2

PolyRoad: Polyline Transformer for Topological Road-Boundary Detection

Topological road-boundary detection using remote sensing imagery plays a critical role in creating high-definition (HD) maps and enabling autonomous driving. Previous approaches follow an iterative graph-growing paradigm for road-boundary extraction, …

An Optimized Edge-Focused Siamese Network for Monitoring New Illegal Buildings Using Satellite Images

Illegal construction is a common problem often encountered by cities with rapid development, which is hard to deal with for multiple reasons. Although these illegal buildings are primarily defined by laws and regulations, they still have physical …

A lightweight multi-layer perceptron for efficient multivariate time series forecasting

Efficient and effective multivariate time series (MTS) forecasting is critical for real-world applications, such as traffic management and energy dispatching. Most of the current deep learning studies (e.g., Spatio-Temporal Graph Neural Networks and …

Big Geodata Reveals Spatial Patterns of Built Environment Stocks Across and Within Cities in China

The patterns of material accumulation in buildings and infrastructure accompanied by rapid urbanization offer an important, yet hitherto largely missing stock perspective for facilitating urban system engineering and informing urban resources, waste, …

Characterizing the temporally stable structure of community evolution in intra-urban origin-destination networks

Intra-urban origin-destination (OD) network communities evolve throughout the day, indicating changing groups of closely connected regions. Under such variation, groups of regions with high consistency of community affiliation characterize the …

Evaluating the impact of urban morphology on urban vitality: an exploratory study using big geo-data

The United Nations has proposed Sustainable Development Goals (SDGs), of which SDG11 aims to “make cities and human settlements inclusive, safe, resilient and sustainable”. This is in line with Urban Vitality's objectives. This study proposes a …

Examining active travel behavior through explainable machine learning: Insights from Beijing, China

Active travel, namely walking and cycling, is an eco-friendly and socially beneficial mode of sustainable transportation. However, existing research on active travel relies on limited survey data and generalized linear models. To fill the gap, our …

Investigating the effect of industry-specific economic distance on the prediction of intercity population movement

Intercity population movement has been extensively studied since it is closely related to human society. Currently, city industry structures play dominant roles in the direction of population movement. Yet, the extent to which different kinds of …

Spatiotemporal Fusion Transformer for large-scale traffic forecasting

The way humans travel and even their daily commute, is gradually expanding beyond the confines of counties and cities. Traffic between counties, cities, and even across the entire state is increasingly becoming a common aspect of daily activities. …

Streamlining trajectory map-matching: a framework leveraging spark and GPU-based stream processing

Real-time online trajectory map-matching has emerged as a critical component in the era of location-based services (LBS) and intelligent transportation systems (ITS). It refers to the process of aligning a user’s GPS trajectory data with the …