gis-remote-sensing-guide
GIS analysis and remote sensing workflows for geospatial research applications
Profile →npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill gis-remote-sensing-guide --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.
# GIS and Remote Sensing Guide A comprehensive skill for conducting geospatial analysis and remote sensing research. Covers data acquisition from satellite platforms, spatial analysis with open-source tools, and publication-quality map production. ## Satellite Data Sources ### Key Earth Observation Platforms | Platform | Provider | Spatial Res. | Revisit | Free? | Use Case | |----------|----------|-------------|---------|-------|----------| | Landsat 8/9 | USGS/NASA | 30m (MS), 15m (pan) | 16 days | Yes | Land cover, NDVI time series | | Sentinel-2 | ESA/Copernicus | 10m | 5 days | Yes | Agriculture, urban mapping | | MODIS | NASA | 250m-1km | 1-2 days | Yes | Large-scale vegetation, fire | | Sentinel-1 | ESA | 5-20m | 6 days | Yes | SAR, flood mapping, deformation | | SRTM/ASTER | NASA | 30m | N/A | Yes | Digital elevation models | ### Data Download with Python ```python import ee # Initialize Google Earth Engine ee.Initialize() def get_sentinel2_composite(aoi: ee.Geometry, start: str, end: str, cloud_max: int = 20) -> ee.Image: """ Create a cloud-free Sentinel-2 composite. Args: aoi: Area of interest as ee.Geometry start: Start date (YYYY-MM-DD) end: End date (YYYY-MM-DD) cloud_m
- Satellite Data Sources
- Key Earth Observation Platforms
- Data Download with Python
- Spatial Analysis with GeoPandas
- Vector Data Processing
- Remote Sensing Indices
- Vegetation and Water Indices
- Map Production
- Coordinate Reference Systems
What does the gis-remote-sensing-guide skill do?
GIS analysis and remote sensing workflows for geospatial research applications
How do I install it?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill gis-remote-sensing-guide --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.