Aiman Soliman

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Recent studies on human mobility show that human movements are not random and tend to be clustered. In this connection, the movements of Twitter users captured by geo-located tweets were found to follow similar patterns, where a few geographic locations dominate the tweeting activity of individual users. However, little is known about the semantics (landuse(More)
Previous studies have shown that Twitter users have biases to tweet from certain locations (locational bias) and during certain hours (temporal bias). We used three years of geo-located Twitter Data to quantify these biases and test our central hypothesis that Twitter users' biases are consistent across US cities. Our results suggest that temporal and(More)
Everyday massive amounts of geo-tagged information are generated around urban environment using micro-blogging services and content sharing platforms. These new Big Geospatial Data sources provide an opportunity to understand people activities and their interaction with the urban environment. In this regard, it is crucial to integrate geo-tagged micro-data(More)
Knowledge about the freeze/thaw state of the surface is of major importance for climate modelling, hydrology and numerous other applications. In this study, a freeze/thaw state detection algorithm using the ASCAT scatterometer is compared to Land Surface Temperature (LST) from MODIS as well as to a product derived from ENVISAT ASAR data. Good agreement with(More)
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