Spatial Logistic Regression for Events Lying on a Network: Car Crashes in Milan

Andrea Gilardi; Riccardo Borgoni; Diego Zappa

Spatial Logistic Regression for Events Lying on a Network: Car Crashes in Milan

Andrea Gilardi^*
, Riccardo Borgoni
, Diego Zappa

^*Autore corrispondente per questo lavoro

Università Cattolica del Sacro Cuore

Risultato della ricerca: Contributo in libro › Contributo a conferenza

Abstract

In this paper we propose a methodology to estimate the probability that a car accident occurs in urban roads. Our approach is based on logistic regression and takes into account the particular nature of the data which conforms to a spatial point pattern on a network. Using the open data on street networks provided within the OpenStreetMap project, we estimate the probability of car accidents for every street in the municipality of Milan.

Lingua originale	Inglese
Titolo della pubblicazione ospite	Smart Statistics for smart applications
Pagine	1165-1170
Numero di pagine	6
Stato di pubblicazione	Pubblicato - 2019
Evento	Smart Statistics for smart applications - MILANO -- ITA Durata: 18 giu 2019 → 21 giu 2019

Convegno

Convegno	Smart Statistics for smart applications
Città	MILANO -- ITA
Periodo	18/6/19 → 21/6/19

Keywords

car accidents
open data
urban geography

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@inproceedings{da29d7353b0147918feb4be484ea81c5,

title = "Spatial Logistic Regression for Events Lying on a Network: Car Crashes in Milan",

abstract = "In this paper we propose a methodology to estimate the probability that a car accident occurs in urban roads. Our approach is based on logistic regression and takes into account the particular nature of the data which conforms to a spatial point pattern on a network. Using the open data on street networks provided within the OpenStreetMap project, we estimate the probability of car accidents for every street in the municipality of Milan.",

keywords = "car accidents, open data, urban geography, car accidents, open data, urban geography",

author = "Andrea Gilardi and Riccardo Borgoni and Diego Zappa",

year = "2019",

language = "English",

isbn = "9788891915108",

pages = "1165--1170",

booktitle = "Smart Statistics for smart applications",

note = "Smart Statistics for smart applications ; Conference date: 18-06-2019 Through 21-06-2019",

}

TY - GEN

T1 - Spatial Logistic Regression for Events Lying on a Network: Car Crashes in Milan

AU - Gilardi, Andrea

AU - Borgoni, Riccardo

AU - Zappa, Diego

PY - 2019

Y1 - 2019

N2 - In this paper we propose a methodology to estimate the probability that a car accident occurs in urban roads. Our approach is based on logistic regression and takes into account the particular nature of the data which conforms to a spatial point pattern on a network. Using the open data on street networks provided within the OpenStreetMap project, we estimate the probability of car accidents for every street in the municipality of Milan.

AB - In this paper we propose a methodology to estimate the probability that a car accident occurs in urban roads. Our approach is based on logistic regression and takes into account the particular nature of the data which conforms to a spatial point pattern on a network. Using the open data on street networks provided within the OpenStreetMap project, we estimate the probability of car accidents for every street in the municipality of Milan.

KW - car accidents

KW - open data

KW - urban geography

KW - car accidents

KW - open data

KW - urban geography

UR - http://hdl.handle.net/10807/137781

M3 - Conference contribution

SN - 9788891915108

SP - 1165

EP - 1170

BT - Smart Statistics for smart applications

T2 - Smart Statistics for smart applications

Y2 - 18 June 2019 through 21 June 2019

ER -

Spatial Logistic Regression for Events Lying on a Network: Car Crashes in Milan

Abstract

Convegno

Keywords

Altri file e collegamenti

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