Skill UI

GeoPandas extends pandas for geospatial vector data, enabling reading/writing shapefiles, GeoJSON, GeoPackage and PostGIS, performing CRS management, spatial joins, overlays, buffering, area/distance calculations, and producing static or interactive choropleth maps.

GeoMaster is a comprehensive geospatial science skill that guides remote sensing, GIS, spatial analysis, and machine learning workflows for Earth observation and planetary data projects, covering satellite imagery, vector/raster math, point clouds, terrain, hydrology, and cloud-native data stacks.

This comprehensive geospatial science skill covers remote sensing, GIS, spatial analysis, and machine learning for Earth observation. It supports satellite imagery processing, vector and raster data operations, spatial statistics, and point cloud processing. Users can utilize cloud-native workflows and 8 programming languages with 500+ code examples. Ideal for terrain analysis, hydrological modeling, and marine spatial analysis tasks.

Provides comprehensive guidelines for authors submitting empirical, quantitative, or theoretical growth papers. It details how to package data sources, code pipelines, calibration files, and historical/geospatial artifacts to meet stringent reproducibility standards for publishing journals.

A comprehensive guide detailing the mandatory replication package requirements for submitting empirical papers to the Journal of Urban Economics (JUE). It covers not only standard data and code deposits but also specialized techniques for handling complex geospatial data, geocoding pipelines, and proprietary/confidential restricted data paths to ensure maximum reproducibility.