SCPSA Sampling Method And It’s Applications In VGI Quality Assessment

Recently,volunteered geographical information(VGI)has attracted more and more attentions worldwide.As a kind of information source,VGI suffers from the lack of quality assurance.It is important to build a quality assessment framework for VGI and a proper sampling design is the first step.The history data in VGI projects like OSM can be used as prior information to design spatial sampling schemes.Usually,there exit some nonlinear relations between them and VGI quality,for instance,more contributors imply higher quality of the region.It is worthy and important to study how to utilize such prior information in VGI to design sampling schemes.Spatially balanced sampling is a hot field in design-based spatial sampling methods recently.The most popular spatially balanced sampling methods consist of Generalized Random Tessellation Stratified(GRTS),Spatially Correlated Poisson Sampling(SCPS)and so on.Based on SCPS method,a new method called Spatially Correlated Poisson Sampling with Anisotropy(SCPSA)is proposed,which uses auxiliary variables to measure anisotropy of population when they are not proportional to the population.SCPS method tries to spread samples over the study region evenly and randomly and only considers the value of distance between samples.The new SCPSA method also takes the direction of distance into consideration and decreases the correlations between samples,which contributes to the reduction of variance.Then the variance estimation problem of the SCPSA method was also discussed and a Bootstrap method was adopted.Simulation study shows that SCPSA method has lower mean square error compared to SCPS method with unequal probability when the auxiliary variable is not proportional to the population.Finally,SCPSA method is applied to VGI quality assessment.The contributors’ number index was calculated from the OSM history data and used as auxiliary variable,then SCPSA method was used to estimate the average positional accuracy of Kowloon peninsula,Hong Kong,which provides basis for further analysis of OSM quality in the region.