Geodiversity Assessment with Crowdsourced Data and Spatial Multicriteria Analysis

Analysis of spatial variation with app-based crowdsourced audio data

Crowdsourcing technologies such as the use of web or smartphone applications enable the collection of large linguistic corpora. Such corpora allow for an analysis of various linguistic features. In the present contribution we analyzed data of >1500 speakers that were crowdsourced with the smartphone application ‘Dialäkt Äpp’ to examine one such feature: the articulation of /kh/ as [kx͡] in Swiss...

Resolving Spatial References using Crowdsourced Geographical Data

We present a study in which we seek to interpret spatial references that are part of in-situ route descriptions. Our aim is to resolve these references to actual entities and places in the city using a crowdsourced geographic database (OpenStreetMap). We discuss the problems related to this task, and present a possible automatic reference resolution method that can find the correct referent in ...

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...

Structured and Unstructured Machine Learning for Crowdsourced Spatial Data

Recent years have seen a significant increase in the number of applications requiring accurate and up-to-date spatial data. In this context crowdsourced maps such as OpenStreetMap (OSM) have the potential to provide a free and timely representation of our world. However, one factor that negatively influences the proliferation of these maps is the uncertainty about their data quality. This paper...

Bayesian Prediction in Spatial Data Analysis