From Terrain to Space: A Survey on Multidomain Data Lifecycle for Urban Embodied Agents

Urban Embodied Agents (UrbanEAs) are emerging to actively interact with complex, large-scale city environments and generate vast, heterogeneous data streams, moving beyond the single-vehicle of existing autonomous driving. However, urban environments present distinct challenges, including environmental variability, limited observability, and interaction complexity. These challenges hinder the effectiveness of existing embodied agents, which have focused on controlled indoor environments, and expose the inherent limitations of relying on single-domain data. Therefore, establishing a comprehensive data lifecycle to fuse multidomain data from terrain, aerial, and space is a strategy for developing actionable embodied capabilities from raw urban streams. Distinct from existing surveys that follow a model-centric paradigm for urban computing or autonomous driving, we systematically propose and review a comprehensive Data Lifecycle from a multidomain data perspective, which is critical for the UrbanEA. First, we propose a unified framework containing four key stages of this lifecycle: Data Perception, Data Management, Data Modeling, and Task Application. Next, we establish a taxonomy for each stage of the lifecycle. Specifically, we detail the evolution from static data storage to active agent memory, and analyze integration strategies designed to bridge multidomain gaps. We demonstrate how UrbanEAs empower downstream tasks, including Urban Scene Question-Answering (SQA), Vision-Language Navigation (VLN), and Human-Agent Collaboration (HAC). Finally, we outline the social impact of the data lifecycle of UrbanEA and open research problems with the future directions. Our survey provides a roadmap for designing the robust, high-performance data frameworks essential for these UrbanEAs.