scispace - formally typeset
Journal ArticleDOI

Kernel density estimation and K-means clustering to profile road accident hotspots.

Tessa Kate Anderson
- 01 May 2009 - 
- Vol. 41, Iss: 3, pp 359-364
TLDR
A methodology using Geographical Information Systems (GIS) and Kernel Density Estimation to study the spatial patterns of injury related road accidents in London, UK and a clustering methodology using environmental data and results from the first section in order to create a classification of road accident hotspots are presented.
About
This article is published in Accident Analysis & Prevention.The article was published on 2009-05-01. It has received 576 citations till now. The article focuses on the topics: Cluster analysis & Kernel density estimation.

read more

Citations
More filters
Journal ArticleDOI

Risk analysis and assessment methodologies in the work sites: On a review, classification and comparative study of the scientific literature of the period 2000–2009

TL;DR: In this paper, the main risk analysis and risk assessment methods and techniques by reviewing the scientific literature are classified into three main categories: (a) the qualitative, (b) the quantitative, and (c) the hybrid techniques (qualitative,quantitative, semi-quantitative).
Journal ArticleDOI

Comparison of four statistical and machine learning methods for crash severity prediction.

TL;DR: Overall correct prediction rate had almost the exact opposite results compared to the proposed approach, showing that neglecting the crash costs can lead to misjudgment in choosing the right prediction method.
Journal ArticleDOI

Big Data in Public Health: Terminology, Machine Learning, and Privacy.

TL;DR: The ethical implications of the big data revolution with particular emphasis on maintaining appropriate care for privacy in a world in which technology is rapidly changing social norms regarding the need for (and even the meaning of) privacy are considered.
Journal ArticleDOI

Identification of hazardous road locations of traffic accidents by means of kernel density estimation and cluster significance evaluation.

TL;DR: A procedure which evaluates clusters of traffic accident and organizes them according to their significance and introduced the cluster strength and cluster stability evaluation procedures was applied in the Southern Moravia Region of the Czech Republic.
Journal ArticleDOI

A new method to quantify surface urban heat island intensity.

TL;DR: A new approach to quantify surface UHII (SUHII) using the relationship between MODIS land surface temperature (LST) and impervious surface areas (ISA) is proposed and verified using finer resolution Landset data, to prove its reliability.
References
More filters
BookDOI

Density estimation for statistics and data analysis

TL;DR: The Kernel Method for Multivariate Data: Three Important Methods and Density Estimation in Action.
Book

Geographic Information Systems and Science

TL;DR: The Third Edition of this bestselling textbook has been fully revised and updated to include the latest developments in the field and still retains its accessible format to appeal to a broad range of students.
Book

Interactive Spatial Data Analysis

TL;DR: A: Introduction 1. Spatial data analysis 2. Computers and Spatial Data Analysis B: The Analysis of Data Associated with Points 3. Methods Relating to Point Patterns 4. Methodsrelating to Marked Point Patterns 5. MethodsRelating to a Continuously Varying Attribute Sampled at Points.
Book

Quantitative geography : perspectives on spatial data analysis

TL;DR: In this article, the role of Geographic Information Systems Exploring Spatial Data Visually Local Analysis Point Pattern Analysis Spatial Regression and Geostatistical Models Statistical Inference for Spatial data Spatial Modelling and the Evolution of Spatial Theory Challenges in SPatial Data Analysis
Journal ArticleDOI

The relationship between truck accidents and geometric design of road sections: Poisson versus negative binomial regressions.

TL;DR: The ZIP regression model appears to be a serious candidate model when data exhibit excess zeros, e.g. due to underreporting, and it is recommended that the Poisson regression model be used as an initial model for developing the relationship.
Related Papers (5)