Dear Colleagues,
The recent availability of big data linked to geographical locations has provided the GIScientists and Remote Sensing scholars a new era of research in for Urban Informatics and Earth Observation. Big data era is far beyond storage and access and by making sense of it, hidden interconnected patterns of data and information can be revealed for the sake of for Urban Informatics and Earth Observation. The unique structure of big data requires new algorithms and methods for exploiting value-added information in various applications, including smart cities, land use change, urban planning, transportation, and biodiversity. On the other hand, the advanced development of spatio-temporal analysis algorithms and techniques has provided a unique opportunity for discovering uncovered information at (near) real time scale.
This Special Issue is dedicated to address the contributions of big data to assist in urban informatics and Earth observation and how it can help advancing geoinformatics-dependent applications, by improving the spatiality and temporality of traditional datasets in geoinformatics and remote sensing applications. Topics of interest include, but are not limited to:
- Innovative tools and toolkits for processing big (geo)data relevant to Earth observation
- Big (geo)data mining, data analytics and visualization for urban informatics
- Big (geo)data: Analysis and visualization for urban land use and land cover
- (Near) real time data-intensive applications for transportation.
- Models, algorithms, and methods for big data understanding, mining, and integration
- Case studies of big data including navigation, public health, 3D modeling, business planning, transportation, urban management, environmental monitoring, and smart cities
- Earth observation big data: Algorithms and applications
- Volunteered/contributed geographic information and crowdsourcing
- Digital Earth and augmented reality
- Indoor and outdoor navigation and routing
- Social media analysis and human dynamics
- Real-time disaster and risk management
- Socio-economic analysis, assessment, and modeling
Dr. Jamal Jokar Arsanjani
Prof. Ming-Hsiang (Ming) Tsou
Guest Editors
Further information: http://www.mdpi.com/journal/ijgi/special_issues/big_data