Process raster, vector, remote sensing, and spatial statistics geodata.
npx skills add https://github.com/dralkh/seerai --skill geomaster-dralkh
Please help me install this Agent Skill. Skill: geomaster Source: https://github.com/dralkh/seerai/tree/main/skills/geomaster Command: npx skills add https://github.com/dralkh/seerai --skill geomaster-dralkh
GeoMaster removes the friction of learning and combining geospatial tools by giving users one skill for vector, raster, remote sensing, and spatial analysis workflows.
Ask GeoMaster to analyze your geospatial dataset, identify the right CRS, and guide the best workflow for your target task in plain language.
High-intent search queries and answers about installing and using this skill.
Remote sensing workflows for Sentinel, Landsat, MODIS, and SAR imagery are supported directly. You can process cloud-native STAC sources, classify land cover, build NDVI maps, and perform change detection across your spatial datasets.
Validating coordinate reference systems is a core requirement before running spatial analysis. The skill identifies the correct CRS for your geospatial dataset and guides you through resolving misalignment and raster issues in production pipelines.
Spatial joins, overlays, terrain modeling, and hydrology tasks are supported for both raster and vector data. It applies efficient large-data handling and spatial statistics to process complex 3D or spatiotemporal problems.
Machine learning and automation examples are included for land cover classification, change detection, and kriging. These workflows apply spatial statistics to build predictive models from your remote sensing and vector datasets.
You can build flood maps and optimize routes by applying the included hydrology and network analysis workflows. The skill guides the best analytical methods for your target task in plain language.
References are provided to ensure reproducible workflows, troubleshooting, and advanced analytical methods. This supports multi-language geospatial development and validates CRS across research and industry scenarios.
jasrajtulsiAnalyze geospatial data workflows using Python and GDAL, Rasterio, GeoPandas, and Shapely.
shushuznBuild end-to-end geospatial analysis pipelines for remote sensing and GIS.
irahardiantoRetrieve implementation knowledge, code examples, and documentation references from a knowledge base.
Yezez9Process geospatial vector and raster data for remote sensing and GIS analysis.
