Does it support Coordinate Reference System (CRS) transformations?

Absolutely. It includes best practices for defining, verifying, and reprojecting data (e.g., from WGS84 to Web Mercator) to ensure spatial accuracy.

How does this skill handle large geographic datasets?

It provides optimization patterns such as rasterization with Datashader, geometry simplification, and tile-based rendering to maintain performance with dense data.

What libraries are required for this skill?

The skill utilizes GeoViews, GeoPandas, Shapely, PyProj, and optionally Cartopy for advanced cartographic operations.

Is it possible to create interactive dashboards?

Yes, the skill is designed to integrate with Panel and HoloViews streams for creating dynamic, filterable, and selectable map interfaces.

Can I use different map backgrounds?

Yes, the skill includes support for various tile providers including OpenStreetMap, ESRI World Imagery, Stamen Terrain, and CartoDB.

Geospatial Visualization

Name: Geospatial Visualization
Author: robertpelloni

byrobertpelloni

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数据科学与机器学习

Builds interactive geographic maps and performs spatial data analysis using GeoViews and GeoPandas.

关于

This skill empowers developers to create sophisticated geographic visualizations by integrating GeoViews, GeoPandas, and the wider HoloViz ecosystem. It provides comprehensive patterns for building interactive point, polygon, and line maps, as well as performing complex spatial operations like joins, buffering, and routing. Whether you are visualizing environmental trends, real estate markets, or infrastructure networks, this skill ensures best practices for coordinate reference system (CRS) management, tile provider integration, and performance optimization for large spatial datasets.

主要功能

Interactive map creation with tile provider and basemap integration
Advanced spatial analysis including joins, buffers, and proximity calculations
Comprehensive management of Coordinate Reference Systems (CRS) and projections
Support for multi-layer map dashboards and dynamic filtering
Large dataset optimization using rasterization and datashader techniques
3 GitHub stars

使用场景

Creating real estate and demographic market analysis dashboards
Visualizing environmental monitoring data and climate change patterns
Analyzing urban infrastructure and transportation route efficiency

关于

主要功能

Interactive map creation with tile provider and basemap integration
Advanced spatial analysis including joins, buffers, and proximity calculations
Comprehensive management of Coordinate Reference Systems (CRS) and projections
Support for multi-layer map dashboards and dynamic filtering
Large dataset optimization using rasterization and datashader techniques
3 GitHub stars

使用场景

Creating real estate and demographic market analysis dashboards
Visualizing environmental monitoring data and climate change patterns
Analyzing urban infrastructure and transportation route efficiency