Aiman Soliman

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Models and observations show that the Arctic is experiencing the most rapid changes in global near-surface air temperature. We developed novel EASE-grid Level 3 (L3) land surface temperature (LST) products from Level 2 (L2) AATSR and MODIS data to provide weekly, monthly and annual LST means over the pan-Arctic region at various grid resolutions (1–25 km)(More)
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)
Thermal remote sensing of soil moisture in vineyards is a challenge. The grass-covered soil, in addition to a standing grape canopy, create complex patterns of heating and cooling and increase the surface temperature variability between vine rows. In this study, we evaluate the strength of relationships between soil moisture, mechanical resistance and(More)
Existing urban boundaries are usually defined by government agencies for administrative, economic, and political purposes. However, it is not clear whether the boundaries truly reflect human interactions with urban space in intraand inter-regional activities. Defining urban boundaries that consider socioeconomic relationships and citizen commute patterns is(More)
A number of recent studies showed that digital footprints around built environments, such as geo-located tweets, are promising data sources for characterizing urban land use. However, challenges for achieving this purpose exist due to the volume and unstructured nature of geo-located social media. Previous studies focused on analyzing Twitter data(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)
Detecting salinity in early stages using electromagnetic survey and multivariate geostatistical techniques. This research is aimed at increasing the accuracy of detecting soil salinity in early stages of the process. This phenomenon develops at depth; optical remote sensing (e.g. satellite images) cannot be useful in detecting subsoil variability. Therefore(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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