A shade map shows where sunlight and shadow fall at a chosen place, date and time. It combines sun geometry with building and terrain heights, letting you plan routes, plantings or window placement before you commit.
Key takeaways
- A shade map predicts where shadows will fall at a given location, date and time by combining the sun’s calculated position with a three-dimensional model of buildings, terrain and sometimes trees.
- The underlying sun position is highly reliable because it follows well-established astronomical formulae, but the shadows drawn on the map are only as accurate as the height data behind them.
- Practical uses include choosing a shaded walking or cycling route, siting solar panels, planning a garden, assessing a flat before renting, and scheduling outdoor photography.
- Coverage is uneven: dense, well-surveyed cities often have detailed building and vegetation models, while smaller towns and rural areas may have coarse terrain data only.
- A shade map cannot account for cloud cover, awnings, scaffolding, seasonal leaf loss or recently constructed buildings, so on-site checking remains necessary for decisions that matter.
What is a shade map, and what is it actually showing?
A shade map is an interactive map layer that renders the shadow cast by physical objects at a specific moment. You pick a point on the map, set a date and a time, and the tool draws which surfaces are in direct sun and which are in shade. Most implementations include a time slider, so you can scrub through a day and watch shadows sweep across streets, gardens and rooftops.
Two separate computations sit behind that picture. The first is the sun’s position — its altitude above the horizon and its azimuth, or compass bearing — for the given latitude, longitude, date and time. The second is a height model: a digital representation of the ground surface plus everything standing on it, such as buildings and, in better datasets, trees. The tool projects each object’s height along the sun’s bearing to work out the ground it obscures.
The result is a prediction of direct sunlight only. Shaded areas in reality are rarely dark; they receive diffuse light scattered by the sky and reflected off nearby surfaces. A shade map answers the question “is the sun hitting this spot?”, not “how bright or how hot is this spot?”.
Why shade mapping is being discussed now
Interest in shade tools tends to surface in technical communities when a well-made example is shared and people compare it against the alternatives they already use. Discussion threads typically move quickly from the tool itself to the data behind it: which cities are covered, whether trees are included, how recent the building footprints are, and what happens at the edges of the modelled area.
There is also a broader driver. Heat in built-up areas has become a mainstream planning concern, and shade is one of the few interventions that is cheap, visible and immediately felt. Tools that make shade legible at street level fit into that wider conversation, alongside tree-planting programmes and cool-surface schemes. The exact scale and outcomes of such programmes vary enormously by country and city, and are not something a shade map itself can measure.
The background a newcomer needs
Solar position calculation is a solved problem. Standard algorithms return the sun’s altitude and azimuth for any point on Earth at any instant, with errors far smaller than anything that matters for shadow drawing. If a shade map gets the sun wrong, it is almost always a time zone, daylight saving or coordinate error rather than an astronomical one.
The harder part is the surface model. Elevation data comes in two broad flavours. A digital terrain model describes bare ground with buildings and vegetation stripped out. A digital surface model keeps everything standing on the ground, which is what shadow casting requires. Surface models are commonly derived from lidar surveys flown by aircraft or drones, from photogrammetry, or from satellite-derived products at coarser resolution.
Separately, many tools use building footprints with an attached height attribute, often drawn from open mapping databases or municipal open-data portals. Footprint-plus-height gives clean, blocky shadows and is cheap to render, but it flattens roof shapes, ignores balconies and overhangs, and misses trees entirely unless a vegetation layer is added. Lidar-derived surfaces capture far more, including tree canopies, but the data is heavier, patchier in coverage and can be years old.
Who is affected, and how
Cyclists and walkers use shade maps to choose a route on a hot day, which matters most for people whose commute is unavoidable and who cannot simply travel at a cooler hour. Runners and dog walkers use them to time outings.
Anyone assessing a property benefits. A flat viewed on a bright winter morning may sit in permanent shadow through the summer if a taller block stands to its south; a shade map lets you check the pattern across the year before signing anything. Gardeners use the same trick in reverse, matching plants to the hours of direct sun a bed actually receives.
Solar installers and self-builders care about shading because a partially shaded panel array can underperform badly relative to a naive yield estimate. Photographers and film crews use shade tools for scouting, and outdoor event organisers use them to place seating and stalls. Urban planners and researchers use more specialised versions of the same modelling, usually with better data than public tools can access.
Where informed people disagree
The main disagreement is about what level of accuracy is honest to present. A crisp, confident shadow drawn from a coarse dataset can imply precision the model does not have. Some argue tools should visibly communicate uncertainty or data vintage; others say a rough answer that is directionally right is more useful than none, provided users understand the limits.
Trees are a second point of contention. Including canopy data makes summer shade far more realistic but introduces a seasonal problem, since deciduous trees cast very different shadows in winter. Handling this properly requires species and phenology assumptions that most tools do not make.
There is also debate about whether direct-sun modelling is the right proxy for thermal comfort at all. Perceived heat depends on air temperature, humidity, wind, radiation reflected from walls and pavements, and surface materials. Shade is a strong single factor, but a shade map is not a comfort map, and treating it as one can lead to poor conclusions.
How to use a shade map in practice
Start by confirming the tool has real data where you are looking. Zoom in and check whether individual buildings appear with plausible heights, and whether trees are represented at all. If the area renders as flat ground, any shadow shown is coming from terrain alone.
Set the date deliberately rather than accepting today. For a worst-case summer check, use a date near the summer solstice; for a worst-case winter check, use one near the winter solstice. Confirm the tool is using local time and handling daylight saving, ideally by checking that shadows point roughly north at local solar noon in the northern hemisphere, and roughly south in the southern.
Then scrub the time slider across the whole day rather than sampling one hour. The useful output is the pattern — when sun arrives, how long it lasts, and when it goes — not a single frame. Cross-check anything consequential against a second source, such as satellite imagery for recent construction, and finish with a site visit at the hour that matters.
What to watch next
Watch for improvements in open surface data, particularly national lidar programmes releasing higher-resolution products and municipalities publishing tree inventories. Better vegetation modelling, including seasonal canopy states, would close the most obvious accuracy gap in current tools.
Also watch how shade information is integrated into everyday navigation. Shade-aware routing is a natural extension of existing pedestrian and cycling directions, though it depends on both good surface data and a willingness to accept slower routes. Finally, expect continued scrutiny of how these tools communicate uncertainty, which is likely to shape whether they are treated as planning aids or as authoritative answers.
Frequently asked questions
Is a shade map accurate enough to rely on?
The sun position calculation is very accurate; the shadows are only as good as the height data. In well-surveyed cities with recent lidar and building heights, results are usually close to reality. In areas with sparse or outdated data, shadows may be missing or wrongly shaped. Treat the output as a strong first estimate and verify on site before making a costly decision.
Do shade maps include trees?
Some do and some do not. Tools built on building footprints with height attributes typically omit vegetation entirely, while those built on lidar-derived surface models often capture canopies. Even when trees are included, the data usually reflects a single survey date and does not model seasonal leaf loss, so winter shade under deciduous trees is commonly overstated.
Can I use a shade map to plan solar panels?
It is a useful screening step for spotting obvious obstructions such as a neighbouring building, chimney or mature tree. It is not a substitute for a proper shading assessment, which measures the horizon from the panel location and models annual yield losses. Use the map to decide whether a site is worth surveying, then have the installation assessed with dedicated tools.
Why do shadows look wrong at sunrise and sunset?
Near the horizon the sun’s altitude is very low, so shadows become extremely long and small errors in object height are hugely magnified. Atmospheric refraction also lifts the apparent sun slightly, and local terrain beyond the modelled area may block the sun earlier than the map suggests. Low-angle results should be read as approximate rather than precise.
What is the difference between a terrain model and a surface model?
A digital terrain model represents bare ground with buildings and vegetation removed, which is useful for hydrology and slope analysis. A digital surface model keeps everything standing on the ground, including roofs and tree canopies. Shadow casting in built-up areas needs a surface model; using terrain alone produces shadows from hills and valleys but none from the buildings around you.
Are shade maps free to use?
Availability varies. Several tools are free for casual browsing, with paid tiers for higher-resolution data, historical or future date ranges, or programmatic access. The underlying datasets are often open, published by national mapping agencies or municipal open-data portals, but processing them into a usable interactive map is what such services charge for.
Sources and further reading
- National mapping and geospatial agencies, for published lidar, terrain and surface elevation datasets and their documented resolution and survey dates.
- Open collaborative mapping projects, for building footprint and height attributes and guidance on how completely those attributes are populated.
- Peer-reviewed urban climate and remote sensing literature, for methods on solar radiation modelling, sky view factor and thermal comfort indices.
- Municipal open-data portals, for tree inventories, building registers and heat-related planning documents at city scale.
Surfaced from the hackernews signal “a shade-mapping tool”. AI-assisted draft, editorially reviewed.
