ClearSKY vs AlphaEarth (and Sentinel-2): Which Fits Your Monitoring Goal?

2025-08-21 · 5 min read · ClearSKY · AlphaEarth · Data Fusion

ClearSKY vs AlphaEarth (and Sentinel-2): Which Fits Your Monitoring Goal?

TL;DR: ClearSKY vs AlphaEarth comes down to date faithfulness and latency. ClearSKY fuses SAR + optical across same day and nearby prior days to deliver a date-specific view in near real time, never using future data. AlphaEarth produces globally consistent, model-derived layers that emphasise coverage and uniformity rather than single-date snapshots. Sentinel-2 remains the free, science-grade baseline.

Why this comparison matters

Many teams search for “Sentinel-2 vs AlphaEarth” or “ClearSKY vs AlphaEarth” when they are deciding between date-specific monitoring and globally consistent layers. These approaches solve different problems. If you need an observation that represents a particular day, time matters more than a perfectly uniform map. If you need a gap-free, consistent layer for large-area analysis, uniformity matters more than strict per-day fidelity.


ClearSKY vs AlphaEarth at a glance

ClearSKY: date-faithful, SAR-powered fusion

  • What it is. A fusion service that combines multiple satellites and multiple sensors (SAR + optical), prioritising same-day observations and, where needed, nearby prior days to reconstruct a surface view for a specific date. No future data is used.
  • Where it shines. Near real time operations, daily change detection, incident response, agricultural and forestry decisions, compliance checks that must reference a date.
  • Why it’s different. SAR penetrates cloud and provides structure when optical is obscured. Multi-constellation intake raises the odds of getting usable signal on the day you care about.

AlphaEarth: globally consistent, model-derived layers

  • What it is. A geospatial AI that learns from many sources to produce consistent, gap-minimised layers and analytics across regions and seasons.
  • Where it shines. Thematic mapping at scale, screening and prioritisation, research workflows that need uniform inputs, long-term context when exact acquisition times are less important.
  • Why it’s different. Outputs are model-derived, optimised for spatial and temporal consistency rather than strict single-date observations or rapid delivery.

Key differences that affect decisions

Temporal consistency and date faithfulness

  • ClearSKY: builds a date-specific product. Same-day data first, then nearby prior days only if needed. The result reflects conditions for a particular date.
  • AlphaEarth: provides consistent layers that are not tied to a single acquisition time. Excellent for completeness and uniformity, not for audit to a specific day.

Latency and operational use

  • ClearSKY: designed for near real time monitoring and decisions made on daily or sub-daily cycles.
  • AlphaEarth: designed for coherent, ready-to-use layers with an emphasis on coverage and stability rather than immediate availability.

Sensors and cloud handling

  • ClearSKY: fuses SAR + optical to recover information under cloud, then blends multi-constellation inputs to improve coverage without long seasonal windows.
  • AlphaEarth: integrates many data sources into a learned representation that improves uniformity but does not guarantee a per-day snapshot.

Where Sentinel-2 fits

Sentinel-2 is the open, science-grade baseline. It offers 13 optical bands at 10–60 m and powers countless indices and methods. On its own it is often cloudy and may require mosaicking or fusion. Many users rely on Sentinel-2 as a reference or as an ingredient in higher-level products.


Use cases: choose by outcome, not by brand

Pick ClearSKY when you need

  • Daily change detection on assets, fields, harvest blocks, or water bodies.
  • Near real time views for response and routing when weather is variable.
  • Date-referenced evidence for checks and inspections.
  • Cloud-robust monitoring using SAR + optical without waiting for a clear scene.

Pick AlphaEarth when you need

  • Consistent layers for mapping and screening across countries or continents.
  • Uniform inputs for modelling and research.
  • Contextual baselines where exact acquisition time is less critical than coverage and coherence.

Keep Sentinel-2 in the toolkit when you need

  • Free, open inputs for custom analysis or academic projects.
  • Band-level control for specialised indices and experiments.

ClearSKY vs AlphaEarth: quick comparison

DimensionClearSKYAlphaEarth
Core ideaFusion of SAR + optical across same day and nearby prior daysModel-derived globally consistent layers
Time fidelityDate-specific product for a particular dayNot a single-date snapshot
LatencyNear real time for operationsEmphasis on coverage and uniformity
Cloud strategySAR plus multi-constellation optical to maintain coverageLearned representation to fill gaps and smooth variability
Best forDaily ops, change detection, inspections, responseLarge-area mapping, screening, research inputs

Sentinel-2, ClearSKY, AlphaEarth: side-by-side

FeatureClearSKYAlphaEarthSentinel-2
What you getDate-specific fusion from SAR + optical with short nearby-days extensionConsistent, model-derived layersSingle optical scenes, often cloudy
Temporal focusDate faithfulnessConsistency and coverageSingle acquisitions
Cost and accessCommercial serviceResearch/partnered platformOpen data
Typical useOperations, compliance, daily monitoringMapping and analytics at scaleDIY processing, indices, experiments

Which should you pick?

If your work depends on what happened on a given date, choose the approach that preserves that date and delivers quickly. If your work depends on a consistent picture across space and time, choose the approach that prioritises uniformity and coverage. Many teams use both: ClearSKY for the daily truth on the ground, AlphaEarth for the big-picture context, and Sentinel-2 as an open reference and research input.

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