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LeonChaoX
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geomaster

Build end-to-end geospatial analysis workflows for remote sensing and GIS operations.

783|65|Updated Feb 27, 2026
Search Tags:#cloud-native#geospatial#spatial statistics#remote sensing#stac#ndvi#gis analysis
One-click install
npx skills add https://github.com/LeonChaoX/qinyan-academic-skills --skill geomaster-leonchaox
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: geomaster
Source: https://github.com/LeonChaoX/qinyan-academic-skills/tree/main/skills/16-%E5%9C%B0%E7%90%86%E7%A9%BA%E9%97%B4%E4%B8%8E%E9%81%A5%E6%84%9F/geomaster
Command: npx skills add https://github.com/LeonChaoX/qinyan-academic-skills --skill geomaster-leonchaox

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

GeoMaster solves the problem of turning raw geospatial data (remote sensing imagery, vector layers, and terrain products) into analysis-ready outputs for mapping, spatial statistics, and Earth-observation ML workflows.

Core Features & Use Cases

  • Remote sensing workflows: compute spectral indices, build composites, apply cloud/SAR processing patterns, and prepare data for change detection or classification.
  • GIS & spatial analysis: manage CRS correctly, perform vector/raster operations, run terrain and viewshed-style analyses, and execute network-style spatial computations.
  • ML for Earth observation: apply classical ML (e.g., RF/SVM/XGBoost) and deep learning patterns (e.g., CNN/U-Net) for land cover and spatial prediction, including explainability and graph-based approaches.
  • Cloud-native & big-data readiness: integrate STAC catalogs and cloud assets (e.g., COG/STAC patterns), plus chunked/distributed processing approaches for large datasets.

Quick Start

Use GeoMaster to calculate NDVI from a Sentinel-2 GeoTIFF you have locally and write the result to a new NDVI GeoTIFF for further analysis.

Frequently Asked Questions about geomaster

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I calculate NDVI from a Sentinel-2 GeoTIFF and save the result?▼

To calculate NDVI, GeoMaster applies spectral index formulas to satellite imagery bands and writes the computed raster output to a new GeoTIFF file for further analysis.

What is the best way to manage CRS validation and reprojection for vector and raster operations?▼

CRS validation and reprojection are handled natively within GeoMaster's GIS workflows, ensuring coordinate reference systems remain consistent across vector and raster operations.

Can I use cloud-native STAC catalogs and COG assets for large-scale Earth observation analysis?▼

Yes, GeoMaster integrates cloud-native STAC catalogs and COG assets, enabling chunked and distributed processing for large-scale Earth observation machine learning workflows.

How do I prepare ML-ready data for land cover classification using remote sensing imagery?▼

GeoMaster prepares ML-ready data by applying satellite preprocessing, computing spectral indices, and structuring raster windows or chunks for classical ML and deep learning models.

Does GeoMaster support GDAL, Rasterio, and GeoPandas-compatible I/O handling?▼

Yes, GeoMaster requires GDAL, Rasterio, and GeoPandas-compatible I/O handling to execute its end-to-end geospatial analysis workflows for remote sensing and spatial statistics.

When should I use raster windows and chunking for terrain and spatiotemporal analysis?▼

Raster windows and chunking should be used when processing large terrain datasets or running spatiotemporal analysis, preventing memory overload and enabling distributed processing approaches.

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