Beyond the Border - Kernel Density Estimation for Urban Geography

The kernelSmoothing() function allows you to square and smooth geolocated data. It calculates a classical kernel smoothing (conservative) or a geographically weighted median. There are four major call modes of the function. The first call mode is kernelSmoothing(obs, epsg, cellsize, bandwidth) for a classical kernel smoothing and automatic grid. The second call mode is kernelSmoothing(obs, epsg, cellsize, bandwidth, quantiles) for a geographically weighted median and automatic grid. The third call mode is kernelSmoothing(obs, epsg, cellsize, bandwidth, centroids) for a classical kernel smoothing and user grid. The fourth call mode is kernelSmoothing(obs, epsg, cellsize, bandwidth, quantiles, centroids) for a geographically weighted median and user grid. Geographically weighted summary statistics : a framework for localised exploratory data analysis, C.Brunsdon & al., in Computers, Environment and Urban Systems C.Brunsdon & al. (2002) , Statistical Analysis of Spatial and Spatio-Temporal Point Patterns, Third Edition, Diggle, pp. 83-86, (2003) .

Beyond the Border

btb ("Beyond the Border - Kernel Density Estimation for Urban Geography") is an R package which provides functions dedicated to urban analysis and density estimation using the KDE (kernel density estimator) method.

A partial transposition of the package in Python is also available: btbpy.

Description

The btb_smooth() function allows you to square and smooth geolocated data. It calculates a classical kernel smoothing (conservative) or a geographically weighted median. There are four major call modes of the function.

• The first call mode is btb_smooth(obs, epsg, cellsize, bandwidth) for a classical kernel smoothing and automatic grid.
• The second call mode is btb_smooth(obs, epsg, cellsize, bandwidth, quantiles) for a geographically weighted median and automatic grid.
• The third call mode is btb_smooth(obs, epsg, cellsize, bandwidth, centroids) for a classical kernel smoothing and user grid.
• The fourth call mode is btb_smooth(obs, epsg, cellsize, bandwidth, quantiles, centroids) for a geographically weighted median and user grid.

Installation

btb is available on CRAN and can therefore be readily installed

install.packages("btb")

To get a bug fix or to use a feature from the development version, you can install the development version of from GitHub :

install.packages("devtools")
devtools::install_github("InseeFr/btb")

Usage

Details on how to use the package can be found in its documentation. Some applications for spatial smoothing are presented in chapter 8 of the Handbook of Spatial Analysis published by Insee. You advise you to start by consulting the vignette of the package

Contributions

Maintainer: Solène Colin solene.colin@insee.fr

Creators, authors and contributors:

• Arlindo DOS SANTOS [aut],
• François SEMECURBE [aut],
• Julien PRAMIL [aut]
• Solène COLIN [cre, ctb],
• Kim ANTUNEZ [ctb],
• Auriane RENAUD [ctb],
• Farida MAROUCHI [ctb]
• Joachim TIMOTEO [ctb]

References

• Geographically weighted summary statistics : a framework for localised exploratory data analysis, C.Brunsdon & al., in Computers, Environment and Urban Systems C.Brunsdon & al. (2002) doi:10.1016/S0198-9715(01)00009-6
• Statistical Analysis of Spatial and Spatio-Temporal Point Patterns, Third Edition, Diggle, pp. 83-86, (2003) doi:10.1080/13658816.2014.937718.