The<b>PySAL</b>Ecosystem: Philosophy and Implementation

2021/06/01 by Sergio J. Rey, Luc Anselin, Pedro Amaral +12 · 6 citations
Social Sciences · Environmental Science · Computer Science · #Geographic Information Systems Studies #Soil Geostatistics and Mapping #Geochemistry and Geologic Mapping

paper · doi:10.1111/gean.12276

Abstract

PySAL is a library for geocomputation and spatial data science. Written in Python, the library has a long history of supporting novel scholarship and broadening methodological impacts far afield of academic work. Recently, many new techniques, methods of analyses, and development modes have been implemented, making the library much larger and more encompassing than that previously discussed in the literature. As such, we provide an introduction to the library as it stands now, as well as the scientific and conceptual underpinnings of its core set of components. Finally, we provide a prospective look at the library's future evolution.

Citations

• Local Indicators of Spatial Association—LISA
• Literate Programming

Cited by

• GeoDa, From the Desktop to an Ecosystem for Exploring Spatial Data
• R Packages for Analyzing Spatial Data: A Comparative Case Study with Areal Data
• Modeling and Analyzing Urban Networks and Amenities With OSMnx
• Using open geographic information science practices to create cascading improvements in research quality and to support discovery
• Comparing the effects of Euclidean distance matching and dynamic time warping in the clustering of COVID-19 evolution: a spatiotemporal analysis of COVID-19 dynamics across Europe
• The Hierarchical Morphotope Classification: A Theory-Driven Framework for Large-Scale Analysis of Built Form

Related

• GeoDa, From the Desktop to an Ecosystem for Exploring Spatial Data
• GeoAI: A Python package for integrating artificial intelligence with geospatial data analysis and visualization
• Spatial Data Science Languages: commonalities and needs
• Spatial data science languages: commonalities and needs
• PyLUSAT: An open-source Python toolkit for GIS-based land use suitability analysis