Sentinel-2 vs Landsat: Which Satellite Data Should You Choose?
- Primary Signal: Sentinel-2 vs Landsat: Which Satellite Data Should You Choose?
- Overview: Sentinel-2 offers sharper 10-metre imagery and five-day revisits; Landsat offers a deeper archive back to the 1970s. Compare resolution, revisit time, bands, and licensing to pick ...
- Verification: Analyzed and compiled by FreeSky GeoData editorial monitoring desk.
Sentinel-2 and Landsat are the two workhorses of free satellite imagery, and beginners often waste hours wondering which one to download first. The honest answer is that neither is better in general; each wins for particular jobs. Sentinel-2, from the European Copernicus programme, gives sharper images and more frequent revisits, which suits current conditions and small features. Landsat, run by the United States Geological Survey and NASA, gives a longer, steadier record, which suits change over decades. Knowing the trade-offs in advance lets you choose in minutes and defend the choice in your project notes.
Sentinel-2 records its visible and near-infrared bands at 10 metres per pixel, with other bands at 20 or 60 metres. Landsat records most bands at 30 metres, with a 15-metre panchromatic band that can sharpen a colour image. In practice, Sentinel-2 can outline a small field, a pond, or a housing block more cleanly, while Landsat can blur those edges together. If your study area is a single farm, a neighbourhood, or a small catchment, Sentinel-2 is usually the better starting point. If your area is a whole district, province, or river basin, Landsat's coarser pixels matter less, and its archive may matter more. Always check the smallest feature you must recognise against the pixel size before downloading.
Sentinel-2's two satellites together revisit most places about every five days, while Landsat revisits about every sixteen days, or every eight days when its two current satellites are combined. More frequent revisits matter most in cloudy regions and fast-changing seasons, because they raise your odds of finding a clear scene close to the date you need. A crop that changes week by week, a flood that rises and falls in days, or a construction site that moves quickly all favour Sentinel-2. For slow change, such as urban growth over ten years or forest loss over twenty, revisit frequency matters far less than having comparable images across the whole period, and Landsat's consistency wins.
Both missions carry the visible, near-infrared, and shortwave-infrared bands that drive vegetation, water, and built-up indices, and both publish their data openly. Sentinel-2 adds red-edge bands that help with crop stress and chlorophyll work, while Landsat adds a thermal band that helps with surface temperature studies. Landsat's archive reaches back to the 1970s, so it is the default for any question that starts with how much has changed since an earlier decade. Sentinel-2's record starts in 2015, which is ample for recent change but cannot answer older questions. Landsat data is United States public domain, and Sentinel-2 data is free and open with attribution requested, so either can be used in published work with a proper credit line.
Use Sentinel-2 when the job is current, detailed, or fast-moving: this season's crop, this month's flood extent, or a small study area where 10-metre detail matters. Use Landsat when the job is historical, broad, or comparative over decades: land-cover change since the 1990s, long-term lake levels, or a regional trend that needs the same sensor family across many years. When in doubt, download a small sample of both for the same area and date, display them side by side in QGIS, and see which one answers your question more clearly. That half-hour test beats a week of second-guessing, and it gives you a documented reason for the choice in your final map.
There is no prize for loyalty to one satellite. Good GIS work picks the sensor that fits the question, the scale, and the time span, and says so plainly. Start with Sentinel-2 for sharp, current detail and Landsat for deep history, and you will rarely pick wrong.
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