The trends in global population growth by international organisations such as the United Nations indicate that the number of people living in cities and urban areas will increase dramatically on current figures in the next decade. These population growth challenges will require global societal responses, the results of which will determine the quality of life of billions of citizens. As it stands, humanity is already using the Earth's resources at an unsustainable rate and subsequently placing increasing pressures on the natural environment and its ecosystem upon which we so greatly depend. With these challenges comes unprecedented opportunities to collect spatial data and information about these cities and urban areas in order to address these problems. Big Data is an emerging research area which has immense potential to help society adapt to population increases and growing urbanization. Big Data is generated by a myriad of sources including satellites, in-situ sensor networks, sensing devices, Internet of Things systems and applications, the social Internet including social media, networking, etc. Indeed, more specifically, Geospatial Big Data refers to all of these data and information streams which contain specific spatial and location references. Citizens generate information and data which combines to make Geospatial Big Data in so many ways—passively (using apps, web sites, sensors, etc., automatically with little or no interaction) and actively with more interaction such as sharing GPS tracks, geolocating social media posts, contributing to Volunteered Geographic Information projects, etc. A massive challenge has arisen to elicit and extract knowledge and intelligence from this Geospatial Big Data in order to understand, predict and manage how cities and urban areas function, change and grow. Cities and urban areas themselves generate massive volumes of Geospatial Big Data directly and indirectly, passively and actively. However, few examples exist where these data resources have been efficiently explored and exploited in Urban and City Studies.
On the other hand, urban studies involve sophisticated factors which, once deployed, are expected to guide towards city smartness and urban smartness. These factors can be more effective using geospatial technology, and spatially enabled Big Data is definitely one of current and future trends of urban studies besides other implementation areas. Thus, considering environmental; physical; social; economic and other urban study factors which include but are not limited to location and geographic aspects such as lakes, seashores, hills, topography, geology and geomorphology, geographic needs, climate changes, current and future land use, socioeconomic level, future economic trends, say of citizens will require the involvement of Geospatial Big Data. Further, extracting valuable information from Geospatial Big Data using analytics, geo analytics spatial analysis, or perhaps the combination of both shall obligate the enforcement of quality dimensions of data and information. Those dimensions will increase the level of confidence while implementing it for urban development, urban planning and miscellaneous urban studies and city smartness and development. Dimensions such as data source reliability; data accuracy and precision as compared to the real values; data completeness and the effect of lacking part of the data on decision making; the uncertainty level of parts of Geospatial Big Data that is related to the fitness of use where the purpose of data extraction is to be deeply involved in the process; and other dimensions can be common in Big Data, etc. Thus, ideas and practical aspects of Geospatial reliability, enabling Big Data for urban studies, will be welcome herein.
This Special Issue is dedicated to exploring the methodologies and research techniques developed and delivered to tackle the challenges of Geospatial Big Data in order to understand how City Studies will benefit from it. We call for original papers which focus on all topics involving Geospatial Big Data and related City and Urban Studies.
The Special Issue will place emphasis on innovative research on Geospatial Big Data and approaches and methodologies to using this data. Example topics may include, but are not limited to, the following:
- Data models for the representation of Geospatial Big Data
- Geospatial Big Data analytics and knowledge discovery
- Quality assessment of Geospatial Big Data
- Examples of City and Urban Studies on Geospatial Big Data
- City Analytics methods and applications
- City Dashboards for spatial planning and citizen engagement
- Urban data visualisation including virtual and augmented reality
Prof. Dr. Maria Antonia Brovelli
Mr. Hussein M. Abdulmuttalib
Dr. Peter Mooney
Prof. Chris Pettit
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