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Integrating ArcGIS with PySAL: Advanced Spatial Analysis Framework

Explore the seamless integration of open-source statistical packages with ArcGIS Python Spatial Analysis Library (PySAL). Transform your spatial analytics with scalable, intuitive, and well-documented tools. Enhance your geospatial insights with cutting-edge techniques and high-level front ends. Install PySAL on GitHub and bridge R with ArcGIS for native data access and efficient workflows. Collaborate and innovate with the R-ArcGIS community for enhanced spatial econometrics and dynamic spatial analytics.

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Integrating ArcGIS with PySAL: Advanced Spatial Analysis Framework

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  1. Integrating Open Source Statistical Packages with ArcGISPython Spatial Analysis Library (PySAL)ArcGIS – R Project Mark V. Janikas Marjean Pobuda

  2. Introduction • Traditional Spatial Analysis • Spatial Analyst • Geostatistics • Spatial Statistics • Most Useful Tools • Best Implementation • Scalable, Intuitive and Well Documented

  3. Integrating ArcGIS with Open Source Software Supporting the Scientific Community • Advanced Analytics • Peer reviewed across a vast number of Academic Disciplines • Methodologies range from empirically broad to specific • Python [NumPy] • Increase Core Python Modules • SciPy, PANDAS, Matplotlib, NetCDF4-Python • Conda in ArcGIS Pro 1.3 • Data Access • Directly extendable • Raster/Vector NumPy • Spatial Statistics Data Object and Utilities • Selection and Feature/NumPy Index Mapping • All Data Formats • Environments • Localization, Errors/Warnings, Bad Records Info

  4. Python Spatial Analysis Library Advanced Spatio-Temporal Analytics • Cutting Edge Techniques • Spatial Econometrics, Spatio-Temporal Dynamics, ESDA etc… • Trusted Techniques • Luc Anselin, Sergio Rey etal. • Designed to Support Various High-Level Front Ends • ArcGIS, QGIS, Web • PySAL on GitHub • Install • ArcGIS Pro 1.3 • conda install pysal • ArcGIS Pro < 1.3 and ArcGIS Classic • pip install pysal

  5. Spatial Statistics API and Integration Framework GIS Statistics Jupyter Notebook Tutorials https://github.com/Esri/gis-stat-analysis-py-tutor

  6. PySAL ArcGIS Toolbox Download Toolbox on GitHub https://github.com/Esri/PySAL-ArcGIS-Toolbox

  7. Demo

  8. R Integration • Highly Active Community • Over 6000 Libraries • Old Method (Indirect) • Out of Proc • Python as the Glue • New Method • In Proc • Native Data Access • Honors Selection Sets and Projections • Vector Data • Charts and Graphs • GUI Interface

  9. What is it? Who is it for? • R Users • Provide an open source bridge library to move data between R and ArcGIS • Fast (Native) • All Vector Formats • Projection Engine • ArcGIS Users • Expand accessibility of R in the ArcGIS community • Run R from ArcGIS geoprocessing tool • Works like any other GP tool • Selection and Environments • Work within GNU licensing and R project intent • Build a collaborative GitHub community for GP tool development and education

  10. R-ArcGIS Links https://r-arcgis.github.io https://github.com/R-ArcGIS

  11. Installation Via Python Toolbox R Package Manager

  12. Standard R Documentation

  13. Demo

  14. Moving Forward - PySAL • Spatial Econometrics • Maximum Likelihood • Spatial Dynamics • Panel Data Model – Space-Time Pattern Mining • Supporting Charts and Graphs • Pro Application • Documentation • Luc Anselin and Serio Rey (2014) Modern Spatial Econometrics in Practice • Formal Publication Submission

  15. Moving Forward - R • Documentation/Tutorials • Collaborative Projects • Raster Support • R Consortium at the Silver Level • Continue to monitor/support changes in the R spatial community

  16. Session Reviews on your Mobile App Please tell us how we did! Day [Session Info] Wed [1868 / 1029] Thur [1868 / 1034]

  17. Mark Janikas mjanikas@esri.com Marjean Pobuda mpobuda@esri.com

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