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1Clear out junk files and repair common Windows errors2Fix the driver behind crashes, sound loss and screen glitches3Repair Windows errors before they cause bigger problemsUse Sentinel-3 for ocean variables, broad-area land and vegetation condition, sea- or land-surface temperature, fire context, and surface-height measurements. Choose Sentinel-2 when you need detailed optical imagery of land, crops, or vegetation. Choose Landsat when a long, consistent land record, 30 m multispectral imagery, or thermal measurements matters most. Sentinel-2 and Landsat often work well together; Sentinel-3 usually complements them because its pixels cover a much larger area.
The right choice depends on the variable you need, the size of the feature, the time span, cloud conditions, and the processing level—not just the satellite name or its nominal revisit interval.
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Quick answer: start with the question, not the satellite
| If you need to measure or monitor | Start with | Why it fits | Check before committing |
|---|---|---|---|
| Ocean colour, chlorophyll-related water properties, sea-surface temperature, sea-surface height, or very broad environmental conditions | Sentinel-3 | It carries dedicated ocean-colour, temperature, and radar-altimetry instruments with systematic, wide-swath coverage. | Select the correct instrument and product level, and confirm that the target is large enough for its coarse sampling. |
| Detailed optical mapping of fields, forests, wetlands, or built-up land | Sentinel-2 | Its multispectral bands and fine headline sampling are designed for land and vegetation analysis. | Check the resolution of the specific band, cloud cover, viewing date, and whether the required variable is optical. |
| Long-term land-change analysis, multispectral observations, or land-surface temperature | Landsat 8/9 plus the historical archive | Landsat combines a deep record with multispectral, panchromatic, and thermal observations. | Choose the appropriate mission, collection, and Level-1 or Level-2 product for your time period. |
| More frequent land observations at medium or fine scale | Sentinel-2 and Landsat together | Their offset acquisition schedules can increase sampling opportunities. | Harmonize bands, calibration, geometry, cloud masks, pixel size, and processing before treating measurements as comparable. |
| Broad-area temperature or fire context alongside detailed land imagery | Sentinel-3 plus Sentinel-2 or Landsat | Sentinel-3 supplies regional context while the other mission resolves smaller land features. | Match the pixel size and acquisition time to the phenomenon; coarse pixels cannot resolve small parcels or objects. |
Core specifications side by side
The figures below are current official mission specifications, not results from a single head-to-head experiment. A nominal revisit describes the spacecraft constellation or acquisition cycle; it does not promise a cloud-free, usable image on a particular date.
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| Mission or sensor | What it measures and spatial sampling | Swath or coverage detail | Nominal timing |
|---|---|---|---|
| Sentinel-3 OLCI | Ocean and Land Colour Instrument with 21 spectral bands from 400–1,020 nm; 300 m spatial resolution. | 1,270 km swath. | ESA describes global coverage about every two days for the two-satellite constellation. |
| Sentinel-3 SLSTR | Visible/near-infrared and shortwave-infrared channels at 500 m; thermal-infrared channels at 1 km. Used for sea- and land-surface temperature and fire-related measurements. | Designed for systematic ocean and land monitoring. | Approximate ocean revisit is one day for the two-satellite constellation. |
| Sentinel-3 SRAL and topography products | Radar altimetry for sea-surface and other surface-height information. | Equatorial ground-track spacing is 47 km after a 27-day repeat cycle. | Useful for large-scale height and ocean dynamics rather than parcel-scale mapping. |
| Sentinel-2 multispectral imaging | 13 optical bands with a 10 m headline resolution; individual bands have different native resolutions. | 290 km swath. | Two-satellite constellation revisit at the equator is five days, with more frequent opportunities at higher latitudes. |
| Landsat 8 OLI and TIRS | OLI provides 15 m panchromatic and 30 m multispectral imagery. TIRS measures land-surface temperature in two thermal bands. | 185 km swath. | Landsat 8 and Landsat 9 each image the Earth on a 16-day cycle, offset to provide an eight-day interval. |
Instrument specifications are documented by ESA for Sentinel-3, ESA for Sentinel-2, and the USGS Landsat 8 mission page. The Sentinel-2 constellation page explains its latitude-dependent revisit, while the USGS Landsat acquisition page describes the Landsat 8/9 timing.
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What Sentinel-3 is designed to do
Sentinel-3 is a multi-sensor environmental mission for systematic measurements of oceans, land, ice, and atmosphere at large scales. It is not simply a sharper version of a land-imaging satellite. Its value comes from combining complementary measurements that describe the state of a region or water body.
OLCI: ocean colour, land colour, and vegetation signals
OLCI records reflected light across 21 bands spanning the visible and near-infrared range. Those bands support ocean-colour products, water-quality analysis, land reflectance, and broad vegetation indicators. The wide swath makes it efficient for regional and global monitoring, but the 300 m sampling means a small field, narrow river, individual building, or isolated fire may occupy only part of a pixel.
For water studies, OLCI is the natural Sentinel-3 starting point when the question concerns colour-derived properties rather than temperature or height. For land, it is most useful when the objective is regional condition, phenology, or change over areas large enough to survive mixed pixels.
SLSTR: temperature and fire-sensitive measurements
SLSTR observes visible, near-infrared, shortwave-infrared, and thermal-infrared channels. Its temperature products address both sea-surface and land-surface conditions. Shortwave and thermal channels also provide information useful for detecting and characterizing fire activity at broad scale.
SLSTR is valuable when temperature is the variable itself or when a rapid regional screen is needed. It should not be mistaken for a high-resolution thermal camera: its thermal sampling is coarser than the optical land products many users associate with field mapping. Use a finer mission to inspect the exact parcel or structure that triggered a broad SLSTR signal.
SRAL and surface-height information
Sentinel-3’s radar-altimetry package measures sea-surface height and supports other topographic and ocean-dynamics products. These observations answer a different question from optical reflectance: they describe elevation or height-related behavior rather than the colour or texture of a surface. The ground-track spacing and repeat pattern make SRAL appropriate for large-scale water and geophysical analysis, not dense mapping of small inland features.
Products and delivery time
ESA describes separate product chains for SLSTR, OLCI, SRAL, and combined OLCI/SLSTR processing, covering ocean colour, land reflectance, temperature, topography, and vegetation. Core Sentinel-3 products are typically available within three hours of sensing, although the exact delay depends on the product and processing stage. Review the current Sentinel-3 data-products documentation before designing an operational pipeline.
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Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstallESA’s current facts page lists Sentinel-3C as launched on 15 September 2026. Mission status and catalogue details can change, so verify the current constellation and access instructions on the Sentinel-3 facts and figures page.
When Sentinel-2 is the better choice
Sentinel-2 is the fine-detail optical option in this comparison. Its 13-band multispectral design supports vegetation indices, crop and forest mapping, water and wetland delineation, burn-scar analysis, land-cover classification, and many other reflectance-based workflows.
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Do not treat “10 m” as the resolution of every band
The often-quoted 10 m value is a headline mission specification. Native sampling differs by band and by product, so a workflow that uses a red-edge, shortwave-infrared, or other non-10 m band must use that band’s stated resolution or a deliberate resampling method. Resampling changes the grid; it does not create new spatial information.
Revisit, latitude, and clouds
ESA states that the two-satellite constellation revisits the equator every five days and can revisit more frequently at higher latitudes. A five-day opportunity can still yield no usable image when clouds, haze, snow, shadows, or unsuitable illumination obscure the target. Build a cloud and quality-screening rule into the analysis instead of counting calendar passes as observations.
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Sentinel-2C and coordination with Landsat
Sentinel-2C joined the mission after its launch on 5 September 2024. ESA also describes coordination with Landsat 8 intended to produce an average three-day revisit over the equator for comparable products. That is a coordination goal, not a guarantee that every location will receive a clear, perfectly matched image every three days.
When Landsat is the better choice
Landsat is the strongest option when historical continuity, medium-resolution multispectral data, or thermal measurements determine the project. Landsat 8’s OLI observes visible, near-infrared, and shortwave-infrared radiation, while TIRS supplies two thermal bands for land-surface temperature. The panchromatic band can support sharper display or pan-sharpening workflows, but pan-sharpening should not be presented as additional independent multispectral information.
The 8/9 acquisition pattern
Landsat 8 and Landsat 9 each have a 16-day imaging cycle and are offset by eight days. The combined pattern improves temporal sampling, but clouds and acquisition geometry still determine whether a scene is usable. Acquisition cadence is not the same as a guaranteed delivery or cloud-free revisit.
Archive and product generations
Landsat’s long-running record is often more important than a single scene’s nominal resolution. For a change study, keep the mission, collection, processing version, seasonal window, and quality masks consistent where possible. If older scenes come from a different mission or product generation, document the band definitions, calibration, and atmospheric-correction differences before calculating a trend.
USGS describes Collection 2 Level-2 surface-reflectance and surface-temperature products and links to known-issue and reprocessing information. Product-generation timing varies by mission and processing stage, so consult the USGS Collection 2 Level-2 documentation for the exact product.
Access and delivery
USGS says Landsat’s no-cost open-data policy remains in effect and provides search and download options through its Landsat data-access page. USGS also states that Level-1 products can be available for download within six hours of acquisition on the acquisition page; that timing should not be generalized to every Level-2 or derived product.
Choose by measurement, feature size, and time span
1. Name the physical variable
Write down whether the project needs reflectance, a vegetation index, water colour, temperature, fire radiance, surface height, or a classified land-cover label. Optical missions cannot substitute for a thermal or altimetry measurement simply because their images look sharper. Conversely, a temperature product will not provide the spectral detail needed for species or crop-type discrimination.
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2. Estimate the smallest feature that must be resolved
Compare that feature with the sensor’s native pixel size and the expected mixed-pixel environment. A target that is smaller than a pixel may still influence a pixel value, but its signal will be diluted by soil, water, canopy, or neighboring objects. Sentinel-3 is generally the wrong starting point for a small parcel, narrow road, individual building, or small burn scar; Sentinel-2 or Landsat is usually more appropriate, subject to the relevant band and cloud limits.
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3. Set the time requirement
For a long historical trend, begin with Landsat’s archive and add newer missions only after checking comparability. For frequent optical snapshots, begin with Sentinel-2 and consider Landsat scenes as additional observations. For rapidly changing regional temperature or ocean conditions, Sentinel-3’s wide coverage and frequent opportunities may outweigh its coarse pixels.
4. Define an acceptable observation
Decide how much cloud, haze, snow, shadow, saturation, or geolocation error is acceptable. A nominal revisit is only an opportunity. Filter by cloud probability or quality flags, inspect the scene, and record the actual acquisition date used in every analysis.
5. Select the product level before downloading
Level-1 data are closer to calibrated sensor measurements; Level-2 products apply additional geophysical or atmospheric processing. Surface reflectance, surface temperature, ocean colour, and altimetry products are not interchangeable. Confirm the variable, projection, scale factor, quality flags, and processing version in the product documentation.
6. Verify access and latency
Sentinel-3 access is routed through ESA’s Copernicus data services as described on its facts page. Landsat search and download are documented by USGS. Operational users should test authentication, catalogue filters, file formats, and actual delivery latency with a representative date before promising a service-level schedule.
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Decide how satellite estimates will be checked against field measurements, weather stations, buoys, airborne data, or a trusted reference product. Validation should use the same spatial support and acquisition window as the satellite measurement; comparing a coarse regional pixel with a point measurement without accounting for scale can produce misleading disagreement.
Using Sentinel-2 and Landsat together
Combining the two missions can increase the number of usable land observations, especially when one mission is cloudy on a date when the other is clear. The combination is most defensible when the study uses comparable surface-reflectance or temperature products, a documented bandpass conversion or harmonization method, and consistent quality masks.
What must be harmonized
- Spectral response: similarly named red, near-infrared, or shortwave-infrared bands do not necessarily measure identical wavelength ranges.
- Spatial support: aggregate or resample deliberately, and state which grid is authoritative.
- Viewing geometry: sun angle, sensor look angle, and bidirectional reflectance can change the observed value.
- Atmospheric correction and calibration: use products with compatible processing assumptions and track reprocessing versions.
- Cloud and shadow masks: apply mission-specific quality flags before comparing dates.
- Time window: vegetation, water level, temperature, and fire conditions can change between acquisitions.
ESA’s mission pages support the high-level complementarity of Sentinel-2 and Landsat, but they do not establish one universal cross-calibration workflow. The method must be chosen for the variable, geography, and study period.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Adding Sentinel-3 to a finer-resolution workflow
Sentinel-3 can provide regional context around a Sentinel-2 or Landsat study area. For example, a broad temperature or vegetation-condition anomaly can identify where to inspect detailed imagery, while a coarse fire or water signal can provide context for a local map. Use the missions at their natural scales: summarize Sentinel-3 over a region or use it as a screening layer, then analyze the smaller feature with the finer mission.
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Do not force Sentinel-3 pixels onto a parcel-scale map or interpret a regional average as a measurement of every field inside it. Mixed land cover, shoreline effects, small clouds, and geolocation differences can dominate the signal when the target is near the sensor’s spatial limit.
Common mistakes and how to correct them
Mistake: choosing by revisit alone
Why it fails: a nominal pass can be cloudy, hazy, snow-covered, or unsuitable for the target variable.
Correction: model usable observations after quality screening and report the actual dates retained.
Mistake: assuming all Sentinel-2 bands are 10 m
Why it fails: the 10 m figure is a headline specification, not a promise for every band.
Correction: read the band and product metadata, then choose a documented resampling strategy.
Mistake: using Sentinel-3 for a small object
Why it fails: a coarse pixel mixes the object with its surroundings and cannot preserve parcel-level boundaries.
Correction: use Sentinel-2 or Landsat for the local feature and reserve Sentinel-3 for regional context or variables it uniquely measures.
Mistake: treating Landsat and Sentinel-2 values as interchangeable
Why it fails: bandpasses, calibration, geometry, atmospheric correction, and pixel grids differ.
Correction: harmonize explicitly, validate on the study area, and document the conversion or model.
Mistake: confusing acquisition cadence with product availability
Why it fails: a satellite may acquire a scene before the required processing level is generated or published.
Correction: distinguish sensing time, Level-1 delivery, Level-2 generation, and downstream catalogue availability.
Mistake: mixing archive generations without checking processing
Why it fails: reprocessing, calibration updates, and changed quality flags can create artificial breaks in a time series.
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Practical selection examples
Mapping crop vigor within individual fields
Start with Sentinel-2 because its optical bands and finer land sampling are suited to field-scale vegetation analysis. Add Landsat to fill temporal gaps or extend the record, but harmonize the reflectance products and report the different acquisition dates. Sentinel-3 can indicate regional crop conditions but is generally too coarse for assigning a value to each small field.
Tracking a large lake’s colour and temperature
Use Sentinel-3 OLCI for broad water-colour observations and SLSTR for temperature-related products. Sentinel-2 can inspect shorelines, bays, and smaller structures that the coarser pixels cannot resolve. Choose the product chain based on whether the primary variable is colour, temperature, or height.
Building a multi-decade land-change series
Begin with the Landsat archive and establish a consistent seasonal and processing baseline. Add Sentinel-2 for more recent, finer optical observations when the analysis can account for different bands and viewing conditions. Use Sentinel-3 only for broad environmental context or variables such as regional temperature that are not the central land-reflectance record.
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Sentinel-3’s temperature and fire-sensitive channels can provide broad, frequent situational awareness. Follow up with Sentinel-2 or Landsat to map the affected boundary and assess vegetation or surface changes at finer scale, subject to smoke and cloud contamination.
Studying sea-level or large-water-surface changes
Start with Sentinel-3 SRAL and its relevant topography products because the measurement is surface height rather than optical colour. Use optical imagery from Sentinel-2 or Landsat only for complementary shoreline, land-cover, or water-extent analysis.
Bottom-line decision rule
Choose the mission that measures your variable at a scale your target can support. Sentinel-3 is the specialist for wide-area environmental monitoring, ocean colour, temperature, fire context, and surface height. Sentinel-2 is the detailed optical land mission. Landsat is the continuity and thermal choice, with a long archive and an offset 8/9 acquisition pattern. Combining Sentinel-2 and Landsat can improve land-observation frequency, while Sentinel-3 adds regional context rather than replacing fine-resolution imagery.
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