@inbook {203,
	title = {Identifying Optimal Study Areas and Spatial Aggregation Units for Point-Based VGI from Multiple Sources},
	booktitle = {Advances in Spatial Data Handling and Analysis},
	year = {2015},
	pages = {65-84},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	abstract = {<p>In this paper, we introduce a new metric for evaluating feasible VGI study areas and the appropriateness of different aggregation unit sizes through three different components of data quality: coverage, density, and user-heterogeneity. Two popular sources of passive VGI are used for initial testing of the metric: Twitter and Flickr. We compare the component and aggregate measures for different simulated point processes and demonstrate the properties of this metric. The three components are assessed iteratively for the point user generated data (tweets and photos) on a local basis by altering grain sizes. We demonstrate the application of this metric with Flickr and Twitter data obtained for three Canadian cities as initial study areas, including Vancouver, Toronto, and Moncton. The utility of the metric for discriminating qualitatively different types of VGI is evaluated for each of these areas based on a relative comparison framework. Finally, we present a use-case for this metric: identifying the optimal spatial grain and extent for a given data set. The results of this analysis will provide a methodology for preliminary evaluation of VGI quality within a given study area, and identify sub-areas with desirable characteristics.</p>},
	isbn = {3319199498},
	author = {Lawrence, Haydn and Robertson, Colin and Feick, Rob and Nelson, Trisalyn}
}
