Which programming languages are covered in this skill?

The skill supports 8 major programming languages: Python, R, Julia, JavaScript, C++, Java, Go, and Rust, ensuring compatibility with diverse engineering stacks.

What satellite missions does GeoMaster support?

GeoMaster provides specialized code and workflows for processing data from Sentinel-2, Landsat, MODIS, and SAR missions, including hyperspectral imagery handling.

Can I use GeoMaster for cloud-native geospatial analysis?

Yes, it includes comprehensive support for modern cloud-native workflows including STAC (Spatiotemporal Asset Catalog), COG (Cloud-Optimized GeoTIFF), and Microsoft Planetary Computer.

Does it handle point cloud and terrain data?

Absolutely. GeoMaster includes patterns for processing point clouds using Laspy and PDAL, as well as terrain analysis metrics like slope, aspect, and hillshade from DEMs.

GeoMaster Geospatial Science

Name: GeoMaster Geospatial Science
Author: K-Dense-AI

byK-Dense-AI

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16,950

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Data Science & ML

Powers geospatial analysis and Earth observation workflows through comprehensive GIS, remote sensing, and spatial machine learning capabilities.

GeoMaster is a specialized Claude Code skill designed for researchers, engineers, and data scientists working with complex geospatial data. It provides expert guidance and over 500 code examples across 8 programming languages for processing satellite imagery from missions like Sentinel and Landsat, managing vector and raster data, and performing advanced spatial statistics. Whether you are building hydrological models, analyzing urban street networks with OSMnx, or implementing cloud-native workflows using STAC and COG, GeoMaster streamlines the development of sophisticated Earth observation and GIS applications by providing domain-specific patterns and best practices.

Key Features

01Cloud-native geospatial workflows with STAC, COG, and Planetary Computer.

0216,950 GitHub stars

03Multi-language support including Python, R, Julia, and Rust with 500+ examples.

04Spatial machine learning and classification for Earth observation.

05Advanced remote sensing for Sentinel-2, Landsat, and SAR data processing.

06Comprehensive vector and raster operations using GeoPandas, GDAL, and Xarray.

Use Cases

01Calculating spectral indices like NDVI and performing terrain analysis from DEMs.

02Analyzing urban street networks and shortest path routing using OSMnx.

03Automating satellite imagery classification using Random Forest and Deep Learning.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add k-dense-ai/claude-scientific-skills geomaster

For use in Claude.ai and ChatGPT

Key Features

01Cloud-native geospatial workflows with STAC, COG, and Planetary Computer.

0216,950 GitHub stars

03Multi-language support including Python, R, Julia, and Rust with 500+ examples.

04Spatial machine learning and classification for Earth observation.

05Advanced remote sensing for Sentinel-2, Landsat, and SAR data processing.

06Comprehensive vector and raster operations using GeoPandas, GDAL, and Xarray.

Use Cases

01Calculating spectral indices like NDVI and performing terrain analysis from DEMs.

02Analyzing urban street networks and shortest path routing using OSMnx.

03Automating satellite imagery classification using Random Forest and Deep Learning.