Data Points

🛰️ Satellite Imagery

Overhead imagery of an area of interest, used for change detection and site analysis.
Geospatial

Sources

0
0 no-auth

Disciplines

0
that use it

Mission domains

0
reach

Workbench

native tool

🔍 Lookup

📜 Playbook — Satellite Imagery exploitation

  1. Direction — frame the requirement for Satellite Imagery: what decision does this support, by when?
  2. Collection — pull the 0 mapped sources (0 free) and the native workbench; capture provenance and observe OPSEC.
  3. Processing — normalize, de-duplicate and enrich the collected data.
  4. Analysis — correlate against local holdings; apply ACH; assign confidence.
  5. Dissemination — open a case, draft a report, share via STIX/MISP.
  6. Feedback — set an alert rule / watchlist to monitor for change.

⚡ AI Skills & Automation

🤖 Copilot brief⚡ AI SkillsResolveEnrichAuto-CollectHuntReportExport

Automate unattended via the cron pipeline (collect → ingest → resolve → enrich → score → alert).

🎫 Satellite Imagery

Satellite imagery is remotely sensed raster data of a location captured by an earth-observation platform, carrying spectral, temporal, and spatial detail. It matters because it provides independent, timestamped ground truth for facilities, movement, damage, and change that no other source can verify.

Format: Georeferenced raster (GeoTIFF/COG/JP2) with bands (RGB, NIR, SWIR, SAR), acquisition timestamp, sensor/platform ID, resolution (GSD in m/px), and scene ID (e.g. Sentinel-2 tile, Landsat path/row).

📡 How it is collected

  • Query open EO archives by AOI and date
  • Tasking or browsing tile/scene catalogs
  • SAR acquisition for cloud/night coverage
  • Fire/thermal anomaly feed subscription
  • Basemap and historical imagery review
  • Download of analysis-ready COGs via STAC

🧩 Analysis & hunting techniques

  • Multi-temporal change detection
  • NDVI/NDWI/NDBI spectral index computation
  • SAR interferometry and coherence change
  • Object detection and counting
  • Pan-sharpening and enhancement
  • Thermal/fire anomaly analysis
  • Cloud masking and mosaicking
  • Shadow-based height estimation

🔧 Tools

  • QGIS
  • SNAP (Sentinel Toolbox)
  • GDAL
  • Rasterio
  • Google Earth Engine
  • EO Browser
  • Orfeo Toolbox
  • STAC Browser

⚡ Workbench actions

  • Query imagery by AOI/date
  • Run change detection
  • Compute spectral indices
  • Detect and count objects
  • Load SAR for cloud-free view
  • Overlay FIRMS thermal hotspots
  • Measure and estimate heights
  • Export annotated scene

📊 Dashboard KPIs

Ground sample distance (m/px)Acquisition freshness (days)Cloud cover %Detected change magnitudeRevisit cadence
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