Climate change and rapid urbanisation exacerbated multiple urban issues threatening
urban sustainability. Numerous studies integrated machine learning and remote sensing to …

Sustainable cities are quintessential complex systems—dynamically changing environments
and developed through a multitude of individual and collective decisions from the bottom up …

Human perception of urban landscape, which signifies to what extent urban landscape is
appreciated by local dwellers, informs human-oriented policies that reinforce public …

Artificial intelligence and machine learning are transforming scientific disciplines, but their
full potential for climate change mitigation remains elusive. Here, we conduct a systematic …

Smart cities (SC) promote economic development, improve the welfare of their citizens, and
help in the ability of people to use technologies to build sustainable services. However …

The challenges for sustainable cities to protect the environment, ensure economic growth,
and maintain social justice have been widely recognized. Along with the digitization …

Data sensing, information processing, and networking technologies are being fast
embedded into the very fabric of the contemporary city to enable the use of innovative …

Diverse urban landscape is an important cultural driving force for urban sustainable
development. Although characterizing landscape to protect landscape diversity is widely …

During the past decades, multiple remote sensing data sources, including nighttime light
images, high spatial resolution multispectral satellite images, unmanned drone images, and …

Eighty percent of big data are associated with spatial information, and thus are Big Spatial
Data (BSD). BSD provides new and great opportunities to rework problems in urban and …