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scientific-geospatial-analysis

Automate geospatial analysis with vector/raster processing, spatial statistics, and interactive maps.

3|1|Updated Feb 11, 2026
Search Tags:#geospatial#gis#geopandas#rasterio#spatial-analysis#kriging#morans-i
One-click install
npx skills add https://github.com/nahisaho/satori --skill scientific-geospatial-analysis
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: scientific-geospatial-analysis
Source: https://github.com/nahisaho/satori/tree/main/src/.github/skills/scientific-geospatial-analysis
Command: npx skills add https://github.com/nahisaho/satori --skill scientific-geospatial-analysis

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Geospatial data analysis often requires stitching together multiple libraries and workflows for vector and raster data, statistics, and interactive visualization. This skill provides a cohesive pipeline to preprocess GIS data, perform spatial analysis, and render clear maps.

Core Features & Use Cases

  • Vector data processing with GeoPandas: read shapefiles/GeoJSON, reproject, and summarize geometries.
  • Raster data analysis with Rasterio: read GeoTIFFs, raster calculations, and band operations.
  • Spatial statistics: global Moran's I and Local Indicators of Spatial Association (LISA) to detect clustering.
  • Spatial interpolation: Kriging-based surface estimation for predictive mapping.
  • Interactive visualization: Folium/Kepler.gl for web maps and map-based reporting.
  • Use Case: Assess habitat suitability by processing GBIF records, performing CRS alignment, detecting spatial autocorrelation, and visualizing results on an interactive map.

Quick Start

Load a geospatial dataset (vector or raster), transform it to the target CRS, run spatial analyses (Moran's I, LISA, Kriging if needed), and generate an interactive map.

Frequently Asked Questions about scientific-geospatial-analysis

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

FAQPage Schema
How do I automate geospatial data cleaning and CRS transformations for shapefiles?▼

Automate geospatial data cleaning by loading shapefiles or GeoJSON into GeoPandas, reprojecting geometries to the target CRS, and summarizing spatial attributes. This pipeline handles coordinate reference system alignment to ensure vector layers overlay correctly for analysis.

What is the best way to calculate spatial autocorrelation and detect clustering in GIS data?▼

Calculate spatial autocorrelation by running global Moran's I and Local Indicators of Spatial Association (LISA) tests on your dataset. These spatial statistics identify whether attribute values cluster spatially, highlighting hot spots and cold spots across your study area.

How does Kriging interpolation work for creating predictive surface maps from point data?▼

Kriging interpolation estimates continuous surfaces from discrete point data by modeling spatial variance between locations. This technique generates predictive raster maps for unsampled areas, applying geostatistical algorithms to produce accurate spatial surface estimations.

Can I process raster calculations and band operations directly from GeoTIFFs?▼

Process raster calculations directly from GeoTIFFs using Rasterio to read multi-band arrays and perform mathematical operations. This supports raster algebra, band math, and spatial overlay analysis required for terrain modeling or remote sensing workflows.

How do I generate interactive web maps for spatial analysis reporting?▼

Generate interactive web maps using Folium or Kepler.gl to visualize spatial analysis outputs. This transforms vector and raster processing results into shareable, map-based reports that allow users to explore clustering patterns and interpolated surfaces dynamically.

Do I need to align projections before running Moran's I or Kriging on my spatial datasets?▼

You must align coordinate reference systems before running spatial statistics like Moran's I or Kriging. Reprojecting all vector and raster layers to a common CRS ensures accurate distance calculations, spatial weights matrix generation, and valid interpolation results.

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