Urban Land Use Mapping and Analysis in the Big Data Era

Dear Colleagues,

Cities are focal points for economic, social, cultural, and recreational activities. Land use is the platform of these various human activities. The configuration and patterns of land use in cities are the basis for urban planning and management, disaster reduction, sustainable development, and human well-being. However, on-time, large-scale, frequent land-use information has been difficult to obtain in most cities due to the diversity and variation of land-use patterns, the complexity of urban scenes, and the high labor and cost involved. The rapid developments in remote sensing technologies, ground-based and wearable devices have greatly expanded our capability in the acquisition of data related to the urban environment and activities of citizens. Richer and richer volumes of data are becoming available, including remotely sensed images, social media, check-in records, taxi trajectory, videos, and street view images, as well as in-situ survey and census data. These have constituted the ever-expanding big data in urban areas. However, how to extract economic, social, cultural, environmental, and recreational information from these data and combine the extracted information to derive information on urban land-use is a problem that requires better solutions. The big data collected in cities are heterogeneous in data formats, spatial scales, temporal scales, and semantic granularity, and have complicated relationships with various economic, social, cultural, environmental, and other human-related factors. Thus, it has become a challenge to map and analyze urban land-use patterns using big data.

This Special Issue calls for innovative fusion and analysis techniques for mapping urban land-use patterns with a specific focus on the use of big data. The topics include, but not limited to, the following:

• Urban big data processing, analysis, and management
• Methods for urban environmental information extraction, including economic, social, cultural, environmental, and other human-related factors
• 4D urban information collection and processing
• Data mining and machine learning methods for data fusion
• Time-series land-cover and land-use mapping in urban areas
• Scale, transferability, and sample issues in urban land-use mapping
• Urban land-use configuration and pattern analysis
• Change detection and dynamic analysis of urban land cover and land-use
• Urban land-use modeling
• Applications of urban land-use information and technologies in support of urban sustainable development, improving the living quality and human well-being of urban citizens.

Prof. Dr. Peng Gong
Prof. Dr. Shihong Du
Prof. Dr. Xin Huang
Dr. Chong Liu
Guest Editors

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