model (nDOM50, 50 cm grid spacing) — no tree cadastre, no species, no planting year. Trees are recorded from around five metres in height, including on private land; hits on buildings were discarded using the official ALKIS footprints.
The “Parking” layer shows the parking strips and parking areas from OpenStreetMap. Unlike in Berlin, here there is no official parking survey : the number of spaces is estimated from the length of the parking strips (5.5 m per longitudinal space) and is therefore a lower bound, not a count. OpenStreetMap is incomplete, and where nothing is recorded the map shows nothing — not “nobody parks here”. No legal claims can be derived from this data; the signage on site is what applies.
The share of the sky visible from a point on the ground — computed purely geometrically from buildings, tree crowns and terrain, using the official surface model at one metre resolution. Green means open sky, red means dense development.
This quantity explains why two streets with the same number of trees can be differently warm: where little sky is visible, less radiation arrives during the day, but the area also cools down less well at night.
Not a temperature. The sky view factor knows neither sun nor time of day. It does not say how warm it is, but how open the space is. Anyone who needs a figure in degrees needs a microclimate simulation; this map provides the geometry such a simulation builds on.
Shows the heat stress on people at 15:00, measured as the Physiologically Equivalent Temperature (PET) from the Klimaanalyse NRW 2026 of the Landesamt für Natur, Umwelt und Klima, calculated with the FITNAH 3D model. PET takes humidity, wind and radiation into account alongside air temperature.
The five classes are cut at the absolute thresholds of VDI guideline 3787 , (23, 29, 35, 41 °C), and not, as usual elsewhere, by quantile from the distribution of this one city. „Severe heat stress“ here therefore means literally „PET from 35 °C“, not „the hottest fifth of this city“. Only this makes the layer comparable between cities.
The grid spacing is 25 m — fine enough to distinguish individual streets, unlike the 100 m analyses of other German states.
Shows the modelled air temperature 2 metres above ground at 4:00 from the Klimaanalyse NRW 2026 of the Landesamt für Natur, Umwelt und Klima, calculated with the FITNAH 3D model at 25 metre grid spacing. What is drawn is the extreme summer night; the typical night lies well below it and appears as a comparison figure in the key-figure box. Classes 4 and 5 begin at 20 °C and are therefore exactly the tropical-night definition of the German Weather Service: a night in which the air temperature does not drop below 20 degrees and the body does not recover. Absolute thresholds instead of quantiles, and therefore comparable between cities. One caveat belongs with it: the night raster carries values only over the built-up area; green, open and water surfaces remain unassessed — the denominator of the percentage is a different one than for the daytime layer.
The official orthophoto (DOP20, 20 cm ground resolution) of the Geobasis NRW sits from district zoom level as an image base beneath the other layers, loaded live per map view. It serves as a direct check: is a parking strip, a search area or a tree crown really where the vector data shows it? Licence dl-de/zero-2.0.
The canopy area this map calculates with: every area between 5 and 45 m high in the official surface model that lies more than 2 m from a building footprint, accurate to 1 m. Visible from district zoom. While the tree canopy layer is on, trees appear as dots at their location; without it, as circles whose size is estimated from their height.
Official building footprints (ALKIS, Geobasis NRW), shown as grey context beneath the other layers. Coverage is filled in step by step; where no tile is available yet, the area stays empty rather than being shown incorrectly.
Shows specific public places — schools, day nurseries, playgrounds, churches, cemeteries, sports grounds, bus stops, benches — with the actually measured canopy cover in their surroundings. The radius depends on the place: 60 m at a school, 20 m at a bus stop, 15 m at a bench. In Meerbusch, 321 of 857 places are under 10 % shaded. This assessment is the map's real purpose: Even the climate analysis's fine 25-metre grid spacing cannot make a statement about a single place of this size.
The district boundaries come from the official ALKIS dataset (Geobasis NRW, dl-de/zero-2.0). The figures per district — tree count, canopy cover, heat-pocket share, mapped parking length, search areas — are computed from the same data as the citywide values, just limited to the area of the respective district. Small rounding differences from the city total are edge effects of the area overlay at the boundaries.