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This distinction matters because reflectance and temperature are different measurements. Sentinel-2 cannot replace a thermal sensor, while a planned mission cannot support a current production workflow. The right choice also depends on spatial scale, cloud-free opportunities, atmospheric correction, product level, and whether you need a continuous historical record.
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At-a-glance choice
| Analysis need | Best fit among these missions | Reason |
|---|---|---|
| Land-surface temperature now | Landsat 8/9 | Operational thermal bands and USGS Collection 2 Level-2 surface-temperature products are available now. |
| Optical land-cover or vegetation detail | Sentinel-2 | Its multispectral instrument provides visible, near-infrared and shortwave-infrared observations; there is no thermal instrument. |
| Frequent, high-resolution thermal observations in the future | TRISHNA | CNES lists planned 60 m products, a three-day equatorial revisit and a 2027 launch target. |
| Current thermal plus optical time series | Landsat 8/9, optionally paired with Sentinel-2 | Landsat supplies both measurement types; Sentinel-2 can add optical observations between suitable Landsat scenes. |
| Long-term continuity | Landsat archive | USGS maintains Collection 2 products for Landsat 8/9 and earlier missions. |
A nominal revisit is an acquisition opportunity, not a promise of a cloud-free, usable image. Check cloud cover, view geometry and product quality for the exact place and date before committing to a method.
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Satellite products answer different physical questions. Surface reflectance describes how much light a surface returns in selected spectral bands. Land-surface temperature (LST) is an estimate of thermal emission, normally requiring a thermal infrared measurement plus atmospheric and emissivity corrections. A high-resolution optical image cannot be converted into a measured temperature simply because it has many bands.
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For land-cover classification, crop vigor, burn scars, turbidity proxies or shoreline mapping, multispectral reflectance may be sufficient. For heat stress, urban thermal patterns, evapotranspiration inputs or the temperature of a lake, reservoir or coastal zone, you need thermal observations or a validated model that uses them. Decide this first; then select the mission and processing level.
TRISHNA: a planned thermal-and-optical mission
What the mission is designed to measure
TRISHNA (Thermal infraRed Imaging Satellite for High-resolution Natural resource Assessment) is a joint CNES–ISRO mission. Its payloads are a four-channel long-wave thermal-infrared sensor and a seven-band visible, near-infrared and shortwave-infrared sensor. The stated objectives include retrieving surface temperature and emissivity, closing surface-energy budgets, estimating evapotranspiration, monitoring vegetation water stress, and studying inland and coastal water.
CNES currently lists TRISHNA as in development with a scheduled launch year of 2027. That is a target, not a guarantee: launch dates and commissioning schedules can change, and no operational TRISHNA imagery should be assumed before an official release.
Planned resolution and revisit
CNES describes 60 m products and a three-day revisit at the equator. ISRO gives approximately 57 m land and coastal spatial resolution at nadir, while oceanic and polar regions are listed at 1 km resolution. These figures describe planned mission performance and products; they are not measurements from an already available archive.
The three-day figure is especially useful for users planning future thermal time series, but it still represents an opportunity to observe. Clouds, viewing geometry, downlink schedules and quality flags can reduce the number of scenes suitable for analysis.
Planned product levels
CNES GEODES describes a product chain rather than a single image download:
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- L1C: top-of-atmosphere reflectances and radiances with a cloud mask.
- L2A: surface reflectance, land or surface temperature, emissivity, water-vapour information and aerosol information.
- L2B: vegetation variables, albedo, evapotranspiration and vegetation-stress indicators.
- L3: daily evapotranspiration time series.
L2B and L3 evapotranspiration are derived or model products, not direct temperature measurements. Their usefulness will depend on algorithms, ancillary data and validation after launch.
Where data are expected to appear
GEODES identifies the CNES GEODES project page and ISRO’s Bhoonidhi portal as planned distribution routes. Treat those as future access plans. Verify release status, licensing, latency, processing versions and quality documentation after launch and commissioning.
Landsat 8 and 9: the current choice for thermal analysis
What Landsat provides
Landsat 8 carries the Operational Land Imager (OLI) for optical measurements and the Thermal Infrared Sensor (TIRS) for thermal measurements. According to the USGS Landsat 8 specifications, its multispectral optical bands are 30 m, the panchromatic band is 15 m, and its two thermal bands have a 100 m native resolution. Landsat 8 has a 16-day repeat cycle; Landsat 9 is offset by eight days, creating alternating acquisition opportunities when both satellites can observe the target.
The native thermal detector size and the spacing of a delivered raster are not necessarily identical. USGS processing documentation notes that TIRS data are resampled in the archive. Report the product grid and the sensor’s native resolution separately in a methods section, rather than calling a resampled 30 m or 100 m grid a new thermal measurement.
Surface-temperature products and cost
USGS Landsat Collection 2 Level-2 products include surface reflectance and surface temperature. USGS states that the Landsat archive is available at no cost through its data-access routes. This makes Landsat 8/9 the practical source in this comparison for a present-day LST workflow and for studies that need continuity with earlier Landsat missions.
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When Landsat is the better fit
- You need a temperature product now rather than a planned mission.
- You need both optical reflectance and thermal observations from a common, established mission family.
- Your study benefits from a long archive and documented Collection 2 processing.
- A 16-day repeat for Landsat 8, with the eight-day offset from Landsat 9, is adequate after cloud screening.
Do not interpret those advantages as proof that Landsat is more accurate than either other mission. A defensible accuracy claim requires a matched validation study for the location, date, surface type and processing chain.
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Sentinel-2: detailed optical data without thermal bands
What Sentinel-2 can and cannot do
Sentinel-2’s Multispectral Instrument has visible, near-infrared and shortwave-infrared bands similar in purpose to Landsat’s optical bands. The USGS comparison of Sentinel-2 MSI and Landsat confirms the critical limitation: Sentinel-2 carries no thermal instrument.
Choose Sentinel-2 for optical land-cover mapping, vegetation indices, crop calendars, burned-area delineation, sediment or water-colour proxies, and surface-reflectance time series. Do not label a Sentinel-2 output as satellite land-surface temperature, and do not claim it can replace Landsat TIRS for thermal analysis.
Access
USGS directs users to Copernicus for Sentinel-2 data access. Select the processing level and atmospheric-correction status that match your analysis, and preserve scene-level cloud and quality metadata in the workflow.
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Which mission fits common land and water questions?
“I need land-surface temperature now.”
Use Landsat 8 or 9 Collection 2 Level-2 surface-temperature products. Confirm that the scene is suitable for your target, inspect cloud and quality masks, and document the product version and scaling instructions. Sentinel-2 can supply matching optical context, but it cannot supply the thermal measurement itself. TRISHNA is not yet an available alternative.
“I need fine optical detail for vegetation or land cover.”
Start with Sentinel-2 surface-reflectance products when its spectral and spatial detail fits the target. Landsat optical bands remain valuable when you need the older archive or a direct optical-plus-thermal pairing. Compare acquisition dates and cloud masks rather than assuming that a nominal revisit produces a usable scene.
“I need the temperature of a lake, reservoir or coastal zone.”
For a current thermal observation, use Landsat 8/9 TIRS-derived products and make the water mask and mixed shoreline pixels explicit. Sentinel-2 can map the water boundary, aquatic vegetation and optical colour or turbidity indicators, but it has no thermal bands. TRISHNA is intended to support inland and coastal water analysis in the future; its planned 1 km oceanic and polar resolution is materially different from its planned land/coastal sampling.
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“I need evapotranspiration or vegetation water stress.”
Today, build the workflow around an available thermal source such as Landsat and use optical observations as inputs or context. CNES GEODES specifically describes a future workflow that combines Sentinel-2 VISNIR images with TRISHNA observations to calibrate simpler FAO-56 evapotranspiration models and produce daily, high-resolution evapotranspiration maps. That workflow depends on TRISHNA data becoming available; it is not a current product.
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Native resolution versus product grid
Spatial numbers describe different things: detector sampling, the resolution of a delivered product, and the size of the area represented by a pixel. TRISHNA’s 60 m figure is a planned product specification, while ISRO’s approximately 57 m value describes land and coastal resolution at nadir. Landsat’s TIRS thermal bands are 100 m native, even when an archive product is resampled to another grid. Keep those definitions separate when comparing pixels or aggregating statistics.
Revisit is not cloud-free frequency
A revisit cycle says how often the spacecraft can offer an observation under its sampling geometry. It does not say how often clear pixels will be available. Clouds, haze, shadows, snow, water glint and quality flags can remove scenes or parts of scenes. For a project schedule, estimate usable acquisitions from the location’s cloud climatology and your quality thresholds, not from the revisit number alone.
Match the satellite scale to the question
A small irrigated field, a broad watershed and an ocean basin need different sampling strategies. Mixed pixels at shorelines, field edges or urban boundaries can dominate an apparent temperature or reflectance change. Aggregate only after masking invalid pixels, and state the spatial support of the statistic you report.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Practical workflows
Workflow 1: current land-surface temperature with Landsat
- Define the temperature question, target dates, acceptable cloud fraction and analysis scale.
- Acquire Landsat 8/9 Collection 2 Level-2 data through USGS access routes, including the surface-temperature and surface-reflectance layers when both are needed.
- Apply the supplied scale factors and units exactly as documented for the product version.
- Mask clouds, cloud shadows, saturation, fill values and other quality flags before calculating statistics.
- Use the water or land mask appropriate to the question; inspect mixed pixels along shorelines and field boundaries.
- Record the scene identifiers, acquisition times, processing collection, native sensor resolution and output grid in your methods log.
- Validate against in-situ or independent observations when making an accuracy claim. A visually plausible thermal map is not a validation result.
Workflow 2: optical land or water analysis with Sentinel-2
- Choose the Sentinel-2 product and atmospheric-correction status suited to your reflectance or index calculation.
- Download through the Copernicus route identified by USGS and retain the scene’s cloud and quality metadata.
- Align bands at their delivered resolutions before calculating indices or classifying features; document any resampling.
- Mask clouds, shadows, snow, invalid pixels and shoreline mixtures.
- For water work, separate open water, emergent vegetation, sediment plumes and land before interpreting spectral differences.
- If temperature is also required, pair the optical scene with a temporally appropriate thermal observation and state that the measurements come from different sensors.
Workflow 3: preparing for TRISHNA
- Design the data model around the planned L1C, L2A, L2B and L3 product distinctions rather than assuming every output is a direct observation.
- Define how a 60 m land product, approximately 57 m nadir sampling and coarser ocean or polar coverage affect your study area.
- Reserve quality-control fields for cloud masks, emissivity, atmospheric variables and algorithm versions.
- Plan cross-sensor checks with Landsat and optical context from Sentinel-2, but do not combine values until product definitions, dates and calibration status are documented.
- Check GEODES and Bhoonidhi after launch for actual availability, access terms and release notes.
Data access and documentation checklist
Use the primary mission pages when setting up a project:
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- USGS Collection 2 Level-2 science products for surface reflectance, surface temperature and no-cost archive access.
- USGS Sentinel-2/Landsat comparison for optical-band context, the absence of Sentinel-2 thermal bands and Copernicus access.
- CNES TRISHNA mission page for current development status, launch target, planned product resolution and revisit.
- ISRO’s TRISHNA mission page for payloads and planned land, coastal, oceanic and polar resolutions.
- CNES GEODES TRISHNA page for planned product levels, distribution plans and the Sentinel-2 complementarity use case.
For every downloaded scene, preserve acquisition date and time, platform, processing collection, product level, cloud and quality masks, spatial reference, scaling instructions and any resampling step. Those details determine whether two apparently similar pixels are actually comparable.
Combining missions without creating false precision
Combining optical and thermal observations can improve temporal coverage, but it introduces differences in overpass time, viewing geometry, atmospheric correction, spatial support, spectral response and algorithm assumptions. A Sentinel-2 reflectance value and a Landsat temperature value are complementary measurements, not interchangeable readings.
ESA describes collaboration among agencies to improve land-surface-temperature monitoring and address inter-sensor comparability and bias, including the context of future thermal missions. See ESA’s thermal-mission calibration overview. Until matched validation and bias information are available for a particular combination, avoid claiming that one mission is inherently more accurate.
Common mistakes and fixes
- Calling Sentinel-2 thermal: Replace the temperature claim with the actual optical variable, or add a thermal dataset.
- Treating TRISHNA as downloadable today: Label it as in development, with a CNES 2027 launch target, and verify post-launch release information.
- Equating grid spacing with native resolution: Report Landsat TIRS’s 100 m native thermal resolution separately from any resampled product grid.
- Assuming revisit equals clear imagery: Build a cloud and quality-screening rule and estimate usable observations for the site.
- Using a derived evapotranspiration layer as a direct observation: Identify L2B or L3 outputs as model or algorithm products and document their inputs.
- Making unsupported accuracy rankings: Cite a location-specific validation study before describing a mission as more accurate or superior.
- Ignoring mixed pixels: Treat shorelines, narrow rivers, small fields and fragmented urban areas as scale-sensitive targets and inspect them at the sensor’s native support.
Decision examples
A city heat-island study starting this month
Use Landsat 8/9 Level-2 surface temperature for the thermal record, add Landsat surface reflectance for land-cover context, and use Sentinel-2 only where its optical detail improves the land-cover mask. Set a cloud-screening threshold and report the thermal native resolution and delivered grid separately.
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A crop-monitoring program focused on vegetation condition
Use Sentinel-2 reflectance and vegetation indices for the optical time series. Add Landsat thermal scenes when canopy temperature or evapotranspiration is a required variable. The two streams answer different questions and should be quality-screened independently.
A future daily evapotranspiration service
Prototype the model with available Landsat thermal data and Sentinel-2 optical inputs, while designing interfaces for the product levels CNES lists for TRISHNA. Do not promise daily high-resolution TRISHNA outputs until the mission is launched, products are released and their validation documentation is available.
What to remember
Choose the sensor that measures the variable your decision requires. Landsat 8/9 is the supported current option here for thermal land and water observations and offers a long, no-cost USGS archive. Sentinel-2 is the optical specialist and cannot provide land-surface temperature. TRISHNA is the prospective high-frequency thermal addition, with planned 60 m products and a three-day equatorial revisit, but its 2027 launch target means it belongs in future planning rather than a current data pipeline.
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