Spatial Data Quality: The Duty to Warn Users of Risks Associated with Using Spatial Data

Study of Spatial Data Quality Elements and VGI Linear Data Quality Assessment Methods

Volunteered Geographic Information has provided a rich and valuable resource for spatial data in a variety of applications. Despite the many benefits, this information does not provide any guarantee for their quality. So far, there are several methods to determine the quality of VGI. In addition to introducing quality elements and their evaluation methods, the present study attempts to explore ...

Bayesian Analysis of Survival Data with Spatial Correlation

Often in practice the data on the mortality of a living unit correlation is due to the location of the observations in the study‎. ‎One of the most important issues in the analysis of survival data with spatial dependence‎, ‎is estimation of the parameters and prediction of the unknown values in known sites based on observations vector‎. ‎In this paper to analyze this type of survival‎, ‎Cox...

Spatial Modeling of Censored Survival Data

An important issue in survival data analysis is the identification of risk factors. Some of these factors are identifiable and explainable by presence of some covariates in the Cox proportional hazard model, while the others are unidentifiable or even immeasurable. Spatial correlation of censored survival data is one of these sources that are rarely considered in the literatures. In this paper,...

Spatial Regression in the Presence of Misaligned data

In this paper, four approaches are presented to the problem of fitting a linear regression model in the presence of spatially misaligned data. These approaches are plug-in method‎, ‎simulation‎, ‎regression calibration and maximum likelihood‎. In the first two approaches‎, ‎with modeling the correlation between the explanatory variable, prediction of explanatory variable is determined at sites...

Spatial Data Quality