2025-09-04
A practical comparison of ClearSKY’s satellite-agnostic SAR + optical fusion and Planet’s 3 m Fusion Monitoring. How each handles clouds, time fidelity, noise, resolution, satellites used, and pricing for small and large areas.
2025-08-29
Practical, field-scale workflows for crop health monitoring in Denmark and Northern Europe using Sentinel-2: indices, cadence, zonal stats, and cloudy-weather strategies.
2025-08-20
Why Sentinel-2 uses UTM tiles, what EPSG codes mean, and how to pick a projection for accurate areas and distances when working with satellite data.
2025-08-18
Plain-English guidance on what each vegetation index measures, how they behave under soil, haze, and saturation, and practical defaults for real-world monitoring.
2025-08-17
What top-of-atmosphere and bottom-of-atmosphere really mean, why L2A is computed from L1C, and when ML or analytics should use L1 vs L2.
2025-08-15
Why optical imagery struggles in northern winters, how Sentinel-1 SAR helps, and the processing choices that make or break time-series.
2025-08-11
A global, practical guide to when skies are clearest, what drives cloud patterns, and how to time cloud-free and cloudless requests with Sentinel-2 and friends.
2025-08-09
Cloud masking for satellite imagery is not binary. Cirrus, stratocumulus, haze, aerosol, snow, bright sand, sunglint, and cloud shadows require probabilistic masks and careful thresholds.
2025-08-07
A practical guide to Sentinel-2 MSI bands at Level-1C and Level-2A, what each band is good for, and how they compare with Landsat, PlanetScope, and EarthDaily class sensors.
2025-08-05
Clear definitions, methods, and trade-offs for multi-sensor harmonization (make sources comparable) and data fusion (combine them into one estimate).
2025-08-01
When to use single-date cloud-free imagery vs. multi-date cloudless mosaics – and why modern AI fusion is changing the definitions.