Spatial and Urban Data Science with PySAL @SciPy22

Instructors

• Sergio Rey - University of California, Riverside
• Elijah Knaap - University of California, Riverside

Short Description

This repository contains the materials and instructions for the PySAL workshop at SciPy 2022.

Proposed Schedule:

• Geographic Data Science with Python

  • PySAL Overview
  • Spatial data processing
  • Choropleth mapping and geovisualization
    • Break

• Fundamentals of Spatial Analysis

  • Spatial weights
  • Global & Local spatial autocorrelation
    • Break

• Applied Spatial Analysis: Neighborhood Analytics

  • Clustering/Geodemographic Analysis
  • Segregation Analysis
    • Break

• Applied Spatial Analysis: Neighborhood Dynamics

  • Modeling neighborhood change
  • Measuring spatial and temporal segregation dynamics

Long Description

Fundamentals of Spatial Analysis

PySAL Overview

Brief introduction to the PySAL ecosystem of packages for spatial data science

Spatial data processing

Reading and writing GIS file formats, spatial data wrangling, changing coordinate transformation systems.

Choropleth mapping and geovisualization

Introduction to choropleth map classification using mapclassify. Basic visualization with GeoPandas, and matplotlib as well as interactive visualization via folium, leaflet and geoviews/hvplot,

Hands-on 1 Exploratory Geovisualization

Spatial weights

Introduction to the spatial weights matrix for formally encoding geographic relationships.

Global & Local spatial autocorrelation

Exploratory spatial data analysis and overview of measures of spatial autocorrelation statistics such as Moran’s I and the join-count statistic.

Hands-on 2 Hot-spot detection

Applied Spatial Analysis: Neighborhood Analytics

Exploring socio-spatial differentiation

Clustering/Geodemographic Analysis

Introduction to classic and spatially-constrained geodemographics (regionalization). This module provides an overview of integrating scikit-learn and pysal to develop socio-demographic cluster models that optionally include a spatial constraint.

Hands-on 3 Defining Neighborhoods

Segregation Analysis

Applied segregation analysis including the calculation of classic, multigroup, and spatial indices. This module also includes analysis of spatial segregation dynamics, and comparative inference

Applied Spatial Analysis: Neighborhood Dynamics

Neighborhood Change

Introduction to geosnap for creating geodemographic typologies over time and modeling neighborhood transitions

Segregation Dynamics

Examine changes in income segregation over space and time

Hands-on 4 Comparative segregation