Honest answers about what satellite imagery can and can't do.
SatMCP shows exactly what the satellite captured — clouds, haze, and all. Services like Google Earth hand-pick the clearest frames over months or years and stitch them together into a perfect-looking mosaic. That's beautiful, but it's not what the sky actually looked like on a given day. We show the real thing.
That's the satellite's ground track. Polar-orbiting satellites sweep narrow strips across Earth as it rotates below them. The black areas simply haven't been overflown on this particular orbit — a neighbouring pass, typically a few days later, will fill them in.
Mostly yes. We render Sentinel-2 and Landsat scenes using their red, green, and blue bands, so the result should look close to what your eyes would see from 500 km up. Some images may appear slightly washed out or hazy due to thin atmosphere — that's real atmosphere, not a rendering artefact.
That's Landsat 7's scan line corrector (SLC) failure. The corrector broke in May 2003 and was never repaired, leaving distinctive striped gaps across every image Landsat 7 collected until it was retired. It's a piece of space history baked into the data.
Simple: no satellites! Landsat 1 launched in 1972, and even that archive is patchy and low-resolution by today's standards. Sentinel-2 — which provides the sharp 10 m imagery we rely on most — only started capturing Earth from 2015 onward. Before that, you're working with whatever old film scanners and early digital sensors managed to record.
Quite recent. Sentinel-2 revisits any given spot every five days (or less at higher latitudes). Landsat 8 and 9 together revisit every eight days. Most locations will have usable imagery from the past few weeks. Cloud cover may occasionally delay useful coverage further.
Because satellites only capture your location when they pass overhead. If no satellite pass exists at that exact moment, there is nothing to return for that timestamp. SatMCP uses the closest available pass for your requested date window. See what satellites SatMCP uses for coverage differences across sensors.
Seasons, sun angle, snow cover, flooding, smoke, and atmospheric conditions all change how a location looks from orbit. A summer scene over the Alps looks nothing like a January capture. That variability is precisely why date-specific imagery is useful — and interesting.
Yes. No account, no API key, no billing. Just ask. The underlying satellite data is publicly funded and freely available; we just make it easier to access by place name and date.
Primarily ESA's Sentinel-2 constellation (10 m resolution, coverage from 2015) and NASA/USGS Landsat 8 and 9 (30 m resolution). For broader, frequent coverage we also use MODIS imagery from NASA's Terra and Aqua missions. Landsat's archive stretches back to 1972 for historical searches, though quality and coverage vary significantly for older dates.