Measuring similarity between geospatial lifelines in studies of environmental health

  title={Measuring similarity between geospatial lifelines in studies of environmental health},
  author={Gaurav Sinha and David M. Mark},
  journal={Journal of Geographical Systems},
  • G. Sinha, D. Mark
  • Published 1 May 2005
  • Environmental Science
  • Journal of Geographical Systems
Abstract.Many epidemiological studies involve analysis of clusters of diseases to infer locations of environmental hazards that could be responsible for the disease. This approach is however only suitable for sedentary populations or diseases with small latency periods. For migratory populations and diseases with long latency periods, people may change their residential location between time of exposure and onset of ill health. For such situations, clusters are diffused and diluted by in- and… 

Models and algorithms for contaminated area detection based on geospatial lifelines

This paper uses patients' residential history (also called geospatial lifeline) to locate contaminated areas using a novel method to identify possible relationships between a disease and the locations where environmental factors might be responsible for the development of a disease.

Case-Control Geographic Clustering for Mobile Populations : Methods for Infectious and Chronic Diseases

Humans are mobile and constructs of Geographic Information Science have been used to model daily and weekly activity patterns, as well as residential and work spaces. But geographic epidemiology

Global, local and focused geographic clustering for case-control data with residential histories

Data with residential histories are preferable when causative exposures and disease latencies occur on a long enough time span that human mobility matters and methods are needed that take residential histories into account.

Movement beyond the snapshot - Dynamic analysis of geospatial lifelines

Space–time clustering of case–control data with residential histories: insights into empirical induction periods, age-specific susceptibility, and calendar year-specific effects

  • J. MelikerG. Jacquez
  • Business
    Stochastic environmental research and risk assessment : research journal
  • 2007
This systematic approach for evaluating space–time clustering has the potential to generate novel hypotheses about environmental risk factors and provides insights into empirical induction periods, age-specific susceptibility, and calendar year-specific effects.

An ontology based personal exposure history

This paper describes the development of an ontology for a personal exposure history that specifies explicit relationships between persons and Locations and locations and putative environmental toxic agents and demonstrates how these can be queried using current semantic web technologies.

Spatial Clustering, Detection and Analysis of

  • Y. Lu
  • Environmental Science
  • 2009

A review of quantitative methods for movement data

Existing quantitative methods for analyzing movement data are reviewed to provide a synthesis of the existing literature on quantitative analysis of movement data while identifying those techniques that have merit with novel datasets.

Spatio-temporal behaviour of residents after the 2004 Chuetsu earthquake : a case study of Kawaguchi Town, Japan

Earthquakes are a global threat causing economical and human losses. The human reaction in the case of a seismic event is a complex process. However, its understanding is vital to the improvement of

How to compare movement? A review of physical movement similarity measures in geographic information science and beyond

This review paper decomposes movement into its spatial, temporal, and spatiotemporal movement parameters, and provides a systematic and comprehensive classification of different movement similarity measures used in geographic information science.



The effects of migration on the detection of geographic differences in disease risk.

The Detection of Clusters in Rare Diseases

The main intention of the paper is to describe and illustrate a new technique for the identification of small clusters of disease, and discuss some common pitfalls in the application of tests of clustering to epidemiological data.


Hagerstrand's time geography is a powerful conceptual framework for understanding constraints on human activity participation in space and time. However, rigorous, analytical definitions of basic

Modeling Moving Objects over Multiple Granularities

This paper examines how different aspects of lifelines become relevant at refined or coarse granularities, which generalizes spatial and temporal aspects of movement allowing for an improved understanding of movement.

Indexing multi-dimensional time-series with support for multiple distance measures

The experimental results demonstrate that the index motivated by the need for a single index structure that can support multiple distance measures can help speed-up the computation of expensive similarity measures such as the LCSS and the DTW.

Exact Computational Methods for Calculating Distances Between Objects in a Cartographic Database

Most existing spatial analytic techniques use a simplified, point-based representation of spatial objects. This facilitates tractability of the standard computational procedures for many spatial

Shape-Based Similarity Query for Trajectory of Mobile Objects

An efficient indexing method can efficiently retrieve trajectories whose shape in a space is similar to the shape of a candidate trajectory from the database by combining a spatial indexing technique (R+-Tree) and a dimension reduction technique, called PAA (Piecewise Approximate Aggregate).

Discovering similar multidimensional trajectories

This work formalizes non-metric similarity functions based on the longest common subsequence (LCSS), which are very robust to noise and furthermore provide an intuitive notion of similarity between trajectories by giving more weight to similar portions of the sequences.

Robust similarity measures for mobile object trajectories

This work proposes the use of non-metric distance functions based on the longest common subsequence (LCSS), in conjunction with a sigmoidal matching function for similarity analysis of spatio-temporal trajectories for mobile objects.

Scaling up Dynamic Time Warping to Massive Dataset

This paper introduces a modification of DTW which operates on a higher level abstraction of the data, in particular, a piecewise linear representation and demonstrates that this approach allows us to outperform DTW by one to three orders of magnitude.