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

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

Dimension | ClearSKY | AlphaEarth
Core idea | Fusion of SAR + optical across same day and nearby prior days | Model-derived globally consistent layers
Time fidelity | Date-specific product for a particular day | Not a single-date snapshot
Latency | Near real time for operations | Emphasis on coverage and uniformity
Cloud strategy | SAR plus multi-constellation optical to maintain coverage | Learned representation to fill gaps and smooth variability
Best for | Daily ops, change detection, inspections, response | Large-area mapping, screening, research inputs

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

Feature | ClearSKY | AlphaEarth | Sentinel-2
What you get | Date-specific fusion from SAR + optical with short nearby-days extension | Consistent, model-derived layers | Single optical scenes, often cloudy
Temporal focus | Date faithfulness | Consistency and coverage | Single acquisitions
Cost and access | Commercial service | Research/partnered platform | Open data
Typical use | Operations, compliance, daily monitoring | Mapping and analytics at scale | DIY 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.