COG Explained: Why Cloud-Optimized GeoTIFF Became the Default
2026-02-18
Cloud-Optimized GeoTIFF (COG) explained: How GeoTIFF streams via HTTP byte-range requests, why it became the default, and how to create fast, valid COGs with GDAL.
ClearSKY Knowledge Hub
Sentinel-2, multi-source fusion, indices & EO workflows — no fluff, just practical guides.
How to Fix Invalid Polygons: Self-intersections, Holes, and GeoJSON Gotchas
2026-02-17
Fix invalid polygons fast: Diagnose self-intersections, hole errors, and CRS mistakes, then repair in GeoJSON, QGIS, or PostGIS.
Sentinel-2 Scaling & Harmonization: Offsets, Processing Baselines, and “Harmonized” Collections
2026-02-17
Convert Sentinel-2 DN to 0–1 reflectance correctly: quantification value, PB 04.00 add offsets, special NoData rules, and when “Harmonized” already fixed it.
Sentinel-2 Indices: The Big Cheat Sheet (Formulas, Uses, and Pitfalls)
2026-01-05
Copy-ready Sentinel-2 index formulas with B8 vs B8A guidance, scaling notes, masking tips, and the pitfalls that break time series.
EPSG and UTM for Satellite Imagery: Choosing the Right CRS
2025-12-15
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.
ClearSKY vs Planet Fusion Monitoring: Daily Imagery Without the Guesswork
2025-10-15
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.
How to Monitor Crop Health with Sentinel-2 (Northern Europe Guide)
2025-09-10
Field-scale Sentinel-2 crop monitoring for Northern Europe: indices, cadence, parcel stats, and cloud-season tactics that hold up in practice.
ClearSKY vs AlphaEarth (and Sentinel-2): Which Fits Your Monitoring Goal?
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.
NDVI vs. EVI2 vs. NIRv: Which Index Should You Trust (and When)?
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.
Level-1 (TOA) vs. Level-2 (BOA): Picking the Right Input for Analytics
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.
Winter and High-Latitude Monitoring: Snow, Low Sun, and Aerosols
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.
Near real-time satellite data: NRT vs same-day delivery and why the timestamps matter
2025-08-13
Concrete definitions for real-time, near real-time, and same-day satellite delivery. Learn timestamps, latency SLAs, and how to avoid temporal leakage.
Cloud Seasonality Playbook: Best Months for Your Region and How to Plan Requests
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.
Cloud Masking: Why a Binary Choice Breaks a Continuous Problem
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.
Sentinel-2 Bands at Level-1 and Level-2: Wavelengths, Uses, and Comparisons
2025-08-07
Sentinel-2 MSI band cheat sheet for L1C vs L2A: wavelengths, resolutions, key uses, and how they map to Landsat and commercial sensors.
Harmonization vs Data Fusion: Making Multi-Sensor Imagery Agree and Work Together
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.
Cloud-free vs. Cloudless: Why the Line is Blurrier Than You Think
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.