Germany's PV Atlas

EarthPV CalibrationGoldCalibrated above and below
the 400 m² floor
Germany PV capacity, by 0.1° cell
11 km × 11 km cells · log scale
MWp / cell
hand-mapped OpenStreetMap capacity (ring grows with MWp)
hand-checked calibration area (hover for detail)
0MWp
Best estimate, the highest defensible figure
0
Training data hand-mapped in OpenStreetMap, ≥400 m²
0
Training data hand-mapped in OpenStreetMap, <400 m²
0
of 0.1° cells have density-matched sub-400 m² calibration
Capacity
The same Sentinel-2-detectable total, by installation size
Capacity per size bin, rooftop vs ground-mount
linear scale · MWp
rooftop
ground-mount
rooftop, extrapolated beyond calibration
The same total photovoltaic capacity detectable with Sentinel-2, re-cut by installation size instead of geography: rooftop bars stack across every bin, while ground-mount only shows up at ≥400 m² -- the two detectors split the total by placement and size, not size alone.
Capacity
The same total, by method
Total Capacity
0 MWp
0 MWp
roofclf alone (its own ≥400 m² replacement plus the sub-400 m² central estimate) supplies 59% of Best; TerraMind segmentation (29%) and direct OSM mapping (13%) split the rest.
Panel orientation
Fitted tilt & azimuth, from Sentinel-2 glint
Tilt (radius) × Azimuth (angle) 0 measured
rooftop generator ground plant unreachable by this sensor's fixed overpass time
0%
of ≥ 1,000 m² installations get a pose in this plot at all -- the rest never produce two self-consistent spikes, so there's nothing to fit
≥1 spike, no fittable pose; 0%
no glint signal at all 0%
azimuth range observed
tilt IQR observed

What is PV glint and how is it detected?

PV Glint is a brief, brighter-than-diffuse flash where a panel's specular reflection lines up with the sun and Sentinel-2's fixed overpass geometry on one date -- see the method page for the full derivation and an annotated image gallery. A single spike can't be checked for self-consistency -- 0% of installations glint once (or on dates that disagree on a panel geometry) and so are correctly detected as "PV is probably here" but carry no orientation information.

Why the plot only fills part of the circle

Sentinel-2 crosses this latitude at a fixed ~10:30 local time, so across two full years of imagery the sun's azimuth at the moment of every overpass never once swings west of due south -- a panel facing southwest, west, or north cannot glint into this sensor no matter how long you wait. That's a sensor limit, not a property of rooftops here: the shaded wedge (0° wide) marks orientations this survey cannot observe at all, not orientations known to be empty. Nothing is plotted there, because nothing was measured there.

Data: . Validated = a single (tilt, azimuth) explains ≥ 2 independent spike dates via the specular reflection condition, tolerance 3°. Point size ∝ √(installation area). Full derivation of the glint signal this pose fit is built on: the method page. Annotated Sentinel-2 / high-res examples of what a validated spike actually looks like in the source imagery: the image gallery.

Background
How to read these numbers
How confident should you be in this? preliminary results, sampling caveats, independent corroboration+

Best estimate: 88,709 MWp, with a 90% range of 78,597–101,104 MWp. That range covers two specific, measured sources of uncertainty -- but not everything that could move this number. Below: what's inside the range, what isn't, and how it compares to unrelated data sources.

What's inside the range:

  • The two "panel area to power" conversion numbers. One converts rooftop panel area to kWp, the other converts open-ground solar-farm land to kWp. Both are measured against real, confirmed power plants rather than assumed, but each carries its own uncertainty.
  • How well the detection model finds panels of different sizes. Its measured precision and recall were checked installation-size by installation-size, and that check itself has a margin of error.

What's outside the range -- and can't be added back in with more arithmetic:

  • Getting the national total right is not evidence the geography is right. Cross-validated, this method's German national figure lands within a few percent of the register while the median municipality is out by roughly half, because over-prediction of the densest tenth of municipalities cancels under-prediction of the other ninety percent. Three different models whose municipal errors spanned 38–64% all produced nearly the same national number. What a grid model is consumed for is the geography, not the total.
  • In Germany, multiplying roof area by a constant does as well as the classifier. Against a per-municipality roof-area baseline, the classifier's median error (48.4%) is worse than the baseline's (37.8%). Where rooftop PV is close to ubiquitous, capacity is nearly proportional to roof area by construction. The classifier earns its keep where PV is rare -- in Pakistan it cuts the same error from 88.9% to 26.5% -- which is the regime it was built for and Germany is not.

Treat this as an early-stage estimate from an active research pipeline, not a finished census. What's genuinely new here -- a reproducible way to estimate distributed solar from free satellite imagery and open-source AI, in places where official statistics are sparse or absent -- holds regardless of whether any single number on this page turns out exactly right. Expect these figures to keep moving as the evidence behind them grows.

There are no hand-mapped ground-truth areas behind this page, and for the small-panel half there do not need to be. Registration in Germany's Marktstammdatenregister is legally mandatory rather than voluntary, and it publishes totals per municipality -- which is exactly the quantity the small-panel estimator produces. The conversion from flagged roof area to kilowatts was therefore fitted against the register across 9,674 fully-covered municipalities, at 0.2793 kWp per m² of credited roof area, and applied countrywide as a genuine out-of-sample test. What a register cannot substitute for is a precision check on small installations: below 30 kWp it publishes no coordinates at all, so there is no way to ask whether a particular flagged roof really carries panels.

A complete national register puts the Best estimate above too high. The Marktstammdatenregister records roughly 74.8 GWp of PV in Germany, below the figure this page reports, so read these tiers as geography -- where capacity sits -- rather than as a national total. The hand-mapped OpenStreetMap component was reconciled against the register in September 2026 and both placements now sit within about 10% of it; what remains unreconciled is the model's own detections and the small-panel half. Every other country in this project would need a register of this kind to make the same statement, and does not have one.

Data
Download the data behind this atlas
Download the underlying data capacity parquets, calibration boundaries, pose survey, raw detections, model checkpoint+
Live OSM PV, not this snapshot -- Overpass query
[out:json][timeout:180]; area ["boundary"="administrative"] ["admin_level"="2"] ["ISO3166-1"="DE"] ->.searchArea; ( nwr["power"="generator"]["generator:source"="solar"](area.searchArea); nwr["power"="plant"]["plant:source"="solar"](area.searchArea); ); out geom;
Paste into overpass-turbo.eu for an interactive map and GeoJSON export, or POST it as the data parameter to https://overpass-api.de/api/interpreter from a script. The raw-detections download above predates this page and will go stale as mappers keep editing; this query always reflects live OSM state.
Raw data

The capacity per grid cell shown on the map, as CSV. One row per 0.1° cell, generated in your browser from the data this page is drawing, so it is exactly the numbers above. lon0/lat0 are the south-west corner of the cell. The GeoParquet carries the cell polygon in EPSG:4326, so it opens directly in QGIS or GeoPandas.

Download GeoParquet