07-10, 15:50–16:00 (Europe/Amsterdam), Method (1.5)
SpatialDependence.jl is a Julia package for exploratory spatial data analysis (ESDA), spatial weight creation, and testing for spatial dependence (spatial autocorrelation). The package contains functions to create and handle spatial weights matrices from polygon and point geometries. It also has functions for calculating spatial lags, testing for global and local spatial autocorrelation, and plotting choropleth maps.
The package SpatialDependence.jl contains functions to create and handle spatial weights matrices from polygon and point geometries. It also has functions for calculating spatial lags, testing for spatial autocorrelation, and plotting choropleth maps.
The talk will show how the SpatialDependence.jl package introduces an architecture for handling spatial weight matrices representing the observation's spatial relationship. The integration with GeoInterface.jl allows the creation of spatial weight matrices from polygons and points geometry obtained from different data sources.
We present how to plot choropleth maps using different algorithms to classify observations. In addition, global and local spatial autocorrelation statistics can tell us if geographically close observations have similar or dissimilar values and help us to identify clusters.
During the talk, we will briefly describe the package's capabilities in a non-technical language, and how was the experience in developing it in the Julia language.
I am a Lecturer in Economics at the Department of Economic Analysis at Universidad Autónoma de Madrid (UAM).