Earth observation turns satellite measurements into knowledge of our land, oceans and atmosphere—helping us understand environmental change, manage resources and respond to natural hazards.
PULSE connects observation data, processing and performance assessment to traceable, decision-ready insights.
Bring multiple sensors and dates into a common framework. Assess the quality of the input, the reliability of the processing and the uncertainty of every derived result.
Vegetation health, agriculture, forests, cities and land-use change.
Water extent, flooding, ocean colour and sea-surface variability.
Surface temperature, trace gases, aerosols and long-term trends.
Ground motion, fire impacts, extreme events and recovery.
Representative mission families for observation-data analysis. Access, licensing and available products depend on each provider; inclusion does not imply a PULSE data partnership.
Sentinel-2 · Landsat 8/9 · PlanetScope · Pléiades Neo · WorldView Legion
Vegetation, land cover, urban growth and coastal waters. Compare spectral signatures and track change through time.
Reflectance · NDVI · Land cover
Sentinel-1 · RADARSAT Constellation · TerraSAR-X / TanDEM-X · COSMO-SkyMed · ICEYE
Day-and-night radar imaging for flood mapping, surface deformation and infrastructure monitoring. Interpret acquisition geometry, speckle and coherence.
Backscatter · Coherence · InSAR
Sentinel-3 · Landsat 8/9 · Sentinel-6 · SWOT
Surface temperature, ocean colour and water-level observations. Assess retrieval quality, seasonal behaviour and agreement with reference measurements.
Temperature · Ocean colour · Altimetry
Sentinel-5P · Sentinel-4 · Sentinel-5 · MetOp / MetOp-SG · Meteosat
Trace gases, aerosols, clouds and meteorological context. Analyse quality-filtered retrievals and temporal anomalies with appropriate spatial sampling.
Trace gases · Aerosols · Clouds
A modular workflow for repeatable analyses: retain scene identifiers, processing parameters, quality masks and provenance alongside every output.
Discover scenes, read metadata and quality bands, check integrity, align coordinate systems and organise multi-temporal data.
Sensor-appropriate calibration, atmospheric correction, cloud screening, SAR terrain correction, co-registration and compositing.
Derive indicators, detect change and anomalies, assess geolocation and radiometry, and compare with independent ground observations.
Export maps, time series, quality summaries and reproducible reports. Define thresholds for alerts and preserve processing logs.
Processing steps and exports are selected for the sensor, product level and application.
Explore the analytical outputs that can be proposed for an observation workflow—from a single acquisition to regional, multi-year monitoring.
NDVI and spectral indicators reveal spatial variability in vegetation. Apply cloud masks and compare like-for-like seasons.
Compare multi-date indicators with a seasonal baseline; flag departures and retain uncertainty and valid-observation counts.
Line-of-sight displacement from interferometric radar. Assess coherence, atmospheric artefacts and reference-point stability.
Map surface water and changes in extent. Validate against reference delineations and account for terrain and urban radar effects.
Explore land-surface temperature patterns, heat anomalies and retrieval uncertainty; distinguish surface from air temperature.
Compare classes and quantify agreement with independent reference samples using confusion matrices and per-class scores.
Assess acquisition coverage, revisit intervals and usable scenes after quality screening, rather than nominal revisit alone.
PULSE figures · Modelled scenarios. Select a figure to enlarge.
Combine satellite measurements with independent observations and explicit evaluation methods. Expand each layer to explore the assessment approach.
Ground-control checkpoints, co-registration residuals, image sharpness, signal-to-noise ratio and radiometric consistency. Report coordinate systems, spatial resolution and viewing geometry.
Independent field surveys, in-situ temperature and water measurements, land-cover reference samples and atmospheric stations. Match acquisition time and spatial support; separate validation data from training data.
Acquisition footprint, usable-pixel fraction, cloud and quality masks, observed revisit, delivery latency and missing scenes. Track completeness and continuity across the area and time interval of interest.
Document algorithms, sensor calibration, quality flags and processing versions. Propagate uncertainty where possible, quantify reference-data limitations and retain a reproducible audit trail.
Connect Earth observation analyses with the wider PULSE processing toolbox and navigation-performance expertise.