Sentinel-2, multi-source fusion, indices & EO workflows — no fluff, just practical guides.
2025-09-23
Convert Sentinel-2 SAFE/JP2 DN to 0–1 reflectance correctly. QUANTIFICATION_VALUE=10000, per-band RADIO/BOA_ADD_OFFSET, and when a ‘harmonized’ collection already did it for you.
2025-09-22
Copy-ready formulas for Sentinel-2 vegetation, moisture, burn severity, water, snow, urban, and bare soil indices. Includes B8 vs B8A tips, scaling notes, and cross-sensor gotchas.
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.
2025-08-21
ClearSKY vs AlphaEarth, plus where Sentinel-2 fits. Compare SAR + optical fusion with date faithfulness and near real-time against model-derived layers.
2025-08-20
Why Sentinel-2 uses UTM tiles, what EPSG codes mean, and how to pick a projection that preserves areas and distances for parcel analytics and time-series.
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.
2025-08-13
Clear definitions for near real-time, near-now, and daily batch. How data moves from sensor to analytics, why hours matter, and how to measure timeliness without losing integrity.
2025-08-11
A practical, global guide to cloud seasonality, why patterns shift by region, and how to time cloud-free and cloudless requests with Sentinel-2 and companion missions.
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 tradeoffs for multi-sensor harmonization, which makes sources comparable, and data fusion, which combines 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.