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 …
Beyond the first law of geography: Learning representations of satellite imagery by leveraging point-of-interests
Satellite imagery depicts the earth's surface remotely and provides comprehensive
information for many applications, such as land use monitoring and urban planning. Existing …
information for many applications, such as land use monitoring and urban planning. Existing …
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 …
Predicting multi-level socioeconomic indicators from structural urban imagery
Understanding economic development and designing government policies requires
accurate and timely measurements of socioeconomic activities. In this paper, we show how …
accurate and timely measurements of socioeconomic activities. In this paper, we show how …
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 …
UrbanVLP: A Multi-Granularity Vision-Language Pre-Trained Foundation Model for Urban Indicator Prediction
Urban indicator prediction aims to infer socio-economic metrics in diverse urban landscapes
using data-driven methods. However, prevalent pre-trained models, particularly those reliant …
using data-driven methods. However, prevalent pre-trained models, particularly those reliant …
MuseCL: Predicting Urban Socioeconomic Indicators via Multi-Semantic Contrastive Learning
X Yong, X Zhou - arXiv preprint arXiv:2407.09523, 2024 - arxiv.org
Predicting socioeconomic indicators within urban regions is crucial for fostering inclusivity,
resilience, and sustainability in cities and human settlements. While pioneering studies have …
resilience, and sustainability in cities and human settlements. While pioneering studies have …
Learning representations of satellite imagery by leveraging point-of-interests
Satellite imagery depicts the Earth's surface remotely and provides comprehensive
information for many applications, such as land use monitoring and urban planning. Existing …
information for many applications, such as land use monitoring and urban planning. Existing …
MOSS: A Large-scale Open Microscopic Traffic Simulation System
In the research of Intelligent Transportation Systems (ITS), traffic simulation is a key
procedure for the evaluation of new methods and optimization of strategies. However …
procedure for the evaluation of new methods and optimization of strategies. However …