geomaster

Process geospatial vector and raster data for remote sensing and GIS analysis.

Updated Mar 10, 2026

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

Ready to run

npx skills add https://github.com/Yezez9/Research-Agent --skill geomaster

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: geomaster
Source: https://github.com/Yezez9/Research-Agent/tree/main/scientific-skills/geomaster
Command: npx skills add https://github.com/Yezez9/Research-Agent --skill geomaster

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides a comprehensive toolkit for handling complex geospatial data, enabling advanced analysis and visualization across various scientific domains and programming languages.

Core Features & Use Cases

Geospatial Data Handling: Process vector (Shapefile, GeoJSON) and raster (GeoTIFF, COG) data efficiently.
Advanced Analysis: Perform remote sensing, GIS operations, spatial statistics, and machine learning tasks.
Multi-Language Support: Utilize examples and tools across Python, R, Julia, JavaScript, and more.
Use Case: Analyze satellite imagery to classify land cover, perform hydrological modeling using DEM data, or conduct network analysis for urban planning.

Quick Start

Use the geomaster skill to calculate the NDVI from the attached Sentinel-2 image 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 a Sentinel-2 satellite imagery file?▼

To calculate NDVI from Sentinel-2 satellite imagery, you process the raster data by applying the normalized difference vegetation index formula to the relevant spectral bands. This Skill provides code examples to perform remote sensing workflows on GeoTIFF files.

What is the best way to handle vector and raster geospatial data for analysis?▼

Handling vector and raster geospatial data requires processing formats like Shapefile, GeoJSON, GeoTIFF, and COG. This Skill supports efficient vector and raster data operations for comprehensive GIS analysis and spatial statistics across multiple programming languages.

Can I use spatial machine learning for Earth observation data processing?▼

Yes, you can use spatial machine learning for Earth observation data processing to classify land cover and conduct spatial analysis. This Skill supports spatial ML tasks alongside remote sensing workflows and satellite imagery processing.

Does this geospatial analysis skill support multiple programming languages?▼

Yes, this geospatial analysis skill supports multiple programming languages including Python, R, Julia, and JavaScript. It provides extensive code examples and tools to execute remote sensing, GIS operations, and spatial statistics across these environments.

How do I perform hydrological modeling using DEM data?▼

To perform hydrological modeling using DEM data, you apply spatial analysis and GIS operations to the digital elevation model. This Skill enables advanced geospatial data handling to model terrain hydrology and conduct network analysis for urban planning.