satellite-remote-sensing
Satellite imagery analysis and remote sensing for earth science research
Profile →npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill satellite-remote-sensing --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Satellite Remote Sensing A skill for processing and analyzing satellite imagery for earth science research. Covers data acquisition from major satellite platforms, preprocessing workflows, spectral index computation, land cover classification, and change detection using Python geospatial tools. ## Satellite Data Sources ### Major Earth Observation Missions | Mission | Operator | Resolution | Revisit | Key Bands | Access | |---------|----------|-----------|---------|-----------|--------| | Landsat 8/9 | USGS/NASA | 30m (MS), 15m (pan) | 16 days | 11 bands, OLI+TIRS | Free (USGS EarthExplorer) | | Sentinel-2 | ESA | 10m-60m | 5 days | 13 bands, MSI | Free (Copernicus Open Access Hub) | | MODIS | NASA | 250m-1km | 1-2 days | 36 bands | Free (NASA LAADS DAAC) | | Sentinel-1 | ESA | 5-20m | 6 days | C-band SAR | Free (Copernicus) | | GOES-16/17 | NOAA | 0.5-2km | 5-15 min | 16 bands, ABI | Free (NOAA CLASS) | ### Programmatic Data Access ```python import planetary_computer import pystac_client import rioxarray # Search Sentinel-2 imagery via Microsoft Planetary Computer catalog = pystac_client.Client.open( "https://planetarycomputer.microsoft.com/api/stac/v1", modifier=planetary_compu
- Satellite Data Sources
- Major Earth Observation Missions
- Programmatic Data Access
- Preprocessing Pipeline
- Atmospheric Correction
- Geometric Correction and Mosaicking
- Spectral Indices
- Vegetation and Water Indices
- Index Interpretation
- Land Cover Classification
- Supervised Classification with Random Forest
- Change Detection
- Tools and Libraries
What does the satellite-remote-sensing skill do?
Satellite imagery analysis and remote sensing for earth science research
How do I install it?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill satellite-remote-sensing --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Auto-Empirical-Research-Skills, a repository with 3,244 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.