Deep learning for cross-domain data fusion in urban computing: Taxonomy, advances, and outlook
As cities continue to burgeon, Urban Computing emerges as a pivotal discipline for
sustainable development by harnessing the power of cross-domain data fusion from diverse …
sustainable development by harnessing the power of cross-domain data fusion from diverse …
Urban foundation models: A survey
Machine learning techniques are now integral to the advancement of intelligent urban
services, playing a crucial role in elevating the efficiency, sustainability, and livability of …
services, playing a crucial role in elevating the efficiency, sustainability, and livability of …
When urban region profiling meets large language models
Urban region profiling from web-sourced data is of utmost importance for urban planning
and sustainable development. We are witnessing a rising trend of LLMs for various fields …
and sustainable development. We are witnessing a rising trend of LLMs for various fields …
Knowledge-infused contrastive learning for urban imagery-based socioeconomic prediction
Monitoring sustainable development goals requires accurate and timely socioeconomic
statistics, while ubiquitous and frequently-updated urban imagery in web like satellite/street …
statistics, while ubiquitous and frequently-updated urban imagery in web like satellite/street …
A satellite imagery dataset for long-term sustainable development in united states cities
Cities play an important role in achieving sustainable development goals (SDGs) to promote
economic growth and meet social needs. Especially satellite imagery is a potential data …
economic growth and meet social needs. Especially satellite imagery is a potential data …
Towards Urban General Intelligence: A Review and Outlook of Urban Foundation Models
Machine learning techniques are now integral to the advancement of intelligent urban
services, playing a crucial role in elevating the efficiency, sustainability, and livability of …
services, playing a crucial role in elevating the efficiency, sustainability, and livability of …
Profiling urban streets: A semi-supervised prediction model based on street view imagery and spatial topology
With the expansion and growth of cities, profiling urban areas with the advent of multi-modal
urban datasets (eg, points-of-interest and street view imagery) has become increasingly …
urban datasets (eg, points-of-interest and street view imagery) has become increasingly …
Geolocation representation from large language models are generic enhancers for spatio-temporal learning
In the geospatial domain, universal representation models are significantly less prevalent
than their extensive use in natural language processing and computer vision. This …
than their extensive use in natural language processing and computer vision. This …
Urbanclip: Learning text-enhanced urban region profiling with contrastive language-image pretraining from the web
Urban region profiling from web-sourced data is of utmost importance for urban computing.
We are witnessing a blossom of LLMs for various fields, especially in multi-modal data …
We are witnessing a blossom of LLMs for various fields, especially in multi-modal data …
Multi-temporal image analysis of wetland dynamics using machine learning algorithms
Wetlands play a crucial role in enhancing groundwater quality, mitigating natural hazards,
controlling erosion, and providing essential habitats for unique flora and wildlife. Despite …
controlling erosion, and providing essential habitats for unique flora and wildlife. Despite …