geomaster

Process satellite imagery and perform geospatial analysis with machine learning.

Updated Mar 15, 2026

Search Tags:#machine learning #data analysis #geospatial #gis #remote sensing #earth observation

Ready to run

npx skills add https://github.com/sagunkayastha/claude_skills_collection --skill geomaster-sagunkayastha

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: geomaster
Source: https://github.com/sagunkayastha/claude_skills_collection/tree/main/data-analysis-visualization/geomaster
Command: npx skills add https://github.com/sagunkayastha/claude_skills_collection --skill geomaster-sagunkayastha

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires gdal, rasterio, fiona, shapely, pyproj, geopandas, rsgislib, torchgeo, earthengine-api, scikit-learn, xgboost, torch-geometric, osmnx, networkx, folium, keplergl, cartopy, contextily, mapclassify, xarray, rioxarray, dask-geopandas, pystac-client, planetary-computer, laspy, pylas, open3d, pdal, postgis, spatialite, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides a comprehensive toolkit for anyone working with geospatial data, from basic GIS operations to advanced remote sensing and machine learning, eliminating the need to juggle multiple specialized tools.

Core Features & Use Cases

Geospatial Analysis: Perform vector and raster operations, spatial statistics, and network analysis.
Remote Sensing: Process satellite imagery (Sentinel, Landsat, SAR), calculate spectral indices, and perform image classification.
Machine Learning: Apply ML models for land cover classification, change detection, and geospatial prediction.
Use Case: A researcher needs to analyze land cover changes over time using Sentinel-2 imagery. They can use this Skill to download the data, calculate NDVI, classify land cover types, and visualize the changes.

Quick Start

Use the geomaster skill to calculate the NDVI for the file 'sentinel2.tif'.

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 Sentinel-2 satellite imagery?▼

To calculate NDVI from Sentinel-2 satellite imagery, you can use this Skill to process raster data, apply spectral index formulas, and generate vegetation density outputs for Earth observation analysis.

Can I use machine learning for land cover classification with raster data?▼

Yes, you can use machine learning for land cover classification with raster data by leveraging integrated libraries like scikit-learn, xgboost, and torch-geometric to train models on satellite imagery.

Does this support spatial network analysis and routing with OpenStreetMap data?▼

Yes, this supports spatial network analysis and routing with OpenStreetMap data by utilizing osmnx and networkx to extract vector graphs, compute shortest paths, and perform topological spatial statistics.

What is the best way to process and classify LiDAR point cloud data?▼

The best way to process and classify LiDAR point cloud data is using integrated libraries like laspy, open3d, and pdal to read 3D point structures, filter noise, and extract elevation features for spatial analysis.

How do I query cloud-native geospatial datasets using STAC catalogs?▼

You can query cloud-native geospatial datasets using STAC catalogs by utilizing pystac-client and planetary-computer APIs to search, connect, and retrieve satellite imagery metadata without downloading full scenes.

Can I perform spatial database operations using PostGIS within an automated workflow?▼

Yes, you can perform spatial database operations using PostGIS within an automated workflow to store vector geometries, execute spatial SQL queries, and manage large-scale geospatial relational outputs efficiently.